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Posted to commits@hudi.apache.org by vi...@apache.org on 2019/03/13 22:41:03 UTC
[incubator-hudi-site] branch asf-site updated (97b3106 -> 3a9ffad)
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a change to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git.
from 97b3106 Refreshing site content
new aa361cc Simplifying site navigation
new 3a9ffad Minor edits
The 19 revisions listed above as "new" are entirely new to this
repository and will be described in separate emails. The revisions
listed as "add" were already present in the repository and have only
been added to this reference.
Summary of changes:
docs/_data/sidebars/mydoc_sidebar.yml | 35 ++-
docs/admin_guide.md | 18 +-
docs/community.md | 14 +-
docs/configurations.md | 54 ----
docs/implementation.md | 278 ---------------------
docs/performance.md | 94 +++++++
docs/{sql_queries.md => querying_data.md} | 4 +-
docs/quickstart.md | 19 +-
.../{incremental_processing.md => writing_data.md} | 4 +-
9 files changed, 142 insertions(+), 378 deletions(-)
delete mode 100644 docs/implementation.md
create mode 100644 docs/performance.md
rename docs/{sql_queries.md => querying_data.md} (98%)
rename docs/{incremental_processing.md => writing_data.md} (99%)
[incubator-hudi-site] 14/19: More documentation cleanup
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit d6b880af14907626f63b527e6461475204f04fda
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Thu Mar 7 11:01:35 2019 -0800
More documentation cleanup
- Fixing search keywords
- Added link to team page
- Fixed configuration page, specifically s3/gcs instructions
- Suggested using gists for sharing code on ML
---
docs/_data/topnav.yml | 3 +-
docs/_includes/head.html | 2 +-
docs/admin_guide.md | 2 +-
docs/community.md | 5 +-
docs/comparison.md | 5 +-
docs/concepts.md | 2 +-
docs/configurations.md | 110 +++++++++++++++++++++--------------------
docs/contributing.md | 2 +-
docs/gcs_filesystem.md | 4 +-
docs/implementation.md | 2 +-
docs/incremental_processing.md | 13 ++---
docs/index.md | 2 +-
docs/migration_guide.md | 2 +-
docs/pages/news/news.html | 2 +-
docs/powered_by.md | 5 +-
docs/privacy.md | 2 +-
docs/quickstart.md | 2 +-
docs/s3_filesystem.md | 8 ++-
docs/sql_queries.md | 2 +-
docs/use_cases.md | 3 +-
20 files changed, 87 insertions(+), 91 deletions(-)
diff --git a/docs/_data/topnav.yml b/docs/_data/topnav.yml
index 0042feb..3b9eca8 100644
--- a/docs/_data/topnav.yml
+++ b/docs/_data/topnav.yml
@@ -25,4 +25,5 @@ topnav_dropdowns:
external_url: https://issues.apache.org/jira/projects/HUDI/summary
- title: Blog
external_url: https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI
-
+ - title: Team
+ external_url: https://projects.apache.org/project.html?incubator-hudi
diff --git a/docs/_includes/head.html b/docs/_includes/head.html
index 9a6f74e..705c1c9 100644
--- a/docs/_includes/head.html
+++ b/docs/_includes/head.html
@@ -2,7 +2,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="{% if page.summary %}{{ page.summary | strip_html | strip_newlines | truncate: 160 }}{% endif %}">
-<meta name="keywords" content="{{page.tags}}{% if page.tags %}, {% endif %} {{page.keywords}}">
+<meta name="keywords" content="{{page.keywords}}">
<title>{{ page.title }} | {{ site.site_title }}</title>
<link rel="stylesheet" href="{{ "css/syntax.css" }}">
diff --git a/docs/admin_guide.md b/docs/admin_guide.md
index 3d37d22..7757d04 100644
--- a/docs/admin_guide.md
+++ b/docs/admin_guide.md
@@ -1,6 +1,6 @@
---
title: Admin Guide
-keywords: admin
+keywords: hudi, administration, operation, devops
sidebar: mydoc_sidebar
permalink: admin_guide.html
toc: false
diff --git a/docs/community.md b/docs/community.md
index c16dc92..5708f3d 100644
--- a/docs/community.md
+++ b/docs/community.md
@@ -1,6 +1,6 @@
---
title: Community
-keywords: usecases
+keywords: hudi, use cases, big data, apache
sidebar: mydoc_sidebar
toc: false
permalink: community.html
@@ -12,7 +12,7 @@ There are several ways to get in touch with the Hudi community.
| When? | Channel to use |
|-------|--------|
-| For any general questions, user support, development discussions | Dev Mailing list ([Subscribe](mailto:dev-subscribe@hudi.apache.org), [Unsubscribe](mailto:dev-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?dev@hudi.apache.org)). Empty email works for subscribe/unsubscribe |
+| For any general questions, user support, development discussions | Dev Mailing list ([Subscribe](mailto:dev-subscribe@hudi.apache.org), [Unsubscribe](mailto:dev-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?dev@hudi.apache.org)). Empty email works for subscribe/unsubscribe. Please use [gists](https://gist.github.com) to share code/stacktraces on the email. |
| For reporting bugs or issues or discover known issues | Please use [ASF Hudi JIRA](https://issues.apache.org/jira/projects/HUDI/summary) |
| For quick pings & 1-1 chats | Join our [slack group](https://join.slack.com/t/apache-hudi/signup) |
| For proposing large features, changes | Start a Hudi Improvement Process (HIP). Instructions coming soon.|
@@ -30,6 +30,7 @@ Here are few ways, you can get involved.
- Ask (and/or) answer questions on our support channels listed above.
- Review code or HIPs
- Help improve documentation
+ - Author blogs on our wiki
- Testing; Improving out-of-box experience by reporting bugs
- Share new ideas/directions to pursue or propose a new HIP
- Contributing code to the project
diff --git a/docs/comparison.md b/docs/comparison.md
index 36a2ec5..0862c26 100644
--- a/docs/comparison.md
+++ b/docs/comparison.md
@@ -1,6 +1,6 @@
---
title: Comparison
-keywords: usecases
+keywords: apache, hudi, kafka, kudu, hive, hbase, stream processing
sidebar: mydoc_sidebar
permalink: comparison.html
toc: false
@@ -56,6 +56,3 @@ More advanced use cases revolve around the concepts of [incremental processing](
uses Hudi even inside the `processing` engine to speed up typical batch pipelines. For e.g: Hudi can be used as a state store inside a processing DAG (similar
to how [rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend) is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam Runner](https://github.com/uber/hoodie/issues/8)
-
-
-
diff --git a/docs/concepts.md b/docs/concepts.md
index 845228a..7532631 100644
--- a/docs/concepts.md
+++ b/docs/concepts.md
@@ -1,6 +1,6 @@
---
title: Concepts
-keywords: concepts
+keywords: hudi, design, storage, views, timeline
sidebar: mydoc_sidebar
permalink: concepts.html
toc: false
diff --git a/docs/configurations.md b/docs/configurations.md
index e6602e6..ce45a3d 100644
--- a/docs/configurations.md
+++ b/docs/configurations.md
@@ -1,13 +1,67 @@
---
title: Configurations
-keywords: configurations
+keywords: garbage collection, hudi, jvm, configs, tuning
sidebar: mydoc_sidebar
permalink: configurations.html
toc: false
summary: "Here we list all possible configurations and what they mean"
---
-### Configuration
+
+#### Talking to Cloud Storage
+
+ * [AWS S3](s3_hoodie.html) <br/>
+ <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span>
+ * [Google Cloud Storage](gcs_hoodie.html) <br/>
+ <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span>
+
+#### Spark Datasource Configs
+
+* [Hoodie Datasource](#datasource) <br/>
+<span style="color:grey">Configs for datasource</span>
+ - [write options](#writeoptions) (write.format.option(...)) <br/>
+ <span style="color:grey"> Options useful for writing datasets </span>
+ - [OPERATION_OPT_KEY](#OPERATION_OPT_KEY) (Default: upsert) <br/>
+ <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span>
+ - [STORAGE_TYPE_OPT_KEY](#STORAGE_TYPE_OPT_KEY) (Default: COPY_ON_WRITE) <br/>
+ <span style="color:grey">The storage type for the underlying data, for this write. This can't change between writes.</span>
+ - [TABLE_NAME_OPT_KEY](#TABLE_NAME_OPT_KEY) (Default: None (mandatory)) <br/>
+ <span style="color:grey">Hive table name, to register the dataset into.</span>
+ - [PRECOMBINE_FIELD_OPT_KEY](#PRECOMBINE_FIELD_OPT_KEY) (Default: ts) <br/>
+ <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
+ we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span>
+ - [PAYLOAD_CLASS_OPT_KEY](#PAYLOAD_CLASS_OPT_KEY) (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br/>
+ <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
+ This will render any value set for `PRECOMBINE_FIELD_OPT_VAL` in-effective</span>
+ - [RECORDKEY_FIELD_OPT_KEY](#RECORDKEY_FIELD_OPT_KEY) (Default: uuid) <br/>
+ <span style="color:grey">Record key field. Value to be used as the `recordKey` component of `HoodieKey`. Actual value
+ will be obtained by invoking .toString() on the field value. Nested fields can be specified using
+ the dot notation eg: `a.b.c`</span>
+ - [PARTITIONPATH_FIELD_OPT_KEY](#PARTITIONPATH_FIELD_OPT_KEY) (Default: partitionpath) <br/>
+ <span style="color:grey">Partition path field. Value to be used at the `partitionPath` component of `HoodieKey`.
+ Actual value ontained by invoking .toString()</span>
+ - [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY) (Default: com.uber.hoodie.SimpleKeyGenerator) <br/>
+ <span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
+ - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: `_`) <br/>
+ <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
+ This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span>
+
+ - [read options](#readoptions) (read.format.option(...)) <br/>
+ <span style="color:grey">Options useful for reading datasets</span>
+ - [VIEW_TYPE_OPT_KEY](#VIEW_TYPE_OPT_KEY) (Default: = read_optimized) <br/>
+ <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
+ (or) Read Optimized mode (obtain latest view, based on columnar data)
+ (or) Real time mode (obtain latest view, based on row & columnar data)</span>
+ - [BEGIN_INSTANTTIME_OPT_KEY](#BEGIN_INSTANTTIME_OPT_KEY) (Default: None (Mandatory in incremental mode)) <br/>
+ <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
+ necessarily correspond to an instant on the timeline. New data written with an
+ `instant_time > BEGIN_INSTANTTIME` are fetched out. For e.g: '20170901080000' will get
+ all new data written after Sep 1, 2017 08:00AM.</span>
+ - [END_INSTANTTIME_OPT_KEY](#END_INSTANTTIME_OPT_KEY) (Default: latest instant (i.e fetches all new data since begin instant time)) <br/>
+ <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
+ `instant_time <= END_INSTANTTIME` are fetched out.</span>
+
+#### Write Client Configuration
* [HoodieWriteConfig](#HoodieWriteConfig) <br/>
<span style="color:grey">Top Level Config which is passed in when HoodieWriteClent is created.</span>
@@ -105,58 +159,8 @@ summary: "Here we list all possible configurations and what they mean"
- [withMaxMemorySizePerCompactionInBytes](#withMaxMemorySizePerCompactionInBytes) (maxMemorySizePerCompactionInBytes = 1GB) <br/>
<span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span>
- - [S3Configs](s3_hoodie.html) (Hoodie S3 Configs) <br/>
- <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span>
-
- - [GCSConfigs](gcs_hoodie.html) (Hoodie GCS Configs) <br/>
- <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span>
-
-* [Hoodie Datasource](#datasource) <br/>
-<span style="color:grey">Configs for datasource</span>
- - [write options](#writeoptions) (write.format.option(...)) <br/>
- <span style="color:grey"> Options useful for writing datasets </span>
- - [OPERATION_OPT_KEY](#OPERATION_OPT_KEY) (Default: upsert) <br/>
- <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span>
- - [STORAGE_TYPE_OPT_KEY](#STORAGE_TYPE_OPT_KEY) (Default: COPY_ON_WRITE) <br/>
- <span style="color:grey">The storage type for the underlying data, for this write. This can't change between writes.</span>
- - [TABLE_NAME_OPT_KEY](#TABLE_NAME_OPT_KEY) (Default: None (mandatory)) <br/>
- <span style="color:grey">Hive table name, to register the dataset into.</span>
- - [PRECOMBINE_FIELD_OPT_KEY](#PRECOMBINE_FIELD_OPT_KEY) (Default: ts) <br/>
- <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
- we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span>
- - [PAYLOAD_CLASS_OPT_KEY](#PAYLOAD_CLASS_OPT_KEY) (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br/>
- <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
- This will render any value set for `PRECOMBINE_FIELD_OPT_VAL` in-effective</span>
- - [RECORDKEY_FIELD_OPT_KEY](#RECORDKEY_FIELD_OPT_KEY) (Default: uuid) <br/>
- <span style="color:grey">Record key field. Value to be used as the `recordKey` component of `HoodieKey`. Actual value
- will be obtained by invoking .toString() on the field value. Nested fields can be specified using
- the dot notation eg: `a.b.c`</span>
- - [PARTITIONPATH_FIELD_OPT_KEY](#PARTITIONPATH_FIELD_OPT_KEY) (Default: partitionpath) <br/>
- <span style="color:grey">Partition path field. Value to be used at the `partitionPath` component of `HoodieKey`.
- Actual value ontained by invoking .toString()</span>
- - [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY) (Default: com.uber.hoodie.SimpleKeyGenerator) <br/>
- <span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
- - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: `_`) <br/>
- <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
- This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span>
-
- - [read options](#readoptions) (read.format.option(...)) <br/>
- <span style="color:grey">Options useful for reading datasets</span>
- - [VIEW_TYPE_OPT_KEY](#VIEW_TYPE_OPT_KEY) (Default: = read_optimized) <br/>
- <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
- (or) Read Optimized mode (obtain latest view, based on columnar data)
- (or) Real time mode (obtain latest view, based on row & columnar data)</span>
- - [BEGIN_INSTANTTIME_OPT_KEY](#BEGIN_INSTANTTIME_OPT_KEY) (Default: None (Mandatory in incremental mode)) <br/>
- <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
- necessarily correspond to an instant on the timeline. New data written with an
- `instant_time > BEGIN_INSTANTTIME` are fetched out. For e.g: '20170901080000' will get
- all new data written after Sep 1, 2017 08:00AM.</span>
- - [END_INSTANTTIME_OPT_KEY](#END_INSTANTTIME_OPT_KEY) (Default: latest instant (i.e fetches all new data since begin instant time)) <br/>
- <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
- `instant_time <= END_INSTANTTIME` are fetched out.</span>
-
-### Tuning
+#### Tuning
Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
diff --git a/docs/contributing.md b/docs/contributing.md
index a93ba54..028ab00 100644
--- a/docs/contributing.md
+++ b/docs/contributing.md
@@ -1,6 +1,6 @@
---
title: Developer Setup
-keywords: developer setup
+keywords: hudi, ide, developer, setup
sidebar: mydoc_sidebar
toc: false
permalink: contributing.html
diff --git a/docs/gcs_filesystem.md b/docs/gcs_filesystem.md
index c94cb66..8cc82da 100644
--- a/docs/gcs_filesystem.md
+++ b/docs/gcs_filesystem.md
@@ -1,12 +1,12 @@
---
title: GCS Filesystem (experimental)
-keywords: sql hive gcs spark presto
+keywords: hudi, hive, google cloud, storage, spark, presto
sidebar: mydoc_sidebar
permalink: gcs_hoodie.html
toc: false
summary: In this page, we go over how to configure hudi with Google Cloud Storage.
---
-Hudi works with HDFS by default and GCS **regional** buckets provide an HDFS API with strong consistency.
+For Hudi storage on GCS, **regional** buckets provide an HDFS API with strong consistency.
## GCS Configs
diff --git a/docs/implementation.md b/docs/implementation.md
index e87a541..cbf394e 100644
--- a/docs/implementation.md
+++ b/docs/implementation.md
@@ -1,6 +1,6 @@
---
title: Implementation
-keywords: implementation
+keywords: hudi, index, storage, compaction, cleaning, implementation
sidebar: mydoc_sidebar
toc: false
permalink: implementation.html
diff --git a/docs/incremental_processing.md b/docs/incremental_processing.md
index c2afad6..7c97cc9 100644
--- a/docs/incremental_processing.md
+++ b/docs/incremental_processing.md
@@ -1,6 +1,6 @@
---
title: Incremental Processing
-keywords: incremental processing
+keywords: hudi, incremental, batch, stream, processing, Hive, ETL, Spark SQL
sidebar: mydoc_sidebar
permalink: incremental_processing.html
toc: false
@@ -86,10 +86,10 @@ Usage: <main class> [options]
* --target-table
name of the target table in Hive
--transformer-class
- subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
- transform raw source dataset to a target dataset (conforming to target
- schema) before writing. Default : Not set. E:g -
- com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
+ subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
+ transform raw source dataset to a target dataset (conforming to target
+ schema) before writing. Default : Not set. E:g -
+ com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
allows a SQL query template to be passed as a transformation function)
```
@@ -233,6 +233,3 @@ Setting the fromCommitTime=0 and maxCommits=-1 will pull in the entire source da
then the utility can determine if the target dataset has no commits or is behind more than 24 hour (this is configurable),
it will automatically use the backfill configuration, since applying the last 24 hours incrementally could take more time than doing a backfill. The current limitation of the tool
is the lack of support for self-joining the same table in mixed mode (normal and incremental modes).
-
-
-
diff --git a/docs/index.md b/docs/index.md
index ad87933..22e1174 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,6 +1,6 @@
---
title: What is Hudi?
-keywords: homepage
+keywords: big data, stream processing, cloud, hdfs, storage, upserts, change capture
tags: [getting_started]
sidebar: mydoc_sidebar
permalink: index.html
diff --git a/docs/migration_guide.md b/docs/migration_guide.md
index 13c27ac..f785251 100644
--- a/docs/migration_guide.md
+++ b/docs/migration_guide.md
@@ -1,6 +1,6 @@
---
title: Migration Guide
-keywords: migration guide
+keywords: hudi, migration, use case
sidebar: mydoc_sidebar
permalink: migration_guide.html
toc: false
diff --git a/docs/pages/news/news.html b/docs/pages/news/news.html
index cb3d5d0..e1428da 100644
--- a/docs/pages/news/news.html
+++ b/docs/pages/news/news.html
@@ -1,7 +1,7 @@
---
title: News
sidebar: home_sidebar
-keywords: news, blog, updates, release notes, announcements
+keywords: apache, hudi, news, blog, updates, release notes, announcements
permalink: news.html
toc: false
folder: news
diff --git a/docs/powered_by.md b/docs/powered_by.md
index e79d05e..3d63509 100644
--- a/docs/powered_by.md
+++ b/docs/powered_by.md
@@ -1,6 +1,6 @@
---
title: Talks & Powered By
-keywords: talks
+keywords: hudi, talks, presentation
sidebar: mydoc_sidebar
permalink: powered_by.html
toc: false
@@ -32,9 +32,8 @@ It also powers several incremental Hive ETL pipelines and being currently integr
5. ["Hudi: Large-Scale, Near Real-Time Pipelines at Uber"](https://databricks
.com/session/hudi-near-real-time-spark-pipelines-at-petabyte-scale) - By Vinoth Chander & Nishith Agarwal
October 2018, Spark+AI Summit Europe, London, UK
-
+
## Articles
1. ["The Case for incremental processing on Hadoop"](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop) - O'reilly Ideas article by Vinoth Chandar
2. ["Hoodie: Uber Engineering's Incremental Processing Framework on Hadoop"](https://eng.uber.com/hoodie/) - Engineering Blog By Prasanna Rajaperumal
-
diff --git a/docs/privacy.md b/docs/privacy.md
index 32fcb91..c7e8de2 100644
--- a/docs/privacy.md
+++ b/docs/privacy.md
@@ -1,6 +1,6 @@
---
title: Privacy Policy
-keywords: privacy
+keywords: hudi, privacy
sidebar: mydoc_sidebar
permalink: privacy.html
---
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 1e6fa49..5a9193a 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -1,6 +1,6 @@
---
title: Quickstart
-keywords: quickstart
+keywords: hudi, quickstart
tags: [quickstart]
sidebar: mydoc_sidebar
toc: false
diff --git a/docs/s3_filesystem.md b/docs/s3_filesystem.md
index 6138821..9bbe068 100644
--- a/docs/s3_filesystem.md
+++ b/docs/s3_filesystem.md
@@ -1,18 +1,18 @@
---
title: S3 Filesystem (experimental)
-keywords: sql hive s3 spark presto
+keywords: hudi, hive, aws, s3, spark, presto
sidebar: mydoc_sidebar
permalink: s3_hoodie.html
toc: false
summary: In this page, we go over how to configure Hudi with S3 filesystem.
---
-Hudi works with HDFS by default. There is an experimental work going on Hoodie-S3 compatibility.
+In this page, we explain how to get your Hudi spark job to store into AWS S3.
## AWS configs
There are two configurations required for Hoodie-S3 compatibility:
-- Adding AWS Credentials for Hudi
+- Adding AWS Credentials for Hudi
- Adding required Jars to classpath
### AWS Credentials
@@ -75,5 +75,3 @@ AWS hadoop libraries to add to our classpath
- com.amazonaws:aws-java-sdk:1.10.34
- org.apache.hadoop:hadoop-aws:2.7.3
-
-
diff --git a/docs/sql_queries.md b/docs/sql_queries.md
index 44848eb..4fa795f 100644
--- a/docs/sql_queries.md
+++ b/docs/sql_queries.md
@@ -1,6 +1,6 @@
---
title: SQL Queries
-keywords: sql hive spark presto
+keywords: hudi, hive, spark, sql, presto
sidebar: mydoc_sidebar
permalink: sql_queries.html
toc: false
diff --git a/docs/use_cases.md b/docs/use_cases.md
index ed352f1..0040bc1 100644
--- a/docs/use_cases.md
+++ b/docs/use_cases.md
@@ -1,6 +1,6 @@
---
title: Use Cases
-keywords: usecases
+keywords: hudi, data ingestion, etl, real time, use cases
sidebar: mydoc_sidebar
permalink: use_cases.html
toc: false
@@ -74,4 +74,3 @@ A popular choice for this queue is Kafka and this model often results in __redun
Once again Hudi can efficiently solve this problem, by having the Spark Pipeline upsert output from
each run into a Hudi dataset, which can then be incrementally tailed (just like a Kafka topic) for new data & written into the serving store.
-
[incubator-hudi-site] 03/19: Merge pull request #1 from
n3nash/asf-site
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 3a2f6eea24f23bce9e1f73037b833bb592fabf3e
Merge: 6f02276 3799e69
Author: Suneel Marthi <sm...@apache.org>
AuthorDate: Mon Feb 11 22:09:26 2019 -0500
Merge pull request #1 from n3nash/asf-site
Initial commit with documentation
docs/.gitignore | 4 +
docs/404.md | 6 +
docs/Dockerfile | 26 +
docs/Gemfile | 10 +
docs/Gemfile.lock | 156 +
docs/_config.yml | 84 +
docs/_data/alerts.yml | 15 +
docs/_data/sidebars/mydoc_sidebar.yml | 66 +
docs/_data/strings.yml | 5 +
docs/_data/tags.yml | 10 +
docs/_data/topnav.yml | 30 +
docs/_includes/archive.html | 15 +
docs/_includes/callout.html | 1 +
docs/_includes/custom/getting_started_series.html | 19 +
.../custom/getting_started_series_next.html | 10 +
docs/_includes/custom/series_acme.html | 19 +
docs/_includes/custom/series_acme_next.html | 30 +
docs/_includes/custom/sidebarconfigs.html | 19 +
docs/_includes/custom/usermap.html | 14 +
docs/_includes/custom/usermapcomplex.html | 91 +
docs/_includes/disqus.html | 16 +
docs/_includes/feedback.html | 13 +
docs/_includes/footer.html | 9 +
docs/_includes/google_analytics.html | 6 +
docs/_includes/head.html | 47 +
docs/_includes/head_print.html | 33 +
docs/_includes/image.html | 1 +
docs/_includes/important.html | 1 +
docs/_includes/initialize_shuffle.html | 130 +
docs/_includes/inline_image.html | 1 +
docs/_includes/links.html | 44 +
docs/_includes/note.html | 1 +
docs/_includes/sidebar.html | 56 +
docs/_includes/taglogic.html | 32 +
docs/_includes/tip.html | 1 +
docs/_includes/toc.html | 21 +
docs/_includes/topnav.html | 75 +
docs/_includes/warning.html | 1 +
docs/_layouts/default.html | 80 +
docs/_layouts/default_print.html | 25 +
docs/_layouts/none.html | 3 +
docs/_layouts/page.html | 70 +
docs/_layouts/page_print.html | 15 +
docs/_layouts/post.html | 41 +
docs/_posts/2016-12-30-strata-talk-2017.md | 11 +
docs/admin_guide.md | 444 ++
docs/api_docs.md | 10 +
docs/code_and_design.md | 38 +
docs/community.md | 22 +
docs/comparison.md | 61 +
docs/concepts.md | 159 +
docs/configurations.md | 203 +
docs/css/bootstrap.min.css | 5 +
docs/css/customstyles.css | 1181 ++++
docs/css/font-awesome.min.css | 4 +
docs/css/fonts/FontAwesome.otf | Bin 0 -> 93888 bytes
docs/css/fonts/fontawesome-webfont.eot | Bin 0 -> 60767 bytes
docs/css/fonts/fontawesome-webfont.svg | 565 ++
docs/css/fonts/fontawesome-webfont.ttf | Bin 0 -> 122092 bytes
docs/css/fonts/fontawesome-webfont.woff | Bin 0 -> 71508 bytes
docs/css/fonts/fontawesome-webfont.woff2 | Bin 0 -> 56780 bytes
docs/css/lavish-bootstrap.css | 5898 ++++++++++++++++++++
docs/css/modern-business.css | 93 +
docs/css/printstyles.css | 160 +
docs/css/syntax.css | 60 +
docs/css/theme-blue.css | 103 +
docs/css/theme-green.css | 99 +
docs/dev_setup.md | 13 +
docs/feed.xml | 32 +
docs/fonts/FontAwesome.otf | Bin 0 -> 85908 bytes
docs/fonts/fontawesome-webfont.eot | Bin 0 -> 56006 bytes
docs/fonts/fontawesome-webfont.svg | 520 ++
docs/fonts/fontawesome-webfont.ttf | Bin 0 -> 112160 bytes
docs/fonts/fontawesome-webfont.woff | Bin 0 -> 65452 bytes
docs/fonts/glyphicons-halflings-regular.eot | Bin 0 -> 20127 bytes
docs/fonts/glyphicons-halflings-regular.svg | 288 +
docs/fonts/glyphicons-halflings-regular.ttf | Bin 0 -> 45404 bytes
docs/fonts/glyphicons-halflings-regular.woff | Bin 0 -> 23424 bytes
docs/fonts/glyphicons-halflings-regular.woff2 | Bin 0 -> 18028 bytes
docs/gcs_filesystem.md | 62 +
docs/images/androidsdkmanagericon.png | Bin 0 -> 795 bytes
docs/images/async_compac_1.png | Bin 0 -> 60344 bytes
docs/images/async_compac_2.png | Bin 0 -> 54164 bytes
docs/images/async_compac_3.png | Bin 0 -> 70516 bytes
docs/images/async_compac_4.png | Bin 0 -> 66932 bytes
docs/images/authorizegithubscreen2.png | Bin 0 -> 76388 bytes
docs/images/authorizeongithub.png | Bin 0 -> 22571 bytes
docs/images/company_logo.png | Bin 0 -> 3105 bytes
docs/images/company_logo_big.png | Bin 0 -> 9588 bytes
docs/images/favicon.ico | Bin 0 -> 1150 bytes
docs/images/helpapi-01.png | Bin 0 -> 91640 bytes
docs/images/helpapi.svg | 1661 ++++++
docs/images/hoodie_commit_duration.png | Bin 0 -> 869144 bytes
docs/images/hoodie_cow.png | Bin 0 -> 31136 bytes
docs/images/hoodie_intro_1.png | Bin 0 -> 23478 bytes
docs/images/hoodie_log_format_v2.png | Bin 0 -> 223676 bytes
docs/images/hoodie_mor.png | Bin 0 -> 56002 bytes
docs/images/hoodie_query_perf_hive.png | Bin 0 -> 158481 bytes
docs/images/hoodie_query_perf_presto.png | Bin 0 -> 33727 bytes
docs/images/hoodie_query_perf_spark.png | Bin 0 -> 29384 bytes
docs/images/hoodie_timeline.png | Bin 0 -> 23093 bytes
docs/images/hoodie_upsert_dag.png | Bin 0 -> 503771 bytes
docs/images/hoodie_upsert_perf1.png | Bin 0 -> 15984 bytes
docs/images/hoodie_upsert_perf2.png | Bin 0 -> 18954 bytes
docs/images/illustratoroptions.png | Bin 0 -> 118175 bytes
docs/images/itermexample.png | Bin 0 -> 68886 bytes
docs/images/jekyll.png | Bin 0 -> 5375 bytes
docs/images/killalljekyll.png | Bin 0 -> 66686 bytes
docs/images/liningup.png | Bin 0 -> 74728 bytes
docs/images/workflowarrow.png | Bin 0 -> 3595 bytes
docs/implementation.md | 275 +
docs/incremental_processing.md | 233 +
docs/index.md | 26 +
docs/js/customscripts.js | 55 +
docs/js/jekyll-search.js | 1 +
docs/js/jquery.ba-throttle-debounce.min.js | 9 +
docs/js/jquery.localScroll.min.js | 7 +
docs/js/jquery.navgoco.min.js | 8 +
docs/js/jquery.scrollTo.min.js | 7 +
docs/js/jquery.shuffle.min.js | 1588 ++++++
docs/js/mydoc_scroll.html | 240 +
docs/js/toc.js | 82 +
docs/licenses/LICENSE | 21 +
docs/licenses/LICENSE-BSD-NAVGOCO.txt | 27 +
docs/migration_guide.md | 71 +
docs/pages/news/news.html | 32 +
docs/pages/news/news_archive.html | 41 +
docs/powered_by.md | 40 +
docs/quickstart.md | 1247 +++++
docs/roadmap.md | 14 +
docs/s3_filesystem.md | 79 +
docs/search.json | 33 +
docs/sitemap.xml | 24 +
docs/sql_queries.md | 68 +
docs/use_cases.md | 77 +
135 files changed, 17349 insertions(+)
[incubator-hudi-site] 12/19: Revised community, contributing pages
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 94f64a7c7e8c8ec0307fbd78c5ec13ec0a7b9175
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Mon Feb 25 07:01:53 2019 -0800
Revised community, contributing pages
- Community engagement instructions
- Strawman contribution guide, to get us going
- Fixed broken image urls from the hudi renames
- Fixed broken code formatting on couple pages
- Removed api_setup, roadmap pages and cleaned up structure
---
.gitignore | 1 +
docs/README.md | 5 +
docs/_config.yml | 2 +-
docs/_data/topnav.yml | 24 ++-
docs/_includes/footer.html | 6 +
docs/_posts/2019-01-18-asf-incubation.md | 10 ++
docs/admin_guide.md | 22 ++-
docs/api_docs.md | 10 --
docs/code_and_design.md | 38 -----
docs/community.md | 38 +++--
docs/concepts.md | 28 ++--
docs/configurations.md | 38 +++--
docs/contributing.md | 101 +++++++++++++
docs/dev_setup.md | 13 --
docs/images/hoodie_cow.png | Bin 31136 -> 0 bytes
docs/images/hoodie_mor.png | Bin 56002 -> 0 bytes
docs/images/hudi_cow.png | Bin 0 -> 48994 bytes
docs/images/hudi_mor.png | Bin 0 -> 92073 bytes
.../{hoodie_timeline.png => hudi_timeline.png} | Bin
docs/implementation.md | 165 +++++++++++----------
docs/index.md | 7 +-
docs/migration_guide.md | 70 ++++-----
docs/quickstart.md | 89 +++++------
docs/roadmap.md | 14 --
docs/sql_queries.md | 5 +-
25 files changed, 383 insertions(+), 303 deletions(-)
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..e43b0f9
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+.DS_Store
diff --git a/docs/README.md b/docs/README.md
index 0995250..8593206 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -11,6 +11,11 @@ The site is based on a [Jekyll](https://jekyllrb.com/) theme hosted [here](idrat
Simply run `docker-compose build --no-cache && docker-compose up` from the `docs` folder and the site should be up & running at `http://localhost:4000`
+To see edits reflect on the site, you may have to bounce the container
+
+ - Stop existing container by `ctrl+c` the docker-compose program
+ - (or) alternatively via `docker stop docs_server_1`
+ - Bring up container again using `docker-compose up`
#### Host OS
diff --git a/docs/_config.yml b/docs/_config.yml
index 781bdb6..9f0effd 100644
--- a/docs/_config.yml
+++ b/docs/_config.yml
@@ -77,7 +77,7 @@ defaults:
sidebars:
- mydoc_sidebar
-description: "Apache Hudi (pronounced “Hoodie”) is a Spark Library, that provides upserts and incremental processing capaibilities on Hadoop datasets"
+description: "Apache Hudi (pronounced “Hoodie”) provides upserts and incremental processing capaibilities on Big Data"
# the description is used in the feed.xml file
# needed for sitemap.xml file only
diff --git a/docs/_data/topnav.yml b/docs/_data/topnav.yml
index 190573a..0042feb 100644
--- a/docs/_data/topnav.yml
+++ b/docs/_data/topnav.yml
@@ -7,24 +7,22 @@ topnav:
url: /news
- title: Community
url: /community.html
- - title: Github
+ - title: Code
external_url: https://github.com/uber/hoodie
#Topnav dropdowns
topnav_dropdowns:
- title: Topnav dropdowns
folders:
- - title: Developer Resources
+ - title: Developers
folderitems:
- - title: Setup
- url: /dev_setup.html
- output: web
- - title: API Docs
- url: /api_docs.html
- output: web
- - title: Code Structure
- url: /code_and_design.html
- output: web
- - title: Roadmap
- url: /roadmap.html
+ - title: Contributing
+ url: /contributing.html
output: web
+ - title: Wiki/Designs
+ external_url: https://cwiki.apache.org/confluence/display/HUDI
+ - title: Issues
+ external_url: https://issues.apache.org/jira/projects/HUDI/summary
+ - title: Blog
+ external_url: https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI
+
diff --git a/docs/_includes/footer.html b/docs/_includes/footer.html
index 00605db..c920c5c 100755
--- a/docs/_includes/footer.html
+++ b/docs/_includes/footer.html
@@ -8,6 +8,12 @@
<a class="footer-link-img" href="https://apache.org">
<img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
</p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the name of <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/docs/_posts/2019-01-18-asf-incubation.md b/docs/_posts/2019-01-18-asf-incubation.md
new file mode 100644
index 0000000..79de37c
--- /dev/null
+++ b/docs/_posts/2019-01-18-asf-incubation.md
@@ -0,0 +1,10 @@
+---
+title: "Hudi entered Apache Incubator"
+categories: update
+permalink: strata-talk.html
+tags: [news]
+---
+
+In the coming weeks, we will be moving in our new home on the Apache Incubator.
+
+{% include links.html %}
diff --git a/docs/admin_guide.md b/docs/admin_guide.md
index 7f7e610..3d37d22 100644
--- a/docs/admin_guide.md
+++ b/docs/admin_guide.md
@@ -43,7 +43,9 @@ hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1 --t
```
To see the description of hoodie table, use the command:
+
```
+
hoodie:hoodie_table_1->desc
18/09/06 15:57:19 INFO timeline.HoodieActiveTimeline: Loaded instants []
_________________________________________________________
@@ -55,6 +57,7 @@ hoodie:hoodie_table_1->desc
| hoodie.table.name | hoodie_table_1 |
| hoodie.table.type | COPY_ON_WRITE |
| hoodie.archivelog.folder| |
+
```
Following is a sample command to connect to a Hoodie dataset contains uber trips.
@@ -183,7 +186,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
| Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta Size| Delta Size - compaction scheduled| Delta Size - compaction unscheduled| Delta To Base Ratio - compaction scheduled| Delta To Base Ratio - compaction unscheduled| Delta Files - compaction scheduled | Delta Files - compaction unscheduled|
|========================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== [...]
| 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | 20.8 KB | 0.0 B | 0.0 B | 0.0 B | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]| [] |
-
+
hoodie:stock_ticks_mor->
```
@@ -224,7 +227,7 @@ This is a sequence file that contains a mapping from commitNumber => json with r
#### Compactions
-To get an idea of the lag between compaction and writer applications, use the below command to list down all
+To get an idea of the lag between compaction and writer applications, use the below command to list down all
pending compactions.
```
@@ -316,7 +319,7 @@ hoodie:stock_ticks_mor->compaction validate --instant 20181005222611
...
COMPACTION PLAN VALID
-
+
___________________________________________________________________________________________________________________________________________________________________________________________________________________________
| File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error|
|==========================================================================================================================================================================================================================|
@@ -340,14 +343,15 @@ hoodie:stock_ticks_mor->compaction validate --instant 20181005222601
The following commands must be executed without any other writer/ingestion application running.
-Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
-operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
+Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
+operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
so that are preserved. Hudi provides the following CLI to support it
##### UnScheduling Compaction
```
+
hoodie:trips->compaction unscheduleFileId --fileId <FileUUID>
....
No File renames needed to unschedule file from pending compaction. Operation successful.
@@ -356,24 +360,28 @@ No File renames needed to unschedule file from pending compaction. Operation suc
In other cases, an entire compaction plan needs to be reverted. This is supported by the following CLI
```
+
hoodie:trips->compaction unschedule --compactionInstant <compactionInstant>
.....
No File renames needed to unschedule pending compaction. Operation successful.
+
```
-
+
##### Repair Compaction
The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
-partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
+partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
`compaction validate`, you can notice invalid compaction operations if there is one. In these cases, the repair
command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
consistent with the compaction plan
```
+
hoodie:stock_ticks_mor->compaction repair --instant 20181005222611
......
Compaction successfully repaired
.....
+
```
diff --git a/docs/api_docs.md b/docs/api_docs.md
deleted file mode 100644
index 24bfd6b..0000000
--- a/docs/api_docs.md
+++ /dev/null
@@ -1,10 +0,0 @@
----
-title: API Docs
-keywords: usecases
-sidebar: mydoc_sidebar
-permalink: api_docs.html
----
-
-Work In Progress
-
-
diff --git a/docs/code_and_design.md b/docs/code_and_design.md
deleted file mode 100644
index 3baaa97..0000000
--- a/docs/code_and_design.md
+++ /dev/null
@@ -1,38 +0,0 @@
----
-title: Code Structure
-keywords: usecases
-sidebar: mydoc_sidebar
-permalink: code_and_design.html
----
-
-## Code & Project Structure
-
- * hoodie-client : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table
- * hoodie-common : Common code shared between different artifacts of Hoodie
-
- ## HoodieLogFormat
-
- The following diagram depicts the LogFormat for Hoodie MergeOnRead. Each logfile consists of one or more log blocks.
- Each logblock follows the format shown below.
-
- | Field | Description |
- |-------------- |------------------|
- | MAGIC | A magic header that marks the start of a block |
- | VERSION | The version of the LogFormat, this helps define how to switch between different log format as it evolves |
- | TYPE | The type of the log block |
- | HEADER LENGTH | The length of the headers, 0 if no headers |
- | HEADER | Metadata needed for a log block. For eg. INSTANT_TIME, TARGET_INSTANT_TIME, SCHEMA etc. |
- | CONTENT LENGTH | The length of the content of the log block |
- | CONTENT | The content of the log block, for example, for a DATA_BLOCK, the content is (number of records + actual records) in byte [] |
- | FOOTER LENGTH | The length of the footers, 0 if no footers |
- | FOOTER | Metadata needed for a log block. For eg. index entries, a bloom filter for records in a DATA_BLOCK etc. |
- | LOGBLOCK LENGTH | The total number of bytes written for a log block, typically the SUM(everything_above). This is a LONG. This acts as a reverse pointer to be able to traverse the log in reverse.|
-
-
- {% include image.html file="hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" %}
-
-
-
-
-
-
diff --git a/docs/community.md b/docs/community.md
index c508191..c16dc92 100644
--- a/docs/community.md
+++ b/docs/community.md
@@ -6,17 +6,35 @@ toc: false
permalink: community.html
---
+## Engage with us
+
+There are several ways to get in touch with the Hudi community.
+
+| When? | Channel to use |
+|-------|--------|
+| For any general questions, user support, development discussions | Dev Mailing list ([Subscribe](mailto:dev-subscribe@hudi.apache.org), [Unsubscribe](mailto:dev-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?dev@hudi.apache.org)). Empty email works for subscribe/unsubscribe |
+| For reporting bugs or issues or discover known issues | Please use [ASF Hudi JIRA](https://issues.apache.org/jira/projects/HUDI/summary) |
+| For quick pings & 1-1 chats | Join our [slack group](https://join.slack.com/t/apache-hudi/signup) |
+| For proposing large features, changes | Start a Hudi Improvement Process (HIP). Instructions coming soon.|
+| For stream of commits, pull requests etc | Commits Mailing list ([Subscribe](mailto:commits-subscribe@hudi.apache.org), [Unsubscribe](mailto:commits-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?commits@hudi.apache.org)) |
+
+If you wish to report a security vulnerability, please contact [security@apache.org](mailto:security@apache.org).
+Apache Hudi follows the typical Apache vulnerability handling [process](https://apache.org/security/committers.html#vulnerability-handling).
+
## Contributing
-We :heart: contributions. If you find a bug in the library or would like to add new features, go ahead and open
-issues or pull requests against this repo. Before you do so, please sign the
-[Apache CLA](https://www.apache.org/licenses/icla.pdf).
-Also, be sure to write unit tests for your bug fix or feature to show that it works as expected.
-If the reviewer feels this contributions needs to be in the release notes, please add it to CHANGELOG.md as well.
-If you want to participate in day-day conversations, please join our [slack group](https://join.slack.com/t/apache-hudi/signup).
-If you are from select pre-listed email domains, you can self signup. Others, please subscribe to dev@hudi.apache.org
+Apache Hudi community welcomes contributions from anyone!
+
+Here are few ways, you can get involved.
+
+ - Ask (and/or) answer questions on our support channels listed above.
+ - Review code or HIPs
+ - Help improve documentation
+ - Testing; Improving out-of-box experience by reporting bugs
+ - Share new ideas/directions to pursue or propose a new HIP
+ - Contributing code to the project
-## Becoming a Committer
+#### Code Contributions
-Hoodie has adopted a lot of guidelines set forth in [Google Chromium project](https://www.chromium.org/getting-involved/become-a-committer), to determine committership proposals. However, given this is a much younger project, we would have the contribution bar to be 10-15 non-trivial patches instead.
-Additionally, we expect active engagement with the community over a few months, in terms of conference/meetup talks, helping out with issues/questions on slack/github.
+Useful resources for contributing can be found under the "Developers" top menu.
+Specifically, please refer to the detailed [contribution guide](contributing.html).
diff --git a/docs/concepts.md b/docs/concepts.md
index 5ce3fc6..845228a 100644
--- a/docs/concepts.md
+++ b/docs/concepts.md
@@ -20,7 +20,7 @@ Such key activities include
* `COMMITS` - A single commit captures information about an **atomic write** of a batch of records into a dataset.
Commits are identified by a monotonically increasing timestamp, denoting the start of the write operation.
* `CLEANS` - Background activity that gets rid of older versions of files in the dataset, that are no longer needed.
- * `DELTA_COMMITS` - A single commit captures information about an **atomic write** of a batch of records into a
+ * `DELTA_COMMITS` - A single commit captures information about an **atomic write** of a batch of records into a
MergeOnRead storage type of dataset
* `COMPACTIONS` - Background activity to reconcile differential data structures within Hudi e.g: moving updates from row based log files to columnar formats.
@@ -37,15 +37,15 @@ only the changed files without say scanning all the time buckets > 07:00.
## Terminologies
- * `Hudi Dataset`
- A structured hive/spark dataset managed by Hudi. Hudi supports both partitioned and non-partitioned Hive tables.
- * `Commit`
- A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
+ * `Hudi Dataset`
+ A structured hive/spark dataset managed by Hudi. Hudi supports both partitioned and non-partitioned Hive tables.
+ * `Commit`
+ A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
published.
* `Commit Timeline`
- Commit Timeline refers to the sequence of Commits that was applied in order on a dataset over its lifetime.
- * `File Slice`
- Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
+ Commit Timeline refers to the sequence of Commits that was applied in order on a dataset over its lifetime.
+ * `File Slice`
+ Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
Hudi uses MVCC to provide atomicity and isolation of readers from a writer. This means that a logical fileId will
have many physical versions of it. Each of these physical version of a file represents a complete view of the
file as of a commit and is called File Slice
@@ -69,8 +69,6 @@ Hudi (will) supports the following storage types.
- Copy On Write : A heavily read optimized storage type, that simply creates new versions of files corresponding to the records that changed.
- Merge On Read : Also provides a near-real time datasets in the order of 5 mins, by shifting some of the write cost, to the reads and merging incoming and on-disk data on-the-fly
-{% include callout.html content="Hudi is a young project. merge-on-read is currently underway. Get involved [here](https://github.com/uber/Hudi/projects/1)" type="info" %}
-
Regardless of the storage type, Hudi organizes a datasets into a directory structure under a `basepath`,
very similar to Hive tables. Dataset is broken up into partitions, which are folders containing files for that partition.
Each partition uniquely identified by its `partitionpath`, which is relative to the basepath.
@@ -92,12 +90,12 @@ commit, such that only columnar data exists. As a result, the write amplificatio
Following illustrates how this works conceptually, when data written into copy-on-write storage and two queries running on top of it.
-{% include image.html file="Hudi_cow.png" alt="Hudi_cow.png" %}
+{% include image.html file="hudi_cow.png" alt="hudi_cow.png" %}
As data gets written, updates to existing file ids, produce a new version for that file id stamped with the commit and
inserts allocate a new file id and write its first version for that file id. These file versions and their commits are color coded above.
-Normal SQL queries running against such dataset (eg: select count(*) counting the total records in that partition), first checks the timeline for latest commit
+Normal SQL queries running against such dataset (eg: `select count(*)` counting the total records in that partition), first checks the timeline for latest commit
and filters all but latest versions of each file id. As you can see, an old query does not see the current inflight commit's files colored in pink,
but a new query starting after the commit picks up the new data. Thus queries are immune to any write failures/partial writes and only run on committed data.
@@ -118,7 +116,7 @@ their columnar base data, to keep the query performance in check (larger append
Following illustrates how the storage works, and shows queries on both near-real time table and read optimized table.
-{% include image.html file="Hudi_mor.png" alt="Hudi_mor.png" max-width="1000" %}
+{% include image.html file="hudi_mor.png" alt="hudi_mor.png" max-width="1000" %}
There are lot of interesting things happening in this example, which bring out the subleties in the approach.
@@ -135,8 +133,6 @@ There are lot of interesting things happening in this example, which bring out t
strategy, where we aggressively compact the latest partitions compared to older partitions, we could ensure the RO Table sees data
published within X minutes in a consistent fashion.
-{% include callout.html content="Hudi is a young project. merge-on-read is currently underway. Get involved [here](https://github.com/uber/hoodie/projects/1)" type="info" %}
-
The intention of merge on read storage, is to enable near real-time processing directly on top of Hadoop, as opposed to copying
data out to specialized systems, which may not be able to handle the data volume.
@@ -156,4 +152,4 @@ data out to specialized systems, which may not be able to handle the data volume
| Trade-off | ReadOptimized | RealTime |
|-------------- |------------------| ------------------|
| Data Latency | Higher | Lower |
-| Query Latency | Lower (raw columnar performance) | Higher (merge columnar + row based delta) |
\ No newline at end of file
+| Query Latency | Lower (raw columnar performance) | Higher (merge columnar + row based delta) |
diff --git a/docs/configurations.md b/docs/configurations.md
index 50a7e5f..e6602e6 100644
--- a/docs/configurations.md
+++ b/docs/configurations.md
@@ -136,7 +136,7 @@ summary: "Here we list all possible configurations and what they mean"
Actual value ontained by invoking .toString()</span>
- [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY) (Default: com.uber.hoodie.SimpleKeyGenerator) <br/>
<span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
- - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: _) <br/>
+ - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: `_`) <br/>
<span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span>
@@ -160,22 +160,33 @@ summary: "Here we list all possible configurations and what they mean"
Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
- - **Write operations** : Use `bulkinsert` to load new data into a table, and there on use `upsert`/`insert`.
+**Write operations** : Use `bulkinsert` to load new data into a table, and there on use `upsert`/`insert`.
Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.
- - **Input Parallelism** : By default, Hoodie tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
- - **Off-heap memory** : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
- - **Spark Memory** : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
- - **Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
- - **Timeseries/Log data** : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
+
+**Input Parallelism** : By default, Hoodie tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
+
+**Off-heap memory** : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
+
+**Spark Memory** : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
+
+**Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
+
+**Timeseries/Log data** : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
- Consider tuning the bloom filter accuracy via `.bloomFilterFPP()/bloomFilterNumEntries()` to achieve your target index look up time
- Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.
- - **GC Tuning** : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
- - [Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions : ``-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/ho [...]
- - If it keeps OOMing still, reduce spark memory conservatively: `spark.memory.fraction=0.2, spark.memory.storageFraction=0.2` allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)
- Below is a full working production config
+**GC Tuning** : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
+[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions :
- ```
+```
+-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+````
+
+If it keeps OOMing still, reduce spark memory conservatively: `spark.memory.fraction=0.2, spark.memory.storageFraction=0.2` allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)
+
+Below is a full working production config
+
+```
spark.driver.extraClassPath /etc/hive/conf
spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
spark.driver.maxResultSize 2g
@@ -200,4 +211,5 @@ Writing data via Hudi happens as a Spark job and thus general rules of spark deb
spark.yarn.driver.memoryOverhead 1024
spark.yarn.executor.memoryOverhead 3072
spark.yarn.max.executor.failures 100
- ```
+
+````
diff --git a/docs/contributing.md b/docs/contributing.md
new file mode 100644
index 0000000..a93ba54
--- /dev/null
+++ b/docs/contributing.md
@@ -0,0 +1,101 @@
+---
+title: Developer Setup
+keywords: developer setup
+sidebar: mydoc_sidebar
+toc: false
+permalink: contributing.html
+---
+## Pre-requisites
+
+To contribute code, you need
+
+ - a GitHub account
+ - a Linux (or) macOS development environment with Java JDK 8, Apache Maven (3.x+) installed
+ - [Docker](https://www.docker.com/) installed for running demo, integ tests or building website
+ - for large contributions, a signed [Individual Contributor License
+ Agreement](https://www.apache.org/licenses/icla.pdf) (ICLA) to the Apache
+ Software Foundation (ASF).
+ - (Recommended) Create an account on [JIRA](https://issues.apache.org/jira/projects/HUDI/summary) to open issues/find similar issues.
+ - (Recommended) Join our dev mailing list & slack channel, listed on [community](community.html) page.
+
+
+## IDE Setup
+
+To contribute, you would need to fork the Hudi code on Github & then clone your own fork locally. Once cloned, we recommend building as per instructions on [quickstart](quickstart.html)
+
+We have embraced the code style largely based on [google format](https://google.github.io/styleguide/javaguide.html). Please setup your IDE with style files from [here](../style/).
+These instructions have been tested on IntelliJ. We also recommend setting up the [Save Action Plugin](https://plugins.jetbrains.com/plugin/7642-save-actions) to auto format & organize imports on save. The Maven Compilation life-cycle will fail if there are checkstyle violations.
+
+
+## Lifecycle
+
+Here's a typical lifecycle of events to contribute to Hudi.
+
+ - [Recommended] Share your intent on the mailing list, so that community can provide early feedback, point out any similar JIRAs or HIPs.
+ - [Optional] If you want to get involved, but don't have a project in mind, please check JIRA for small, quick-starters.
+ - [Optional] Familiarize yourself with internals of Hudi using content on this page, as well as [wiki](https://cwiki.apache.org/confluence/display/HUDI)
+ - Once you finalize on a project/task, please open a new JIRA or assign an existing one to yourself. (If you don't have perms to do this, please email the dev mailing list with your JIRA id and a small intro for yourself. We'd be happy to add you as a contributor)
+ - Make your code change
+ - Every source file needs to include the Apache license header. Every new dependency needs to
+ have an open source license [compatible](https://www.apache.org/legal/resolved.html#criteria) with Apache.
+ - Get existing tests to pass using `mvn clean install -DskipITs`
+ - Add adequate tests for your new functionality
+ - [Optional] For involved changes, its best to also run the entire integration test suite using `mvn clean install`
+ - For website changes, please build the site locally & test navigation, formatting & links thoroughly
+ - Format commit messages and the pull request title like `[HUDI-XXX] Fixes bug in Spark Datasource`,
+ where you replace HUDI-XXX with the appropriate JIRA issue.
+ - Push your commit to your own fork/branch & create a pull request (PR) against the Hudi repo.
+ - If you don't hear back within 3 days on the PR, please send an email to dev @ mailing list.
+ - Address code review comments & keep pushing changes to your fork/branch, which automatically updates the PR
+ - Before your change can be merged, it should be squashed into a single commit for cleaner commit history.
+
+
+## Releases
+
+ - Apache Hudi community plans to do minor version releases every 6 weeks or so.
+ - If your contribution merged onto `master` branch after the last release, it will become part of next release.
+ - Website changes are regenerated once a week (until automation in place to reflect immediately)
+
+
+## Accounts and Permissions
+
+ - [Hudi issue tracker (JIRA)](https://issues.apache.org/jira/projects/HUDI/issues):
+ Anyone can access it and browse issues. Anyone can register an account and login
+ to create issues or add comments. Only contributors can be assigned issues. If
+ you want to be assigned issues, a PMC member can add you to the project contributor
+ group. Email the dev mailing list to ask to be added as a contributor, and include your ASF Jira username.
+
+ - [Hudi Wiki Space](https://cwiki.apache.org/confluence/display/HUDI):
+ Anyone has read access. If you wish to contribute changes, please create an account and
+ request edit access on the dev@ mailing list (include your Wiki account user ID).
+
+ - Pull requests can only be merged by a HUDI committer, listed [here](https://incubator.apache.org/projects/hudi.html)
+
+ - [Voting on a release](https://www.apache.org/foundation/voting.html): Everyone can vote.
+ Only Hudi PMC members should mark their votes as binding.
+
+## Communication
+
+All communication is expected to align with the [Code of Conduct](https://www.apache.org/foundation/policies/conduct).
+Discussion about contributing code to Hudi happens on the [dev@ mailing list](community.html). Introduce yourself!
+
+
+## Code & Project Structure
+
+ * `docker` : Docker containers used by demo and integration tests. Brings up a mini data ecosystem locally
+ * `hoodie-cli` : CLI to inspect, manage and administer datasets
+ * `hoodie-client` : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table
+ * `hoodie-common` : Common classes used across modules
+ * `hoodie-hadoop-mr` : InputFormat implementations for ReadOptimized, Incremental, Realtime views
+ * `hoodie-hive` : Manage hive tables off Hudi datasets and houses the HiveSyncTool
+ * `hoodie-integ-test` : Longer running integration test processes
+ * `hoodie-spark` : Spark datasource for writing and reading Hudi datasets. Streaming sink.
+ * `hoodie-utilities` : Houses tools like DeltaStreamer, SnapshotCopier
+ * `packaging` : Poms for building out bundles for easier drop in to Spark, Hive, Presto
+ * `style` : Code formatting, checkstyle files
+
+
+## Website
+
+[Apache Hudi site](https://hudi.apache.org) is hosted on a special `asf-site` branch. Please follow the `README` file under `docs` on that branch for
+instructions on making changes to the website.
diff --git a/docs/dev_setup.md b/docs/dev_setup.md
deleted file mode 100644
index 1bdeec7..0000000
--- a/docs/dev_setup.md
+++ /dev/null
@@ -1,13 +0,0 @@
----
-title: Developer Setup
-keywords: developer setup
-sidebar: mydoc_sidebar
-permalink: dev_setup.html
----
-
-### Code Style
-
- We have embraced the code style largely based on [google format](https://google.github.io/styleguide/javaguide.html).
- Please setup your IDE with style files from [here](../style/)
- We also recommend setting up the [Save Action Plugin](https://plugins.jetbrains.com/plugin/7642-save-actions) to auto format & organize imports on save.
- The Maven Compilation life-cycle will fail if there are checkstyle violations.
diff --git a/docs/images/hoodie_cow.png b/docs/images/hoodie_cow.png
deleted file mode 100644
index bad15a8..0000000
Binary files a/docs/images/hoodie_cow.png and /dev/null differ
diff --git a/docs/images/hoodie_mor.png b/docs/images/hoodie_mor.png
deleted file mode 100644
index 8d7d902..0000000
Binary files a/docs/images/hoodie_mor.png and /dev/null differ
diff --git a/docs/images/hudi_cow.png b/docs/images/hudi_cow.png
new file mode 100644
index 0000000..40aca71
Binary files /dev/null and b/docs/images/hudi_cow.png differ
diff --git a/docs/images/hudi_mor.png b/docs/images/hudi_mor.png
new file mode 100644
index 0000000..100b8f0
Binary files /dev/null and b/docs/images/hudi_mor.png differ
diff --git a/docs/images/hoodie_timeline.png b/docs/images/hudi_timeline.png
similarity index 100%
rename from docs/images/hoodie_timeline.png
rename to docs/images/hudi_timeline.png
diff --git a/docs/implementation.md b/docs/implementation.md
index 6215155..e87a541 100644
--- a/docs/implementation.md
+++ b/docs/implementation.md
@@ -23,7 +23,7 @@ Hudi upsert/insert is merely a Spark DAG, that can be broken into two big pieces
Hudi currently provides two choices for indexes : `BloomIndex` and `HBaseIndex` to map a record key into the file id to which it belongs to. This enables
us to speed up upserts significantly, without scanning over every record in the dataset. Hudi Indices can be classified based on
-their ability to lookup records across partition. A `global` index does not need partition information for finding the file-id for a record key
+their ability to lookup records across partition. A `global` index does not need partition information for finding the file-id for a record key
but a `non-global` does.
#### HBase Index (global)
@@ -63,8 +63,8 @@ records such that
In this storage, index updation is a no-op, since the bloom filters are already written as a part of committing data.
-In the case of Copy-On-Write, a single parquet file constitutes one `file slice` which contains one complete version of
-the file
+In the case of Copy-On-Write, a single parquet file constitutes one `file slice` which contains one complete version of
+the file
{% include image.html file="hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" max-width="1000" %}
@@ -73,27 +73,27 @@ the file
In the Merge-On-Read storage model, there are 2 logical components - one for ingesting data (both inserts/updates) into the dataset
and another for creating compacted views. The former is hereby referred to as `Writer` while the later
is referred as `Compactor`.
-
+
##### Merge On Read Writer
-
+
At a high level, Merge-On-Read Writer goes through same stages as Copy-On-Write writer in ingesting data.
- The key difference here is that updates are appended to latest log (delta) file belonging to the latest file slice
+ The key difference here is that updates are appended to latest log (delta) file belonging to the latest file slice
without merging. For inserts, Hudi supports 2 modes:
1. Inserts to Log Files - This is done for datasets that have an indexable log files (for eg global index)
2. Inserts to parquet files - This is done for datasets that do not have indexable log files, for eg bloom index
embedded in parquer files. Hudi treats writing new records in the same way as inserting to Copy-On-Write files.
-As in the case of Copy-On-Write, the input tagged records are partitioned such that all upserts destined to
+As in the case of Copy-On-Write, the input tagged records are partitioned such that all upserts destined to
a `file id` are grouped together. This upsert-batch is written as one or more log-blocks written to log-files.
Hudi allows clients to control log file sizes (See [Storage Configs](../configurations))
The WriteClient API is same for both Copy-On-Write and Merge-On-Read writers.
-
+
With Merge-On-Read, several rounds of data-writes would have resulted in accumulation of one or more log-files.
All these log-files along with base-parquet (if exists) constitute a `file slice` which represents one complete version
-of the file.
-
+of the file.
+
#### Compactor
Realtime Readers will perform in-situ merge of these delta log-files to provide the most recent (committed) view of
@@ -106,48 +106,52 @@ Asynchronous Compaction involves 2 steps:
to be compacted atomically in a single compaction commit. Hudi allows pluggable strategies for choosing
file slices for each compaction runs. This step is typically done inline by Writer process as Hudi expects
only one schedule is being generated at a time which allows Hudi to enforce the constraint that pending compaction
- plans do not step on each other file-slices. This constraint allows for multiple concurrent `Compactors` to run at
+ plans do not step on each other file-slices. This constraint allows for multiple concurrent `Compactors` to run at
the same time. Some of the common strategies used for choosing `file slice` for compaction are:
- * BoundedIO - Limit the number of file slices chosen for a compaction plan by expected total IO (read + write)
- needed to complete compaction run
+ * BoundedIO - Limit the number of file slices chosen for a compaction plan by expected total IO (read + write)
+ needed to complete compaction run
* Log File Size - Prefer file-slices with larger amounts of delta log data to be merged
* Day Based - Prefer file slice belonging to latest day partitions
- ```
- API for scheduling compaction
- /**
- * Schedules a new compaction instant
- * @param extraMetadata
- * @return Compaction Instant timestamp if a new compaction plan is scheduled
- */
- Optional<String> scheduleCompaction(Optional<Map<String, String>> extraMetadata) throws IOException;
- ```
+
* `Compactor` : Hudi provides a separate API in Write Client to execute a compaction plan. The compaction
plan (just like a commit) is identified by a timestamp. Most of the design and implementation complexities for Async
Compaction is for guaranteeing snapshot isolation to readers and writer when
multiple concurrent compactors are running. Typical compactor deployment involves launching a separate
spark application which executes pending compactions when they become available. The core logic of compacting
file slices in the Compactor is very similar to that of merging updates in a Copy-On-Write table. The only
- difference being in the case of compaction, there is an additional step of merging the records in delta log-files.
-
- Here are the main API to lookup and execute a compaction plan.
- ```
- Main API in HoodieWriteClient for running Compaction:
- /**
- * Performs Compaction corresponding to instant-time
- * @param compactionInstantTime Compaction Instant Time
- * @return
- * @throws IOException
- */
- public JavaRDD<WriteStatus> compact(String compactionInstantTime) throws IOException;
-
- To lookup all pending compactions, use the API defined in HoodieReadClient
-
- /**
- * Return all pending compactions with instant time for clients to decide what to compact next.
- * @return
- */
- public List<Pair<String, HoodieCompactionPlan>> getPendingCompactions();
- ```
+ difference being in the case of compaction, there is an additional step of merging the records in delta log-files.
+
+Here are the main API to lookup and execute a compaction plan.
+
+```
+ Main API in HoodieWriteClient for running Compaction:
+ /**
+ * Performs Compaction corresponding to instant-time
+ * @param compactionInstantTime Compaction Instant Time
+ * @return
+ * @throws IOException
+ */
+ public JavaRDD<WriteStatus> compact(String compactionInstantTime) throws IOException;
+
+ To lookup all pending compactions, use the API defined in HoodieReadClient
+
+ /**
+ * Return all pending compactions with instant time for clients to decide what to compact next.
+ * @return
+ */
+ public List<Pair<String, HoodieCompactionPlan>> getPendingCompactions();
+```
+API for scheduling compaction
+
+```
+
+ /**
+ * Schedules a new compaction instant
+ * @param extraMetadata
+ * @return Compaction Instant timestamp if a new compaction plan is scheduled
+ */
+ Optional<String> scheduleCompaction(Optional<Map<String, String>> extraMetadata) throws IOException;
+```
Refer to __hoodie-client/src/test/java/HoodieClientExample.java__ class for an example of how compaction
is scheduled and executed.
@@ -172,65 +176,65 @@ plan to be run to figure out the number of file slices being compacted and choos
## Async Compaction Design Deep-Dive (Optional)
-For the purpose of this section, it is important to distinguish between 2 types of commits as pertaining to the file-group:
+For the purpose of this section, it is important to distinguish between 2 types of commits as pertaining to the file-group:
A commit which generates a merged and read-optimized file-slice is called `snapshot commit` (SC) with respect to that file-group.
-A commit which merely appended the new/updated records assigned to the file-group into a new log block is called `delta commit` (DC)
+A commit which merely appended the new/updated records assigned to the file-group into a new log block is called `delta commit` (DC)
with respect to that file-group.
### Algorithm
The algorithm is described with an illustration. Let us assume a scenario where there are commits SC1, DC2, DC3 that have
-already completed on a data-set. Commit DC4 is currently ongoing with the writer (ingestion) process using it to upsert data.
-Let us also imagine there are a set of file-groups (FG1 … FGn) in the data-set whose latest version (`File-Slice`)
-contains the base file created by commit SC1 (snapshot-commit in columnar format) and a log file containing row-based
-log blocks of 2 delta-commits (DC2 and DC3).
+already completed on a data-set. Commit DC4 is currently ongoing with the writer (ingestion) process using it to upsert data.
+Let us also imagine there are a set of file-groups (FG1 … FGn) in the data-set whose latest version (`File-Slice`)
+contains the base file created by commit SC1 (snapshot-commit in columnar format) and a log file containing row-based
+log blocks of 2 delta-commits (DC2 and DC3).
{% include image.html file="async_compac_1.png" alt="async_compac_1.png" max-width="1000" %}
- * Writer (Ingestion) that is going to commit "DC4" starts. The record updates in this batch are grouped by file-groups
- and appended in row formats to the corresponding log file as delta commit. Let us imagine a subset of file-groups has
+ * Writer (Ingestion) that is going to commit "DC4" starts. The record updates in this batch are grouped by file-groups
+ and appended in row formats to the corresponding log file as delta commit. Let us imagine a subset of file-groups has
this new log block (delta commit) DC4 added.
- * Before the writer job completes, it runs the compaction strategy to decide which file-group to compact by compactor
- and creates a new compaction-request commit SC5. This commit file is marked as “requested” with metadata denoting
- which fileIds to compact (based on selection policy). Writer completes without running compaction (will be run async).
-
+ * Before the writer job completes, it runs the compaction strategy to decide which file-group to compact by compactor
+ and creates a new compaction-request commit SC5. This commit file is marked as “requested” with metadata denoting
+ which fileIds to compact (based on selection policy). Writer completes without running compaction (will be run async).
+
{% include image.html file="async_compac_2.png" alt="async_compac_2.png" max-width="1000" %}
-
- * Writer job runs again ingesting next batch. It starts with commit DC6. It reads the earliest inflight compaction
- request marker commit in timeline order and collects the (fileId, Compaction Commit Id “CcId” ) pairs from meta-data.
- Ingestion DC6 ensures a new file-slice with base-commit “CcId” gets allocated for the file-group.
- The Writer will simply append records in row-format to the first log-file (as delta-commit) assuming the
+
+ * Writer job runs again ingesting next batch. It starts with commit DC6. It reads the earliest inflight compaction
+ request marker commit in timeline order and collects the (fileId, Compaction Commit Id “CcId” ) pairs from meta-data.
+ Ingestion DC6 ensures a new file-slice with base-commit “CcId” gets allocated for the file-group.
+ The Writer will simply append records in row-format to the first log-file (as delta-commit) assuming the
base-file (“Phantom-Base-File”) will be created eventually by the compactor.
-
+
{% include image.html file="async_compac_3.png" alt="async_compac_3.png" max-width="1000" %}
-
- * Compactor runs at some time and commits at “Tc” (concurrently or before/after Ingestion DC6). It reads the commit-timeline
- and finds the first unprocessed compaction request marker commit. Compactor reads the commit’s metadata finding the
- file-slices to be compacted. It compacts the file-slice and creates the missing base-file (“Phantom-Base-File”)
- with “CCId” as the commit-timestamp. Compactor then marks the compaction commit timestamp as completed.
- It is important to realize that at data-set level, there could be different file-groups requesting compaction at
+
+ * Compactor runs at some time and commits at “Tc” (concurrently or before/after Ingestion DC6). It reads the commit-timeline
+ and finds the first unprocessed compaction request marker commit. Compactor reads the commit’s metadata finding the
+ file-slices to be compacted. It compacts the file-slice and creates the missing base-file (“Phantom-Base-File”)
+ with “CCId” as the commit-timestamp. Compactor then marks the compaction commit timestamp as completed.
+ It is important to realize that at data-set level, there could be different file-groups requesting compaction at
different commit timestamps.
-
+
{% include image.html file="async_compac_4.png" alt="async_compac_4.png" max-width="1000" %}
- * Near Real-time reader interested in getting the latest snapshot will have 2 cases. Let us assume that the
+ * Near Real-time reader interested in getting the latest snapshot will have 2 cases. Let us assume that the
incremental ingestion (writer at DC6) happened before the compaction (some time “Tc”’).
- The below description is with regards to compaction from file-group perspective.
- * `Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”`:
- Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
- merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
- a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
- For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
+ The below description is with regards to compaction from file-group perspective.
+ * `Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”`:
+ Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
+ merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
+ a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
+ For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
and merge on the fly.
- * `Reader querying at time after compaction finished (> “Tc”)` : In this case, reader will not find any pending
- compactions in the timeline and will simply have the current behavior of reading the latest file-slice and
+ * `Reader querying at time after compaction finished (> “Tc”)` : In this case, reader will not find any pending
+ compactions in the timeline and will simply have the current behavior of reading the latest file-slice and
merging on-the-fly.
-
- * Read-Optimized View readers will query against the latest columnar base-file for each file-groups.
+
+ * Read-Optimized View readers will query against the latest columnar base-file for each file-groups.
The above algorithm explains Async compaction w.r.t a single compaction run on a single file-group. It is important
-to note that multiple compaction plans can be run concurrently as they are essentially operating on different
+to note that multiple compaction plans can be run concurrently as they are essentially operating on different
file-groups.
## Performance
@@ -272,4 +276,3 @@ with no impact on queries. Following charts compare the Hudi vs non-Hudi dataset
**Presto**
{% include image.html file="hoodie_query_perf_presto.png" alt="hoodie_query_perf_presto.png" max-width="1000" %}
-
diff --git a/docs/index.md b/docs/index.md
index b5b9da7..ad87933 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -4,12 +4,9 @@ keywords: homepage
tags: [getting_started]
sidebar: mydoc_sidebar
permalink: index.html
-summary: "Hudi lowers data latency across the board, while simultaneously achieving orders of magnitude of efficiency over traditional batch processing."
+summary: "Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing."
---
-
-
-
Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud stores and provides three logical views for query access.
* **Read Optimized View** - Provides excellent query performance on pure columnar storage, much like plain [Parquet](https://parquet.apache.org/) tables.
@@ -21,4 +18,4 @@ Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical dat
By carefully managing how data is laid out in storage & how it’s exposed to queries, Hudi is able to power a rich data ecosystem where external sources can be ingested in near real-time and made available for interactive SQL Engines like [Presto](https://prestodb.io) & [Spark](https://spark.apache.org/sql/), while at the same time capable of being consumed incrementally from processing/ETL frameworks like [Hive](https://hive.apache.org/) & [Spark](https://spark.apache.org/docs/latest/) t [...]
-Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access.
+Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access. See [quickstart](quickstart.html) for a demo.
diff --git a/docs/migration_guide.md b/docs/migration_guide.md
index a5d5506..13c27ac 100644
--- a/docs/migration_guide.md
+++ b/docs/migration_guide.md
@@ -4,9 +4,8 @@ keywords: migration guide
sidebar: mydoc_sidebar
permalink: migration_guide.html
toc: false
-summary: In this page, we will discuss some available tools for migrating your existing dataset into a Hudi managed
-dataset
-
+summary: In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset
+---
Hudi maintains metadata such as commit timeline and indexes to manage a dataset. The commit timelines helps to understand the actions happening on a dataset as well as the current state of a dataset. Indexes are used by Hudi to maintain a record key to file id mapping to efficiently locate a record. At the moment, Hudi supports writing only parquet columnar formats.
To be able to start using Hudi for your existing dataset, you will need to migrate your existing dataset into a Hudi managed dataset. There are a couple of ways to achieve this.
@@ -15,57 +14,60 @@ To be able to start using Hudi for your existing dataset, you will need to migra
## Approaches
-### Approach 1
+#### Use Hudi for new partitions alone
-Hudi can be used to manage an existing dataset without affecting/altering the historical data already present in the
-dataset. Hudi has been implemented to be compatible with such a mixed dataset with a caveat that either the complete
-Hive partition is Hudi managed or not. Thus the lowest granularity at which Hudi manages a dataset is a Hive
-partition. Start using the datasource API or the WriteClient to write to the dataset and make sure you start writing
+Hudi can be used to manage an existing dataset without affecting/altering the historical data already present in the
+dataset. Hudi has been implemented to be compatible with such a mixed dataset with a caveat that either the complete
+Hive partition is Hudi managed or not. Thus the lowest granularity at which Hudi manages a dataset is a Hive
+partition. Start using the datasource API or the WriteClient to write to the dataset and make sure you start writing
to a new partition or convert your last N partitions into Hudi instead of the entire table. Note, since the historical
- partitions are not managed by HUDI, none of the primitives provided by HUDI work on the data in those partitions. More concretely, one cannot perform upserts or incremental pull on such older partitions not managed by the HUDI dataset.
+ partitions are not managed by HUDI, none of the primitives provided by HUDI work on the data in those partitions. More concretely, one cannot perform upserts or incremental pull on such older partitions not managed by the HUDI dataset.
Take this approach if your dataset is an append only type of dataset and you do not expect to perform any updates to existing (or non Hudi managed) partitions.
-### Approach 2
+#### Convert existing dataset to Hudi
Import your existing dataset into a Hudi managed dataset. Since all the data is Hudi managed, none of the limitations
- of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
- make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
+ of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
+ make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
there are other additional advantages of doing this. Hudi automatically manages file sizes of a Hudi managed dataset
- . You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
- adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
+ . You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
+ adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
small files rather than writing new small ones thus maintaining the health of your cluster.
There are a few options when choosing this approach.
+
#### Option 1
-Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
-parquet file
-format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.
-#### Option 2
+Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
+parquet file
+format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.
+
+#### Option 2
For huge datasets, this could be as simple as : for partition in [list of partitions in source dataset] {
val inputDF = spark.read.format("any_input_format").load("partition_path")
inputDF.write.format("com.uber.hoodie").option()....save("basePath")
}
+
#### Option 3
Write your own custom logic of how to load an existing dataset into a Hudi managed one. Please read about the RDD API
- [here](quickstart.md).
+ [here](quickstart.html).
```
-Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
+Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
-hoodie->hdfsparquetimport
- --upsert false
- --srcPath /user/parquet/dataset/basepath
- --targetPath
- /user/hoodie/dataset/basepath
- --tableName hoodie_table
- --tableType COPY_ON_WRITE
- --rowKeyField _row_key
- --partitionPathField partitionStr
- --parallelism 1500
- --schemaFilePath /user/table/schema
- --format parquet
- --sparkMemory 6g
+hoodie->hdfsparquetimport
+ --upsert false
+ --srcPath /user/parquet/dataset/basepath
+ --targetPath
+ /user/hoodie/dataset/basepath
+ --tableName hoodie_table
+ --tableType COPY_ON_WRITE
+ --rowKeyField _row_key
+ --partitionPathField partitionStr
+ --parallelism 1500
+ --schemaFilePath /user/table/schema
+ --format parquet
+ --sparkMemory 6g
--retry 2
-```
\ No newline at end of file
+```
diff --git a/docs/quickstart.md b/docs/quickstart.md
index f1516ae..1e6fa49 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -13,13 +13,14 @@ permalink: quickstart.html
Check out code and pull it into Intellij as a normal maven project.
Normally build the maven project, from command line
+
```
$ mvn clean install -DskipTests -DskipITs
+```
To work with older version of Hive (pre Hive-1.2.1), use
-
+```
$ mvn clean install -DskipTests -DskipITs -Dhive11
-
```
{% include callout.html content="You might want to add your spark jars folder to project dependencies under 'Module Setttings', to be able to run Spark from IDE" type="info" %}
@@ -31,13 +32,13 @@ $ mvn clean install -DskipTests -DskipITs -Dhive11
Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We have verified that Hudi works with the following combination of Hadoop/Hive/Spark.
-| Hadoop | Hive | Spark | Instructions to Build Hudi |
+| Hadoop | Hive | Spark | Instructions to Build Hudi |
| ---- | ----- | ---- | ---- |
| 2.6.0-cdh5.7.2 | 1.1.0-cdh5.7.2 | spark-2.[1-3].x | Use “mvn clean install -DskipTests -Dhadoop.version=2.6.0-cdh5.7.2 -Dhive.version=1.1.0-cdh5.7.2” |
| Apache hadoop-2.8.4 | Apache hive-2.3.3 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
| Apache hadoop-2.7.3 | Apache hive-1.2.1 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
-If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
+If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
It would be of great help if you can reach out to us with your setup and experience with hoodie.
## Generate a Hudi Dataset
@@ -60,7 +61,7 @@ export PATH=$JAVA_HOME/bin:$HIVE_HOME/bin:$HADOOP_HOME/bin:$SPARK_INSTALL/bin:$P
### Supported API's
-Use the DataSource API to quickly start reading or writing Hudi datasets in few lines of code. Ideal for most
+Use the DataSource API to quickly start reading or writing Hudi datasets in few lines of code. Ideal for most
ingestion use-cases.
Use the RDD API to perform more involved actions on a Hudi dataset
@@ -132,11 +133,11 @@ This can be run as frequently as the ingestion pipeline to make sure new partiti
cd hoodie-hive
./run_sync_tool.sh
--user hive
- --pass hive
- --database default
- --jdbc-url "jdbc:hive2://localhost:10010/"
- --base-path tmp/hoodie/sample-table/
- --table hoodie_test
+ --pass hive
+ --database default
+ --jdbc-url "jdbc:hive2://localhost:10010/"
+ --base-path tmp/hoodie/sample-table/
+ --table hoodie_test
--partitioned-by field1,field2
```
@@ -304,7 +305,7 @@ hive>
## A Demo using docker containers
Lets use a real world example to see how hudi works end to end. For this purpose, a self contained
-data infrastructure is brought up in a local docker cluster within your computer.
+data infrastructure is brought up in a local docker cluster within your computer.
The steps assume you are using Mac laptop
@@ -313,7 +314,7 @@ The steps assume you are using Mac laptop
* Docker Setup : For Mac, Please follow the steps as defined in [https://docs.docker.com/v17.12/docker-for-mac/install/]. For running Spark-SQL queries, please ensure atleast 6 GB and 4 CPUs are allocated to Docker (See Docker -> Preferences -> Advanced). Otherwise, spark-SQL queries could be killed because of memory issues.
* kafkacat : A command-line utility to publish/consume from kafka topics. Use `brew install kafkacat` to install kafkacat
* /etc/hosts : The demo references many services running in container by the hostname. Add the following settings to /etc/hosts
-
+
```
127.0.0.1 adhoc-1
127.0.0.1 adhoc-2
@@ -378,15 +379,15 @@ At this point, the docker cluster will be up and running. The demo cluster bring
* HDFS Services (NameNode, DataNode)
* Spark Master and Worker
* Hive Services (Metastore, HiveServer2 along with PostgresDB)
- * Kafka Broker and a Zookeeper Node (Kakfa will be used as upstream source for the demo)
+ * Kafka Broker and a Zookeeper Node (Kakfa will be used as upstream source for the demo)
* Adhoc containers to run Hudi/Hive CLI commands
### Demo
-Stock Tracker data will be used to showcase both different Hudi Views and the effects of Compaction.
+Stock Tracker data will be used to showcase both different Hudi Views and the effects of Compaction.
-Take a look at the directory `docker/demo/data`. There are 2 batches of stock data - each at 1 minute granularity.
-The first batch contains stocker tracker data for some stock symbols during the first hour of trading window
+Take a look at the directory `docker/demo/data`. There are 2 batches of stock data - each at 1 minute granularity.
+The first batch contains stocker tracker data for some stock symbols during the first hour of trading window
(9:30 a.m to 10:30 a.m). The second batch contains tracker data for next 30 mins (10:30 - 11 a.m). Hudi will
be used to ingest these batches to a dataset which will contain the latest stock tracker data at hour level granularity.
The batches are windowed intentionally so that the second batch contains updates to some of the rows in the first batch.
@@ -396,7 +397,7 @@ The batches are windowed intentionally so that the second batch contains updates
Upload the first batch to Kafka topic 'stock ticks'
```
-cat docker/demo/data/batch_1.json | kafkacat -b kafkabroker -t stock_ticks -P
+cat docker/demo/data/batch_1.json | kafkacat -b kafkabroker -t stock_ticks -P
To check if the new topic shows up, use
kafkacat -b kafkabroker -L -J | jq .
@@ -443,7 +444,7 @@ kafkacat -b kafkabroker -L -J | jq .
Hudi comes with a tool named DeltaStreamer. This tool can connect to variety of data sources (including Kafka) to
pull changes and apply to Hudi dataset using upsert/insert primitives. Here, we will use the tool to download
-json data from kafka topic and ingest to both COW and MOR tables we initialized in the previous step. This tool
+json data from kafka topic and ingest to both COW and MOR tables we initialized in the previous step. This tool
automatically initializes the datasets in the file-system if they do not exist yet.
```
@@ -468,8 +469,8 @@ spark-submit --class com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer
exit
```
-You can use HDFS web-browser to look at the datasets
-`http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow`.
+You can use HDFS web-browser to look at the datasets
+`http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow`.
You can explore the new partition folder created in the dataset along with a "deltacommit"
file under .hoodie which signals a successful commit.
@@ -501,7 +502,7 @@ docker exec -it adhoc-2 /bin/bash
....
exit
```
-After executing the above command, you will notice
+After executing the above command, you will notice
1. A hive table named `stock_ticks_cow` created which provides Read-Optimized view for the Copy On Write dataset.
2. Two new tables `stock_ticks_mor` and `stock_ticks_mor_rt` created for the Merge On Read dataset. The former
@@ -511,7 +512,7 @@ provides the ReadOptimized view for the Hudi dataset and the later provides the
#### Step 4 (a): Run Hive Queries
Run a hive query to find the latest timestamp ingested for stock symbol 'GOOG'. You will notice that both read-optimized
-(for both COW and MOR dataset)and realtime views (for MOR dataset)give the same value "10:29 a.m" as Hudi create a
+(for both COW and MOR dataset)and realtime views (for MOR dataset)give the same value "10:29 a.m" as Hudi create a
parquet file for the first batch of data.
```
@@ -565,7 +566,7 @@ Now, run a projection query:
# Merge-On-Read Queries:
==========================
-Lets run similar queries against M-O-R dataset. Lets look at both
+Lets run similar queries against M-O-R dataset. Lets look at both
ReadOptimized and Realtime views supported by M-O-R dataset
# Run against ReadOptimized View. Notice that the latest timestamp is 10:29
@@ -670,7 +671,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, close
# Merge-On-Read Queries:
==========================
-Lets run similar queries against M-O-R dataset. Lets look at both
+Lets run similar queries against M-O-R dataset. Lets look at both
ReadOptimized and Realtime views supported by M-O-R dataset
# Run against ReadOptimized View. Notice that the latest timestamp is 10:29
@@ -718,7 +719,7 @@ Upload the second batch of data and ingest this batch using delta-streamer. As t
partitions, there is no need to run hive-sync
```
-cat docker/demo/data/batch_2.json | kafkacat -b kafkabroker -t stock_ticks -P
+cat docker/demo/data/batch_2.json | kafkacat -b kafkabroker -t stock_ticks -P
# Within Docker container, run the ingestion command
docker exec -it adhoc-2 /bin/bash
@@ -734,15 +735,15 @@ exit
With Copy-On-Write table, the second ingestion by DeltaStreamer resulted in a new version of Parquet file getting created.
See `http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow/2018/08/31`
-With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
+With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
Take a look at the HDFS filesystem to get an idea: `http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_mor/2018/08/31`
#### Step 6(a): Run Hive Queries
-With Copy-On-Write table, the read-optimized view immediately sees the changes as part of second batch once the batch
-got committed as each ingestion creates newer versions of parquet files.
+With Copy-On-Write table, the read-optimized view immediately sees the changes as part of second batch once the batch
+got committed as each ingestion creates newer versions of parquet files.
-With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
+With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
This is the time, when ReadOptimized and Realtime views will provide different results. ReadOptimized view will still
return "10:29 am" as it will only read from the Parquet file. Realtime View will do on-the-fly merge and return
latest committed data which is "10:59 a.m".
@@ -773,7 +774,7 @@ WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the futu
As you can notice, the above queries now reflect the changes that came as part of ingesting second batch.
-# Merge On Read Table:
+# Merge On Read Table:
# Read Optimized View
0: jdbc:hive2://hiveserver:10000> select symbol, max(ts) from stock_ticks_mor group by symbol HAVING symbol = 'GOOG';
@@ -843,7 +844,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, close
As you can notice, the above queries now reflect the changes that came as part of ingesting second batch.
-# Merge On Read Table:
+# Merge On Read Table:
# Read Optimized View
scala> spark.sql("select symbol, max(ts) from stock_ticks_mor group by symbol HAVING symbol = 'GOOG'").show(100, false)
@@ -909,8 +910,8 @@ To show the effects of incremental-query, let us assume that a reader has alread
ingesting first batch. Now, for the reader to see effect of the second batch, he/she has to keep the start timestamp to
the commit time of the first batch (20180924064621) and run incremental query
-`Hudi incremental mode` provides efficient scanning for incremental queries by filtering out files that do not have any
-candidate rows using hudi-managed metadata.
+`Hudi incremental mode` provides efficient scanning for incremental queries by filtering out files that do not have any
+candidate rows using hudi-managed metadata.
```
docker exec -it adhoc-2 /bin/bash
@@ -1008,7 +1009,7 @@ hoodie:stock_ticks_mor->compactions show all
___________________________________________________________________
| Compaction Instant Time| State | Total FileIds to be Compacted|
|==================================================================|
-
+
# Schedule a compaction. This will use Spark Launcher to schedule compaction
hoodie:stock_ticks_mor->compaction schedule
....
@@ -1028,7 +1029,7 @@ hoodie:stock_ticks_mor->compactions show all
___________________________________________________________________
| Compaction Instant Time| State | Total FileIds to be Compacted|
|==================================================================|
- | 20180924070031 | REQUESTED| 1 |
+ | 20180924070031 | REQUESTED| 1 |
# Execute the compaction. The compaction instant value passed below must be the one displayed in the above "compactions show all" query
hoodie:stock_ticks_mor->compaction run --compactionInstant 20180924070031 --parallelism 2 --sparkMemory 1G --schemaFilePath /var/demo/config/schema.avsc --retry 1
@@ -1052,7 +1053,7 @@ hoodie:stock_ticks->compactions show all
|==================================================================|
| 20180924070031 | COMPLETED| 1 |
-```
+```
#### Step 9: Run Hive Queries including incremental queries
@@ -1169,9 +1170,9 @@ You can bring up a hadoop docker environment containing Hadoop, Hive and Spark s
```
$ mvn pre-integration-test -DskipTests
```
-The above command builds docker images for all the services with
-current Hudi source installed at /var/hoodie/ws and also brings up the services using a compose file. We
-currently use Hadoop (v2.8.4), Hive (v2.3.3) and Spark (v2.3.1) in docker images.
+The above command builds docker images for all the services with
+current Hudi source installed at /var/hoodie/ws and also brings up the services using a compose file. We
+currently use Hadoop (v2.8.4), Hive (v2.3.3) and Spark (v2.3.1) in docker images.
To bring down the containers
```
@@ -1185,9 +1186,9 @@ $ cd hoodie-integ-test
$ mvn docker-compose:up -DdetachedMode=true
```
-Hudi is a library that is operated in a broader data analytics/ingestion environment
+Hudi is a library that is operated in a broader data analytics/ingestion environment
involving Hadoop, Hive and Spark. Interoperability with all these systems is a key objective for us. We are
-actively adding integration-tests under __hoodie-integ-test/src/test/java__ that makes use of this
+actively adding integration-tests under __hoodie-integ-test/src/test/java__ that makes use of this
docker environment (See __hoodie-integ-test/src/test/java/com/uber/hoodie/integ/ITTestHoodieSanity.java__ )
@@ -1202,10 +1203,10 @@ and compose scripts are carefully implemented so that they serve dual-purpose
inbuilt jars by mounting local HUDI workspace over the docker location
This helps avoid maintaining separate docker images and avoids the costly step of building HUDI docker images locally.
-But if users want to test hudi from locations with lower network bandwidth, they can still build local images
-run the script
+But if users want to test hudi from locations with lower network bandwidth, they can still build local images
+run the script
`docker/build_local_docker_images.sh` to build local docker images before running `docker/setup_demo.sh`
-
+
Here are the commands:
```
diff --git a/docs/roadmap.md b/docs/roadmap.md
deleted file mode 100644
index c65c3a9..0000000
--- a/docs/roadmap.md
+++ /dev/null
@@ -1,14 +0,0 @@
----
-title: Roadmap
-keywords: usecases
-sidebar: mydoc_sidebar
-permalink: roadmap.html
----
-
-## Planned Features
-
-* Support for Self Joins - As of now, you cannot incrementally consume the same table more than once, since the InputFormat does not understand the QueryPlan.
-* Hudi Spark Datasource - Allows for reading and writing data back using Apache Spark natively (without falling back to InputFormat), which can be more performant
-* Hudi Presto Connector - Allows for querying data managed by Hudi using Presto natively, which can again boost [performance](https://prestodb.io/docs/current/release/release-0.138.html)
-
-
diff --git a/docs/sql_queries.md b/docs/sql_queries.md
index 955e794..44848eb 100644
--- a/docs/sql_queries.md
+++ b/docs/sql_queries.md
@@ -62,7 +62,4 @@ spark.sparkContext.hadoopConfiguration.setClass("mapreduce.input.pathFilter.clas
## Presto
-Presto requires a [patch](https://github.com/prestodb/presto/pull/7002) (until the PR is merged) and the hoodie-hadoop-mr-bundle jar to be placed
-into `<presto_install>/plugin/hive-hadoop2/`.
-
-{% include callout.html content="Get involved to improve this integration [here](https://github.com/uber/hoodie/issues/81)" type="info" %}
+Presto requires the `hoodie-presto-bundle` jar to be placed into `<presto_install>/plugin/hive-hadoop2/`, across the installation.
[incubator-hudi-site] 08/19: Merge pull request #4 from
vinothchandar/asf-site
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 6b2b80941f0f033428bef98fdc7cf9b13a9091e1
Merge: 14855d4 ada1ba2
Author: vinoth chandar <vi...@users.noreply.github.com>
AuthorDate: Fri Feb 15 20:58:12 2019 -0800
Merge pull request #4 from vinothchandar/asf-site
Improve aesthetics of site & added README for docs
docs/.gitignore | 1 +
docs/Dockerfile | 12 +-
docs/Gemfile.lock | 46 +-
docs/README.md | 37 +
docs/_data/sidebars/mydoc_sidebar.yml | 6 +-
docs/_includes/topnav.html | 7 +-
docs/community.md | 4 +-
docs/css/lavish-bootstrap.css | 13 +-
docs/css/theme-blue.css | 6 +-
docs/docker-compose.yml | 13 +
docs/images/androidsdkmanagericon.png | Bin 795 -> 0 bytes
docs/images/authorizegithubscreen2.png | Bin 76388 -> 0 bytes
docs/images/authorizeongithub.png | Bin 22571 -> 0 bytes
docs/images/company_logo.png | Bin 3105 -> 0 bytes
docs/images/company_logo_big.png | Bin 9588 -> 0 bytes
docs/images/favicon.ico | Bin 1150 -> 1150 bytes
docs/images/helpapi-01.png | Bin 91640 -> 0 bytes
docs/images/helpapi.svg | 1661 --------------------------------
docs/images/hudi_site_logo.png | Bin 0 -> 13170 bytes
docs/images/illustratoroptions.png | Bin 118175 -> 0 bytes
docs/images/itermexample.png | Bin 68886 -> 0 bytes
docs/images/jekyll.png | Bin 5375 -> 0 bytes
docs/images/killalljekyll.png | Bin 66686 -> 0 bytes
docs/images/liningup.png | Bin 74728 -> 0 bytes
docs/index.md | 3 +-
25 files changed, 104 insertions(+), 1705 deletions(-)
[incubator-hudi-site] 06/19: Improve aesthetics of site & added
README for docs
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit d40cdf8e879bf14f8b8fac9d008a763bdb381786
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Fri Feb 15 10:15:56 2019 -0800
Improve aesthetics of site & added README for docs
- Uses the Apache Hudi logo
- Fixed topnav bg to be transparent to match logo
- Adjusted font colors
- Removed unsued icons
- Added README with build instructions
---
docs/.DS_Store | Bin 0 -> 8196 bytes
docs/Gemfile.lock | 44 +-
docs/README.md | 29 +
docs/_data/sidebars/mydoc_sidebar.yml | 6 +-
docs/_includes/topnav.html | 7 +-
docs/css/lavish-bootstrap.css | 13 +-
docs/css/theme-blue.css | 6 +-
docs/images/androidsdkmanagericon.png | Bin 795 -> 0 bytes
docs/images/authorizegithubscreen2.png | Bin 76388 -> 0 bytes
docs/images/authorizeongithub.png | Bin 22571 -> 0 bytes
docs/images/company_logo.png | Bin 3105 -> 0 bytes
docs/images/company_logo_big.png | Bin 9588 -> 0 bytes
docs/images/favicon.ico | Bin 1150 -> 1150 bytes
docs/images/helpapi-01.png | Bin 91640 -> 0 bytes
docs/images/helpapi.svg | 1661 --------------------------------
docs/images/hudi_site_logo.png | Bin 0 -> 13170 bytes
docs/images/illustratoroptions.png | Bin 118175 -> 0 bytes
docs/images/itermexample.png | Bin 68886 -> 0 bytes
docs/images/jekyll.png | Bin 5375 -> 0 bytes
docs/images/killalljekyll.png | Bin 66686 -> 0 bytes
docs/images/liningup.png | Bin 74728 -> 0 bytes
21 files changed, 70 insertions(+), 1696 deletions(-)
diff --git a/docs/.DS_Store b/docs/.DS_Store
new file mode 100644
index 0000000..83b1f95
Binary files /dev/null and b/docs/.DS_Store differ
diff --git a/docs/Gemfile.lock b/docs/Gemfile.lock
index 65eae02..8359d57 100644
--- a/docs/Gemfile.lock
+++ b/docs/Gemfile.lock
@@ -13,19 +13,19 @@ GEM
execjs
coffee-script-source (1.12.2)
colorator (1.1.0)
- concurrent-ruby (1.0.5)
- ethon (0.11.0)
+ concurrent-ruby (1.1.4)
+ ethon (0.12.0)
ffi (>= 1.3.0)
execjs (2.7.0)
- faraday (0.13.1)
+ faraday (0.15.4)
multipart-post (>= 1.2, < 3)
- ffi (1.9.24)
+ ffi (1.10.0)
forwardable-extended (2.6.0)
gemoji (2.1.0)
github-pages (106)
activesupport (= 4.2.7)
github-pages-health-check (= 1.2.0)
- jekyll (= 3.6.3)
+ jekyll (= 3.3.1)
jekyll-avatar (= 0.4.2)
jekyll-coffeescript (= 1.0.1)
jekyll-feed (= 0.8.0)
@@ -53,12 +53,12 @@ GEM
octokit (~> 4.0)
public_suffix (~> 1.4)
typhoeus (~> 0.7)
- html-pipeline (2.7.1)
+ html-pipeline (2.10.0)
activesupport (>= 2)
nokogiri (>= 1.4)
- i18n (0.9.1)
+ i18n (0.9.5)
concurrent-ruby (~> 1.0)
- jekyll (3.6.3)
+ jekyll (3.3.1)
addressable (~> 2.4)
colorator (~> 1.0)
jekyll-sass-converter (~> 1.0)
@@ -110,24 +110,24 @@ GEM
rb-fsevent (>= 0.9.3)
rb-inotify (>= 0.9.7)
mercenary (0.3.6)
- mini_portile2 (2.3.0)
+ mini_portile2 (2.4.0)
minima (2.0.0)
- minitest (5.11.1)
+ minitest (5.11.3)
multipart-post (2.0.0)
- net-dns (0.8.0)
- nokogiri (1.8.2)
- mini_portile2 (~> 2.3.0)
- octokit (4.8.0)
+ net-dns (0.9.0)
+ nokogiri (1.10.1)
+ mini_portile2 (~> 2.4.0)
+ octokit (4.13.0)
sawyer (~> 0.8.0, >= 0.5.3)
- pathutil (0.16.1)
+ pathutil (0.16.2)
forwardable-extended (~> 2.6)
public_suffix (1.5.3)
- rb-fsevent (0.10.2)
- rb-inotify (0.9.10)
- ffi (>= 0.5.0, < 2)
+ rb-fsevent (0.10.3)
+ rb-inotify (0.10.0)
+ ffi (~> 1.0)
rouge (1.11.1)
safe_yaml (1.0.4)
- sass (3.5.5)
+ sass (3.7.3)
sass-listen (~> 4.0.0)
sass-listen (4.0.0)
rb-fsevent (~> 0.9, >= 0.9.4)
@@ -140,16 +140,16 @@ GEM
thread_safe (0.3.6)
typhoeus (0.8.0)
ethon (>= 0.8.0)
- tzinfo (1.2.4)
+ tzinfo (1.2.5)
thread_safe (~> 0.1)
- unicode-display_width (1.3.0)
+ unicode-display_width (1.4.1)
PLATFORMS
ruby
DEPENDENCIES
github-pages (~> 106)
- jekyll (= 3.6.3)
+ jekyll (= 3.3.1)
jekyll-feed (~> 0.6)
BUNDLED WITH
diff --git a/docs/README.md b/docs/README.md
new file mode 100644
index 0000000..6c5030d
--- /dev/null
+++ b/docs/README.md
@@ -0,0 +1,29 @@
+## Site Documentation
+
+This folder contains resources that build the [Apache Hudi website](https://hudi.apache.org)
+
+
+### Building docs
+
+The site is based on a [Jekyll](https://jekyllrb.com/) theme hosted [here](idratherbewriting.com/documentation-theme-jekyll/) with detailed instructions.
+
+To build the docs, first you need to install
+
+- gem, ruby (using apt-get/brew)
+- bundler (`gem install bundler`)
+- jekyll (`gem install jekyll`)
+
+and then run the following from `docs` folder to serve a local site
+
+`bundle exec jekyll serve`
+
+### Submitting changes
+
+To submit changes to the docs, please make the changes on the `asf-site` branch, build the site locally, test it out and submit a pull request with the changes to .md and theme files under `docs`
+
+### Updating site
+
+At a regular cadence, one of the Hudi committers will regenerate the site. In order to do this, first build it locally, test and then move the generated site from `_site` locally to `docs/../content`. Submit changes as a PR.
+
+### Automation
+Coming soon.
diff --git a/docs/_data/sidebars/mydoc_sidebar.yml b/docs/_data/sidebars/mydoc_sidebar.yml
index c4f6c46..118bd89 100644
--- a/docs/_data/sidebars/mydoc_sidebar.yml
+++ b/docs/_data/sidebars/mydoc_sidebar.yml
@@ -2,8 +2,8 @@
entries:
- title: sidebar
- product: Documentation
- version:
+ product: Latest
+ version: Version
folders:
- title: Getting Started
@@ -62,5 +62,3 @@ entries:
- title: Comparison
url: /comparison.html
output: web
-
-
diff --git a/docs/_includes/topnav.html b/docs/_includes/topnav.html
index 8748605..7019fe8 100644
--- a/docs/_includes/topnav.html
+++ b/docs/_includes/topnav.html
@@ -1,4 +1,5 @@
<!-- Navigation -->
+
<nav class="navbar navbar-inverse navbar-fixed-top">
<div class="container topnavlinks">
<div class="navbar-header">
@@ -8,7 +9,11 @@
<span class="icon-bar"></span>
<span class="icon-bar"></span>
</button>
- <a class="fa fa-home fa-lg navbar-brand" href="index.html"> <span class="projectTitle"> {{site.topnav_title}}</span></a>
+
+ <a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
+ <img src="{{ "images/hudi_site_logo.png" }}" alt="Hudi logo"/>
+ <!--{{site.topnav_title}}-->
+ </span></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
diff --git a/docs/css/lavish-bootstrap.css b/docs/css/lavish-bootstrap.css
index c2af93e..ff64532 100644
--- a/docs/css/lavish-bootstrap.css
+++ b/docs/css/lavish-bootstrap.css
@@ -513,10 +513,10 @@ dd {
.dl-horizontal dd:after {
content: " ";
/* 1 */
-
+
display: table;
/* 2 */
-
+
}
.dl-horizontal dd:after {
clear: both;
@@ -525,10 +525,10 @@ dd {
.dl-horizontal dd:after {
content: " ";
/* 1 */
-
+
display: table;
/* 2 */
-
+
}
.dl-horizontal dd:after {
clear: both;
@@ -3471,6 +3471,7 @@ textarea.input-group-sm > .input-group-btn > .btn {
min-height: 50px;
margin-bottom: 20px;
border: 1px solid transparent;
+ background-color: white
}
.navbar:before,
.navbar:after {
@@ -3916,11 +3917,11 @@ textarea.input-group-sm > .input-group-btn > .btn {
color: #f9faf9;
}
.navbar-inverse .navbar-nav > li > a {
- color: #f9faf9;
+ /*color: #f9faf9;*/
}
.navbar-inverse .navbar-nav > li > a:hover,
.navbar-inverse .navbar-nav > li > a:focus {
- color: #ffffff;
+ color: #347DBE;
background-color: transparent;
}
.navbar-inverse .navbar-nav > .active > a,
diff --git a/docs/css/theme-blue.css b/docs/css/theme-blue.css
index 3b99929..f9aa248 100644
--- a/docs/css/theme-blue.css
+++ b/docs/css/theme-blue.css
@@ -38,8 +38,10 @@ a[data-toggle="tooltip"] {
}
.navbar-inverse {
- background-color: #347DBE;
- border-color: #015CAE;
+ background-color: transparent;
+ border-color: transparent;
+ /*background-color: #347DBE;
+ border-color: #015CAE;*/
}
.navbar-inverse .navbar-nav > .open > a, .navbar-inverse .navbar-nav > .open > a:hover, .navbar-inverse .navbar-nav > .open > a:focus {
diff --git a/docs/images/androidsdkmanagericon.png b/docs/images/androidsdkmanagericon.png
deleted file mode 100644
index 65014a2..0000000
Binary files a/docs/images/androidsdkmanagericon.png and /dev/null differ
diff --git a/docs/images/authorizegithubscreen2.png b/docs/images/authorizegithubscreen2.png
deleted file mode 100644
index 2f6b6ca..0000000
Binary files a/docs/images/authorizegithubscreen2.png and /dev/null differ
diff --git a/docs/images/authorizeongithub.png b/docs/images/authorizeongithub.png
deleted file mode 100644
index 9380f80..0000000
Binary files a/docs/images/authorizeongithub.png and /dev/null differ
diff --git a/docs/images/company_logo.png b/docs/images/company_logo.png
deleted file mode 100644
index f2d9e7e..0000000
Binary files a/docs/images/company_logo.png and /dev/null differ
diff --git a/docs/images/company_logo_big.png b/docs/images/company_logo_big.png
deleted file mode 100644
index 2a4b9e8..0000000
Binary files a/docs/images/company_logo_big.png and /dev/null differ
diff --git a/docs/images/favicon.ico b/docs/images/favicon.ico
index a002093..3a010fb 100644
Binary files a/docs/images/favicon.ico and b/docs/images/favicon.ico differ
diff --git a/docs/images/helpapi-01.png b/docs/images/helpapi-01.png
deleted file mode 100644
index 51308a1..0000000
Binary files a/docs/images/helpapi-01.png and /dev/null differ
diff --git a/docs/images/helpapi.svg b/docs/images/helpapi.svg
deleted file mode 100644
index 0ddc922..0000000
--- a/docs/images/helpapi.svg
+++ /dev/null
@@ -1,1661 +0,0 @@
-<?xml version="1.0" encoding="utf-8"?>
-<!-- Generator: Adobe Illustrator 18.1.1, SVG Export Plug-In . SVG Version: 6.00 Build 0) -->
-<svg version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
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- c5.5,0,10,4.5,10,10V609.5z"/>
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- <path fill="#F2F2F2" d="M663,765.3c0,5.5-4.5,10-10,10H449.5c-5.5,0-10-4.5-10-10V622.1c0-5.5,4.5-10,10-10H653
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diff --git a/docs/images/hudi_site_logo.png b/docs/images/hudi_site_logo.png
new file mode 100644
index 0000000..705edf6
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diff --git a/docs/images/illustratoroptions.png b/docs/images/illustratoroptions.png
deleted file mode 100644
index d043971..0000000
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diff --git a/docs/images/itermexample.png b/docs/images/itermexample.png
deleted file mode 100644
index e412af0..0000000
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diff --git a/docs/images/jekyll.png b/docs/images/jekyll.png
deleted file mode 100644
index ebaf27d..0000000
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diff --git a/docs/images/killalljekyll.png b/docs/images/killalljekyll.png
deleted file mode 100644
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diff --git a/docs/images/liningup.png b/docs/images/liningup.png
deleted file mode 100644
index ede4dc0..0000000
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[incubator-hudi-site] 13/19: Pushing refreshed site content
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit dec68b2816fd79eb2e58b09c8c1606e8e61e95f6
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Mon Feb 25 12:58:29 2019 -0800
Pushing refreshed site content
- Reflects footer, privacy disclaimer changes
- Reflects various fixes to image links
- Reflects new contribution, community links
---
content/404.html | 31 +-
content/admin_guide.html | 83 +++--
content/api_docs.html | 399 --------------------
content/community.html | 98 +++--
content/comparison.html | 31 +-
content/concepts.html | 53 +--
content/configurations.html | 91 +++--
content/{dev_setup.html => contributing.html} | 154 ++++++--
content/css/customstyles.css | 4 +-
content/css/lavish-bootstrap.css | 8 +
content/css/theme-blue.css | 3 +-
content/feed.xml | 20 +-
content/gcs_hoodie.html | 31 +-
content/images/asf_logo.svg | 210 +++++++++++
content/images/hoodie_cow.png | Bin 31136 -> 0 bytes
content/images/hoodie_intro_1.png | Bin 23478 -> 27890 bytes
content/images/hoodie_mor.png | Bin 56002 -> 0 bytes
content/images/hudi_cow.png | Bin 0 -> 48994 bytes
content/images/hudi_mor.png | Bin 0 -> 92073 bytes
.../{hoodie_timeline.png => hudi_timeline.png} | Bin
content/implementation.html | 142 ++++----
content/incremental_processing.html | 38 +-
content/index.html | 55 +--
content/js/mydoc_scroll.html | 31 +-
content/migration_guide.html | 154 ++++----
content/news.html | 45 ++-
content/news_archive.html | 42 ++-
content/powered_by.html | 31 +-
content/{code_and_design.html => privacy.html} | 114 ++----
content/quickstart.html | 186 ++++++----
content/roadmap.html | 405 ---------------------
content/s3_hoodie.html | 31 +-
content/search.json | 60 ++-
content/sitemap.xml | 20 +-
content/sql_queries.html | 37 +-
content/strata-talk.html | 44 ++-
content/use_cases.html | 31 +-
docs/_includes/footer.html | 2 +-
38 files changed, 1218 insertions(+), 1466 deletions(-)
diff --git a/content/404.html b/content/404.html
index 5c95e2c..9491810 100644
--- a/content/404.html
+++ b/content/404.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -379,9 +380,19 @@ $('#toc').on('click', 'a', function() {
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/admin_guide.html b/content/admin_guide.html
index 72e5af4..470a219 100644
--- a/content/admin_guide.html
+++ b/content/admin_guide.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -379,8 +380,9 @@ hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1
</code></pre>
</div>
-<p>To see the description of hoodie table, use the command:
-<code class="highlighter-rouge">
+<p>To see the description of hoodie table, use the command:</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>
hoodie:hoodie_table_1->desc
18/09/06 15:57:19 INFO timeline.HoodieActiveTimeline: Loaded instants []
_________________________________________________________
@@ -392,7 +394,9 @@ hoodie:hoodie_table_1->desc
| hoodie.table.name | hoodie_table_1 |
| hoodie.table.type | COPY_ON_WRITE |
| hoodie.archivelog.folder| |
-</code></p>
+
+</code></pre>
+</div>
<p>Following is a sample command to connect to a Hoodie dataset contains uber trips.</p>
@@ -511,7 +515,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
| Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta Size| Delta Size - compaction scheduled| Delta Size - compaction unscheduled| Delta To Base Ratio - compaction scheduled| Delta To Base Ratio - compaction unscheduled| Delta Files - compaction scheduled | Delta Files - compaction unscheduled|
|========================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== [...]
| 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | 20.8 KB | 0.0 B | 0.0 B | 0.0 B | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]| [] |
-
+
hoodie:stock_ticks_mor->
</code></pre>
</div>
@@ -548,7 +552,7 @@ This is a sequence file that contains a mapping from commitNumber => json wit
<h4 id="compactions">Compactions</h4>
-<p>To get an idea of the lag between compaction and writer applications, use the below command to list down all
+<p>To get an idea of the lag between compaction and writer applications, use the below command to list down all
pending compactions.</p>
<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->compactions show all
@@ -639,7 +643,7 @@ Description: Run Compaction for given instant time
...
COMPACTION PLAN VALID
-
+
___________________________________________________________________________________________________________________________________________________________________________________________________________________________
| File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error|
|==========================================================================================================================================================================================================================|
@@ -664,13 +668,14 @@ hoodie:stock_ticks_mor->compaction validate --instant 20181005222601
<p>The following commands must be executed without any other writer/ingestion application running.</p>
-<p>Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
-operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
+<p>Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
+operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
so that are preserved. Hudi provides the following CLI to support it</p>
<h5 id="unscheduling-compaction">UnScheduling Compaction</h5>
-<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->compaction unscheduleFileId --fileId <FileUUID>
+<div class="highlighter-rouge"><pre class="highlight"><code>
+hoodie:trips->compaction unscheduleFileId --fileId <FileUUID>
....
No File renames needed to unschedule file from pending compaction. Operation successful.
@@ -678,27 +683,31 @@ No File renames needed to unschedule file from pending compaction. Operation suc
</div>
<p>In other cases, an entire compaction plan needs to be reverted. This is supported by the following CLI
-<code class="highlighter-rouge">
-hoodie:trips->compaction unschedule --compactionInstant <compactionInstant>
+```</p>
+
+<p>hoodie:trips->compaction unschedule –compactionInstant <compactionInstant>
.....
-No File renames needed to unschedule pending compaction. Operation successful.
-</code></p>
+No File renames needed to unschedule pending compaction. Operation successful.</compactionInstant></p>
-<h5 id="repair-compaction">Repair Compaction</h5>
+<div class="highlighter-rouge"><pre class="highlight"><code>
+##### Repair Compaction
-<p>The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
-partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
-<code class="highlighter-rouge">compaction validate</code>, you can notice invalid compaction operations if there is one. In these cases, the repair
+The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
+partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
+`compaction validate`, you can notice invalid compaction operations if there is one. In these cases, the repair
command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
-consistent with the compaction plan</p>
+consistent with the compaction plan
-<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:stock_ticks_mor->compaction repair --instant 20181005222611
-......
-Compaction successfully repaired
-.....
</code></pre>
</div>
+<p>hoodie:stock_ticks_mor->compaction repair –instant 20181005222611
+……
+Compaction successfully repaired
+…..</p>
+
+<p>```</p>
+
<h2 id="metrics">Metrics</h2>
<p>Once the Hoodie Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hoodie datasets</p>
@@ -785,9 +794,19 @@ In the future, a more sophisticated debug/management UI would be added to the pr
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/api_docs.html b/content/api_docs.html
deleted file mode 100644
index 2898b67..0000000
--- a/content/api_docs.html
+++ /dev/null
@@ -1,399 +0,0 @@
-<!DOCTYPE html>
-<head>
- <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1">
-<meta name="description" content="">
-<meta name="keywords" content=" usecases">
-<title>API Docs | Hudi</title>
-<link rel="stylesheet" href="css/syntax.css">
-
-
-<link rel="stylesheet" type="text/css" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css">
-<!--<link rel="stylesheet" type="text/css" href="css/bootstrap.min.css">-->
-<link rel="stylesheet" href="css/modern-business.css">
-<link rel="stylesheet" href="css/lavish-bootstrap.css">
-<link rel="stylesheet" href="css/customstyles.css">
-<link rel="stylesheet" href="css/theme-blue.css">
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-<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery-cookie/1.4.1/jquery.cookie.min.js"></script>
-<script src="js/jquery.navgoco.min.js"></script>
-
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-<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/js/bootstrap.min.js"></script>
-<script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/2.0.0/anchor.min.js"></script>
-<script src="js/toc.js"></script>
-<script src="js/customscripts.js"></script>
-
-<script>
- (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
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- })(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
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- ga('create', 'UA-93561550-1', 'auto');
- ga('send', 'pageview');
-
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-
-<!-- HTML5 Shim and Respond.js IE8 support of HTML5 elements and media queries -->
-<!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
-<!--[if lt IE 9]>
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-<script src="https://oss.maxcdn.com/libs/respond.js/1.4.2/respond.min.js"></script>
-<![endif]-->
-
-<link rel="alternate" type="application/rss+xml" title="" href="http://0.0.0.0:4000feed.xml">
-
- <script>
- $(document).ready(function() {
- // Initialize navgoco with default options
- $("#mysidebar").navgoco({
- caretHtml: '',
- accordion: true,
- openClass: 'active', // open
- save: false, // leave false or nav highlighting doesn't work right
- cookie: {
- name: 'navgoco',
- expires: false,
- path: '/'
- },
- slide: {
- duration: 400,
- easing: 'swing'
- }
- });
-
- $("#collapseAll").click(function(e) {
- e.preventDefault();
- $("#mysidebar").navgoco('toggle', false);
- });
-
- $("#expandAll").click(function(e) {
- e.preventDefault();
- $("#mysidebar").navgoco('toggle', true);
- });
-
- });
-
- </script>
- <script>
- $(function () {
- $('[data-toggle="tooltip"]').tooltip()
- })
- </script>
-
-
-</head>
-<body>
-<!-- Navigation -->
-
-<nav class="navbar navbar-inverse navbar-fixed-top">
- <div class="container topnavlinks">
- <div class="navbar-header">
- <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
- <span class="sr-only">Toggle navigation</span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- </button>
-
- <a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
- <img src="images/hudi_site_logo.png" alt="Hudi logo"/>
- <!--Hudi-->
- </span></a>
- </div>
- <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
- <ul class="nav navbar-nav navbar-right">
- <!-- entries without drop-downs appear here -->
-
-
-
- <li><a href="news">News</a></li>
-
-
-
- <li><a href="community.html">Community</a></li>
-
-
-
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
-
-
-
- <!-- entries with drop-downs appear here -->
- <!-- conditional logic to control which topnav appears for the audience defined in the configuration file.-->
-
-
- <li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
- <ul class="dropdown-menu">
-
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- <li><a href="dev_setup.html">Setup</a></li>
-
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- <li class="dropdownActive"><a href="api_docs.html">API Docs</a></li>
-
-
-
- <li><a href="code_and_design.html">Code Structure</a></li>
-
-
-
- <li><a href="roadmap.html">Roadmap</a></li>
-
-
- </ul>
- </li>
-
-
-
- <li>
-
-
-
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the API Docs page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
-
-<li>
-
-
- <!--comment out this block if you want to hide search-->
- <li>
- <!--start search-->
- <div id="search-demo-container">
- <input type="text" id="search-input" placeholder="search...">
- <ul id="results-container"></ul>
- </div>
- <script src="js/jekyll-search.js" type="text/javascript"></script>
- <script type="text/javascript">
- SimpleJekyllSearch.init({
- searchInput: document.getElementById('search-input'),
- resultsContainer: document.getElementById('results-container'),
- dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="API Docs">{title}</a></li>',
- noResultsText: 'No results found.',
- limit: 10,
- fuzzy: true,
- })
- </script>
- <!--end search-->
- </li>
- </ul>
- </div>
- </div>
- <!-- /.container -->
-</nav>
-
-<!-- Page Content -->
-<div class="container">
- <div class="col-lg-12"> </div>
- <!-- Content Row -->
- <div class="row">
- <!-- Sidebar Column -->
- <div class="col-md-3">
-
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-
-
-
-
-<ul id="mysidebar" class="nav">
- <li class="sidebarTitle">Latest Version</li>
-
-
-
- <li>
- <a href="#">Getting Started</a>
- <ul>
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- <li><a href="index.html">Overview</a></li>
-
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- <li><a href="powered_by.html">Talks & Powered By</a></li>
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- <li><a href="sql_queries.html">SQL Queries</a></li>
-
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- <li><a href="migration_guide.html">Migration Guide</a></li>
-
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- <li><a href="incremental_processing.html">Incremental Processing</a></li>
-
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- <li><a href="admin_guide.html">Admin Guide</a></li>
-
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- <li><a href="comparison.html">Comparison</a></li>
-
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- </ul>
-
-
-
- <!-- if you aren't using the accordion, uncomment this block:
- <p class="external">
- <a href="#" id="collapseAll">Collapse All</a> | <a href="#" id="expandAll">Expand All</a>
- </p>
- -->
- </li>
-</ul>
-</div>
-
-<!-- this highlights the active parent class in the navgoco sidebar. this is critical so that the parent expands when you're viewing a page. This must appear below the sidebar code above. Otherwise, if placed inside customscripts.js, the script runs before the sidebar code runs and the class never gets inserted.-->
-<script>$("li.active").parents('li').toggleClass("active");</script>
-
- <!-- Content Column -->
- <div class="col-md-9">
- <div class="post-header">
- <h1 class="post-title-main">API Docs</h1>
-</div>
-
-
-
-<div class="post-content">
-
-
-
-
-
-<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
-<script>
-$( document ).ready(function() {
- // Handler for .ready() called.
-
-$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
-
-/* this offset helps account for the space taken up by the floating toolbar. */
-$('#toc').on('click', 'a', function() {
- var target = $(this.getAttribute('href'))
- , scroll_target = target.offset().top
-
- $(window).scrollTop(scroll_target - 10);
- return false
-})
-
-});
-</script>
-
-<div id="toc"></div>
-
-
-
-
-
-
- <p>Work In Progress</p>
-
-
-
- <div class="tags">
-
- </div>
-
-
-
-</div>
-
-<hr class="shaded"/>
-
-<footer>
- <div class="row">
- <div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
- </div>
- </div>
-</footer>
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\ No newline at end of file
diff --git a/content/community.html b/content/community.html
index de173be..39488eb 100644
--- a/content/community.html
+++ b/content/community.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -340,20 +341,63 @@
- <h2 id="contributing">Contributing</h2>
-<p>We :heart: contributions. If you find a bug in the library or would like to add new features, go ahead and open
-issues or pull requests against this repo. Before you do so, please sign the
-<a href="https://www.apache.org/licenses/icla.pdf">Apache CLA</a>.
-Also, be sure to write unit tests for your bug fix or feature to show that it works as expected.
-If the reviewer feels this contributions needs to be in the release notes, please add it to CHANGELOG.md as well.</p>
-
-<p>If you want to participate in day-day conversations, please join our <a href="https://join.slack.com/t/apache-hudi/signup">slack group</a>.
-If you are from select pre-listed email domains, you can self signup. Others, please subscribe to dev@hudi.apache.org</p>
+ <h2 id="engage-with-us">Engage with us</h2>
+
+<p>There are several ways to get in touch with the Hudi community.</p>
+
+<table>
+ <thead>
+ <tr>
+ <th>When?</th>
+ <th>Channel to use</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>For any general questions, user support, development discussions</td>
+ <td>Dev Mailing list (<a href="mailto:dev-subscribe@hudi.apache.org">Subscribe</a>, <a href="mailto:dev-unsubscribe@hudi.apache.or& [...]
+ </tr>
+ <tr>
+ <td>For reporting bugs or issues or discover known issues</td>
+ <td>Please use <a href="https://issues.apache.org/jira/projects/HUDI/summary">ASF Hudi JIRA</a></td>
+ </tr>
+ <tr>
+ <td>For quick pings & 1-1 chats</td>
+ <td>Join our <a href="https://join.slack.com/t/apache-hudi/signup">slack group</a></td>
+ </tr>
+ <tr>
+ <td>For proposing large features, changes</td>
+ <td>Start a Hudi Improvement Process (HIP). Instructions coming soon.</td>
+ </tr>
+ <tr>
+ <td>For stream of commits, pull requests etc</td>
+ <td>Commits Mailing list (<a href="mailto:commits-subscribe@hudi.apache.org">Subscribe</a>, <a href="mailto:commits-unsubscribe@hudi.� [...]
+ </tr>
+ </tbody>
+</table>
+
+<p>If you wish to report a security vulnerability, please contact <a href="mailto:security@apache.org">security@apache.org</a>.
+Apache Hudi follows the typical Apache vulnerability handling <a href="https://apache.org/security/committers.html#vulnerability-handling">process</a>.</p>
+
+<h2 id="contributing">Contributing</h2>
+
+<p>Apache Hudi community welcomes contributions from anyone!</p>
+
+<p>Here are few ways, you can get involved.</p>
+
+<ul>
+ <li>Ask (and/or) answer questions on our support channels listed above.</li>
+ <li>Review code or HIPs</li>
+ <li>Help improve documentation</li>
+ <li>Testing; Improving out-of-box experience by reporting bugs</li>
+ <li>Share new ideas/directions to pursue or propose a new HIP</li>
+ <li>Contributing code to the project</li>
+</ul>
-<h2 id="becoming-a-committer">Becoming a Committer</h2>
+<h4 id="code-contributions">Code Contributions</h4>
-<p>Hoodie has adopted a lot of guidelines set forth in <a href="https://www.chromium.org/getting-involved/become-a-committer">Google Chromium project</a>, to determine committership proposals. However, given this is a much younger project, we would have the contribution bar to be 10-15 non-trivial patches instead.
-Additionally, we expect active engagement with the community over a few months, in terms of conference/meetup talks, helping out with issues/questions on slack/github.</p>
+<p>Useful resources for contributing can be found under the “Developers” top menu.
+Specifically, please refer to the detailed <a href="contributing.html">contribution guide</a>.</p>
<div class="tags">
@@ -369,9 +413,19 @@ Additionally, we expect active engagement with the community over a few months,
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/comparison.html b/content/comparison.html
index d56ab17..34082e0 100644
--- a/content/comparison.html
+++ b/content/comparison.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -404,9 +405,19 @@ and will eventually happen as a <a href="https://github.com/uber/hoodie/issues/8
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/concepts.html b/content/concepts.html
index cc498fb..7e85d32 100644
--- a/content/concepts.html
+++ b/content/concepts.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -357,7 +358,7 @@ Such key activities include</p>
<li><code class="highlighter-rouge">COMMITS</code> - A single commit captures information about an <strong>atomic write</strong> of a batch of records into a dataset.
Commits are identified by a monotonically increasing timestamp, denoting the start of the write operation.</li>
<li><code class="highlighter-rouge">CLEANS</code> - Background activity that gets rid of older versions of files in the dataset, that are no longer needed.</li>
- <li><code class="highlighter-rouge">DELTA_COMMITS</code> - A single commit captures information about an <strong>atomic write</strong> of a batch of records into a
+ <li><code class="highlighter-rouge">DELTA_COMMITS</code> - A single commit captures information about an <strong>atomic write</strong> of a batch of records into a
MergeOnRead storage type of dataset</li>
<li><code class="highlighter-rouge">COMPACTIONS</code> - Background activity to reconcile differential data structures within Hudi e.g: moving updates from row based log files to columnar formats.</li>
</ul>
@@ -375,15 +376,15 @@ only the changed files without say scanning all the time buckets > 07:00.</p>
<h2 id="terminologies">Terminologies</h2>
<ul>
- <li><code class="highlighter-rouge">Hudi Dataset</code>
+ <li><code class="highlighter-rouge">Hudi Dataset</code>
A structured hive/spark dataset managed by Hudi. Hudi supports both partitioned and non-partitioned Hive tables.</li>
- <li><code class="highlighter-rouge">Commit</code>
- A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
+ <li><code class="highlighter-rouge">Commit</code>
+ A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
published.</li>
<li><code class="highlighter-rouge">Commit Timeline</code>
Commit Timeline refers to the sequence of Commits that was applied in order on a dataset over its lifetime.</li>
- <li><code class="highlighter-rouge">File Slice</code>
- Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
+ <li><code class="highlighter-rouge">File Slice</code>
+ Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
Hudi uses MVCC to provide atomicity and isolation of readers from a writer. This means that a logical fileId will
have many physical versions of it. Each of these physical version of a file represents a complete view of the
file as of a commit and is called File Slice</li>
@@ -423,8 +424,6 @@ to the queries (i.e how data is read).</p>
<li>Merge On Read : Also provides a near-real time datasets in the order of 5 mins, by shifting some of the write cost, to the reads and merging incoming and on-disk data on-the-fly</li>
</ul>
-<div class="bs-callout bs-callout-info">Hudi is a young project. merge-on-read is currently underway. Get involved <a href="https://github.com/uber/Hudi/projects/1">here</a></div>
-
<p>Regardless of the storage type, Hudi organizes a datasets into a directory structure under a <code class="highlighter-rouge">basepath</code>,
very similar to Hive tables. Dataset is broken up into partitions, which are folders containing files for that partition.
Each partition uniquely identified by its <code class="highlighter-rouge">partitionpath</code>, which is relative to the basepath.</p>
@@ -444,11 +443,11 @@ commit, such that only columnar data exists. As a result, the write amplificatio
<p>Following illustrates how this works conceptually, when data written into copy-on-write storage and two queries running on top of it.</p>
-<figure><img class="docimage" src="images/Hudi_cow.png" alt="Hudi_cow.png" /></figure>
+<figure><img class="docimage" src="images/hudi_cow.png" alt="hudi_cow.png" /></figure>
<p>As data gets written, updates to existing file ids, produce a new version for that file id stamped with the commit and
inserts allocate a new file id and write its first version for that file id. These file versions and their commits are color coded above.
-Normal SQL queries running against such dataset (eg: select count(*) counting the total records in that partition), first checks the timeline for latest commit
+Normal SQL queries running against such dataset (eg: <code class="highlighter-rouge">select count(*)</code> counting the total records in that partition), first checks the timeline for latest commit
and filters all but latest versions of each file id. As you can see, an old query does not see the current inflight commit’s files colored in pink,
but a new query starting after the commit picks up the new data. Thus queries are immune to any write failures/partial writes and only run on committed data.</p>
@@ -470,7 +469,7 @@ their columnar base data, to keep the query performance in check (larger append
<p>Following illustrates how the storage works, and shows queries on both near-real time table and read optimized table.</p>
-<figure><img class="docimage" src="images/Hudi_mor.png" alt="Hudi_mor.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_mor.png" alt="hudi_mor.png" style="max-width: 1000px" /></figure>
<p>There are lot of interesting things happening in this example, which bring out the subleties in the approach.</p>
@@ -488,8 +487,6 @@ their columnar base data, to keep the query performance in check (larger append
published within X minutes in a consistent fashion.</li>
</ul>
-<div class="bs-callout bs-callout-info">Hudi is a young project. merge-on-read is currently underway. Get involved <a href="https://github.com/uber/hoodie/projects/1">here</a></div>
-
<p>The intention of merge on read storage, is to enable near real-time processing directly on top of Hadoop, as opposed to copying
data out to specialized systems, which may not be able to handle the data volume.</p>
@@ -567,9 +564,19 @@ data out to specialized systems, which may not be able to handle the data volume
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/configurations.html b/content/configurations.html
index be91882..5f1adb8 100644
--- a/content/configurations.html
+++ b/content/configurations.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -488,7 +489,7 @@
Actual value ontained by invoking .toString()</span></li>
<li><a href="#KEYGENERATOR_CLASS_OPT_KEY">KEYGENERATOR_CLASS_OPT_KEY</a> (Default: com.uber.hoodie.SimpleKeyGenerator) <br />
<span style="color:grey">Key generator class, that implements will extract the key out of incoming <code class="highlighter-rouge">Row</code> object</span></li>
- <li><a href="#COMMIT_METADATA_KEYPREFIX_OPT_KEY">COMMIT_METADATA_KEYPREFIX_OPT_KEY</a> (Default: _) <br />
+ <li><a href="#COMMIT_METADATA_KEYPREFIX_OPT_KEY">COMMIT_METADATA_KEYPREFIX_OPT_KEY</a> (Default: <code class="highlighter-rouge">_</code>) <br />
<span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span></li>
</ul>
@@ -518,31 +519,33 @@
<p>Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.</p>
-<ul>
- <li><strong>Write operations</strong> : Use <code class="highlighter-rouge">bulkinsert</code> to load new data into a table, and there on use <code class="highlighter-rouge">upsert</code>/<code class="highlighter-rouge">insert</code>.
- Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</li>
- <li><strong>Input Parallelism</strong> : By default, Hoodie tends to over-partition input (i.e <code class="highlighter-rouge">withParallelism(1500)</code>), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism <code class="highlighter-rouge">hoodie.[insert|upsert|bulkinsert].shuffle.parallelism</code> such that its atleast input_data_size/500MB</li>
- <li><strong>Off-heap memory</strong> : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like <code class="highlighter-rouge">spark.yarn.executor.memoryOverhead</code> or <code class="highlighter-rouge">spark.yarn.driver.memoryOverhead</code>, if you are running into such failures.</li>
- <li><strong>Spark Memory</strong> : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some <code class="highlighter-rouge">spark.storage.memoryFraction</code> will generally help boost performance.</li>
- <li><strong>Sizing files</strong> : Set <code class="highlighter-rouge">limitFileSize</code> above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.</li>
- <li><strong>Timeseries/Log data</strong> : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
- <ul>
- <li>Consider tuning the bloom filter accuracy via <code class="highlighter-rouge">.bloomFilterFPP()/bloomFilterNumEntries()</code> to achieve your target index look up time</li>
- <li>Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.</li>
- </ul>
- </li>
- <li><strong>GC Tuning</strong> : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
- <ul>
- <li>[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions : ``-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tm [...]
- <li>If it keeps OOMing still, reduce spark memory conservatively: <code class="highlighter-rouge">spark.memory.fraction=0.2, spark.memory.storageFraction=0.2</code> allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)</li>
- </ul>
- </li>
-</ul>
+<p><strong>Write operations</strong> : Use <code class="highlighter-rouge">bulkinsert</code> to load new data into a table, and there on use <code class="highlighter-rouge">upsert</code>/<code class="highlighter-rouge">insert</code>.
+ Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</p>
+
+<p><strong>Input Parallelism</strong> : By default, Hoodie tends to over-partition input (i.e <code class="highlighter-rouge">withParallelism(1500)</code>), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism <code class="highlighter-rouge">hoodie.[insert|upsert|bulkinsert].shuffle.parallelism</code> such that its atleast input_data_size/500MB</p>
+
+<p><strong>Off-heap memory</strong> : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like <code class="highlighter-rouge">spark.yarn.executor.memoryOverhead</code> or <code class="highlighter-rouge">spark.yarn.driver.memoryOverhead</code>, if you are running into such failures.</p>
+
+<p><strong>Spark Memory</strong> : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some <code class="highlighter-rouge">spark.storage.memoryFraction</code> will generally help boost performance.</p>
+
+<p><strong>Sizing files</strong> : Set <code class="highlighter-rouge">limitFileSize</code> above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.</p>
+
+<p><strong>Timeseries/Log data</strong> : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
+ - Consider tuning the bloom filter accuracy via <code class="highlighter-rouge">.bloomFilterFPP()/bloomFilterNumEntries()</code> to achieve your target index look up time
+ - Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.</p>
+
+<p><strong>GC Tuning</strong> : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
+[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions :</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+</code></pre>
+</div>
+
+<p>If it keeps OOMing still, reduce spark memory conservatively: <code class="highlighter-rouge">spark.memory.fraction=0.2, spark.memory.storageFraction=0.2</code> allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)</p>
<p>Below is a full working production config</p>
-<p>```
- spark.driver.extraClassPath /etc/hive/conf
+<div class="highlighter-rouge"><pre class="highlight"><code> spark.driver.extraClassPath /etc/hive/conf
spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
spark.driver.maxResultSize 2g
spark.driver.memory 4g
@@ -551,9 +554,9 @@
spark.executor.id driver
spark.executor.instances 300
spark.executor.memory 6g
- spark.rdd.compress true</p>
+ spark.rdd.compress true
-<p>spark.kryoserializer.buffer.max 512m
+ spark.kryoserializer.buffer.max 512m
spark.serializer org.apache.spark.serializer.KryoSerializer
spark.shuffle.memoryFraction 0.2
spark.shuffle.service.enabled true
@@ -561,12 +564,14 @@
spark.storage.memoryFraction 0.6
spark.submit.deployMode cluster
spark.task.cpus 1
- spark.task.maxFailures 4</p>
+ spark.task.maxFailures 4
-<p>spark.yarn.driver.memoryOverhead 1024
+ spark.yarn.driver.memoryOverhead 1024
spark.yarn.executor.memoryOverhead 3072
spark.yarn.max.executor.failures 100
- ```</p>
+
+</code></pre>
+</div>
<div class="tags">
@@ -582,9 +587,19 @@
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/dev_setup.html b/content/contributing.html
similarity index 52%
rename from content/dev_setup.html
rename to content/contributing.html
index 5f8a314..1901952 100644
--- a/content/dev_setup.html
+++ b/content/contributing.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li class="dropdownActive"><a href="dev_setup.html">Setup</a></li>
+ <li class="dropdownActive"><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -336,39 +337,116 @@
+
+
-<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
-<script>
-$( document ).ready(function() {
- // Handler for .ready() called.
-$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
+ <h2 id="pre-requisites">Pre-requisites</h2>
-/* this offset helps account for the space taken up by the floating toolbar. */
-$('#toc').on('click', 'a', function() {
- var target = $(this.getAttribute('href'))
- , scroll_target = target.offset().top
+<p>To contribute code, you need</p>
- $(window).scrollTop(scroll_target - 10);
- return false
-})
-
-});
-</script>
+<ul>
+ <li>a GitHub account</li>
+ <li>a Linux (or) macOS development environment with Java JDK 8, Apache Maven (3.x+) installed</li>
+ <li><a href="https://www.docker.com/">Docker</a> installed for running demo, integ tests or building website</li>
+ <li>for large contributions, a signed <a href="https://www.apache.org/licenses/icla.pdf">Individual Contributor License
+Agreement</a> (ICLA) to the Apache
+Software Foundation (ASF).</li>
+ <li>(Recommended) Create an account on <a href="https://issues.apache.org/jira/projects/HUDI/summary">JIRA</a> to open issues/find similar issues.</li>
+ <li>(Recommended) Join our dev mailing list & slack channel, listed on <a href="community.html">community</a> page.</li>
+</ul>
+
+<h2 id="ide-setup">IDE Setup</h2>
+
+<p>To contribute, you would need to fork the Hudi code on Github & then clone your own fork locally. Once cloned, we recommend building as per instructions on <a href="quickstart.html">quickstart</a></p>
+
+<p>We have embraced the code style largely based on <a href="https://google.github.io/styleguide/javaguide.html">google format</a>. Please setup your IDE with style files from <a href="../style/">here</a>.
+These instructions have been tested on IntelliJ. We also recommend setting up the <a href="https://plugins.jetbrains.com/plugin/7642-save-actions">Save Action Plugin</a> to auto format & organize imports on save. The Maven Compilation life-cycle will fail if there are checkstyle violations.</p>
+
+<h2 id="lifecycle">Lifecycle</h2>
+
+<p>Here’s a typical lifecycle of events to contribute to Hudi.</p>
+
+<ul>
+ <li>[Recommended] Share your intent on the mailing list, so that community can provide early feedback, point out any similar JIRAs or HIPs.</li>
+ <li>[Optional] If you want to get involved, but don’t have a project in mind, please check JIRA for small, quick-starters.</li>
+ <li>[Optional] Familiarize yourself with internals of Hudi using content on this page, as well as <a href="https://cwiki.apache.org/confluence/display/HUDI">wiki</a></li>
+ <li>Once you finalize on a project/task, please open a new JIRA or assign an existing one to yourself. (If you don’t have perms to do this, please email the dev mailing list with your JIRA id and a small intro for yourself. We’d be happy to add you as a contributor)</li>
+ <li>Make your code change
+ <ul>
+ <li>Every source file needs to include the Apache license header. Every new dependency needs to
+have an open source license <a href="https://www.apache.org/legal/resolved.html#criteria">compatible</a> with Apache.</li>
+ <li>Get existing tests to pass using <code class="highlighter-rouge">mvn clean install -DskipITs</code></li>
+ <li>Add adequate tests for your new functionality</li>
+ <li>[Optional] For involved changes, its best to also run the entire integration test suite using <code class="highlighter-rouge">mvn clean install</code></li>
+ <li>For website changes, please build the site locally & test navigation, formatting & links thoroughly</li>
+ </ul>
+ </li>
+ <li>Format commit messages and the pull request title like <code class="highlighter-rouge">[HUDI-XXX] Fixes bug in Spark Datasource</code>,
+where you replace HUDI-XXX with the appropriate JIRA issue.</li>
+ <li>Push your commit to your own fork/branch & create a pull request (PR) against the Hudi repo.</li>
+ <li>If you don’t hear back within 3 days on the PR, please send an email to dev @ mailing list.</li>
+ <li>Address code review comments & keep pushing changes to your fork/branch, which automatically updates the PR</li>
+ <li>Before your change can be merged, it should be squashed into a single commit for cleaner commit history.</li>
+</ul>
-<div id="toc"></div>
+<h2 id="releases">Releases</h2>
-
+<ul>
+ <li>Apache Hudi community plans to do minor version releases every 6 weeks or so.</li>
+ <li>If your contribution merged onto <code class="highlighter-rouge">master</code> branch after the last release, it will become part of next release.</li>
+ <li>Website changes are regenerated once a week (until automation in place to reflect immediately)</li>
+</ul>
+<h2 id="accounts-and-permissions">Accounts and Permissions</h2>
+
+<ul>
+ <li>
+ <p><a href="https://issues.apache.org/jira/projects/HUDI/issues">Hudi issue tracker (JIRA)</a>:
+Anyone can access it and browse issues. Anyone can register an account and login
+to create issues or add comments. Only contributors can be assigned issues. If
+you want to be assigned issues, a PMC member can add you to the project contributor
+group. Email the dev mailing list to ask to be added as a contributor, and include your ASF Jira username.</p>
+ </li>
+ <li>
+ <p><a href="https://cwiki.apache.org/confluence/display/HUDI">Hudi Wiki Space</a>:
+Anyone has read access. If you wish to contribute changes, please create an account and
+request edit access on the dev@ mailing list (include your Wiki account user ID).</p>
+ </li>
+ <li>
+ <p>Pull requests can only be merged by a HUDI committer, listed <a href="https://incubator.apache.org/projects/hudi.html">here</a></p>
+ </li>
+ <li>
+ <p><a href="https://www.apache.org/foundation/voting.html">Voting on a release</a>: Everyone can vote.
+Only Hudi PMC members should mark their votes as binding.</p>
+ </li>
+</ul>
-
+<h2 id="communication">Communication</h2>
+
+<p>All communication is expected to align with the <a href="https://www.apache.org/foundation/policies/conduct">Code of Conduct</a>.
+Discussion about contributing code to Hudi happens on the <a href="community.html">dev@ mailing list</a>. Introduce yourself!</p>
+
+<h2 id="code--project-structure">Code & Project Structure</h2>
+
+<ul>
+ <li><code class="highlighter-rouge">docker</code> : Docker containers used by demo and integration tests. Brings up a mini data ecosystem locally</li>
+ <li><code class="highlighter-rouge">hoodie-cli</code> : CLI to inspect, manage and administer datasets</li>
+ <li><code class="highlighter-rouge">hoodie-client</code> : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table</li>
+ <li><code class="highlighter-rouge">hoodie-common</code> : Common classes used across modules</li>
+ <li><code class="highlighter-rouge">hoodie-hadoop-mr</code> : InputFormat implementations for ReadOptimized, Incremental, Realtime views</li>
+ <li><code class="highlighter-rouge">hoodie-hive</code> : Manage hive tables off Hudi datasets and houses the HiveSyncTool</li>
+ <li><code class="highlighter-rouge">hoodie-integ-test</code> : Longer running integration test processes</li>
+ <li><code class="highlighter-rouge">hoodie-spark</code> : Spark datasource for writing and reading Hudi datasets. Streaming sink.</li>
+ <li><code class="highlighter-rouge">hoodie-utilities</code> : Houses tools like DeltaStreamer, SnapshotCopier</li>
+ <li><code class="highlighter-rouge">packaging</code> : Poms for building out bundles for easier drop in to Spark, Hive, Presto</li>
+ <li><code class="highlighter-rouge">style</code> : Code formatting, checkstyle files</li>
+</ul>
- <h3 id="code-style">Code Style</h3>
+<h2 id="website">Website</h2>
-<p>We have embraced the code style largely based on <a href="https://google.github.io/styleguide/javaguide.html">google format</a>.
- Please setup your IDE with style files from <a href="../style/">here</a>
- We also recommend setting up the <a href="https://plugins.jetbrains.com/plugin/7642-save-actions">Save Action Plugin</a> to auto format & organize imports on save.
- The Maven Compilation life-cycle will fail if there are checkstyle violations.</p>
+<p><a href="https://hudi.apache.org">Apache Hudi site</a> is hosted on a special <code class="highlighter-rouge">asf-site</code> branch. Please follow the <code class="highlighter-rouge">README</code> file under <code class="highlighter-rouge">docs</code> on that branch for
+instructions on making changes to the website.</p>
<div class="tags">
@@ -384,9 +462,19 @@ $('#toc').on('click', 'a', function() {
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/css/customstyles.css b/content/css/customstyles.css
index 676c804..d6667a5 100644
--- a/content/css/customstyles.css
+++ b/content/css/customstyles.css
@@ -83,7 +83,7 @@ padding-top: 60px;
margin-top: -40px
}
-body h1 {margin-top:40px;}
+body h1 {margin-top:80px;}
.post-content img {
margin: 12px 0px 3px 0px;
@@ -1178,4 +1178,4 @@ div.box.box1 {
h4.panel-title {
padding-top: 0px;
margin-top: 0px;
-}
\ No newline at end of file
+}
diff --git a/content/css/lavish-bootstrap.css b/content/css/lavish-bootstrap.css
index ff64532..a050c9a 100644
--- a/content/css/lavish-bootstrap.css
+++ b/content/css/lavish-bootstrap.css
@@ -3643,6 +3643,14 @@ textarea.input-group-sm > .input-group-btn > .btn {
.navbar-brand:focus {
text-decoration: none;
}
+.navbar-incubate {
+ text-align: center;
+ font-size: 24px;
+ color: grey;
+}
+
+
+
@media (min-width: 768px) {
.navbar > .container .navbar-brand {
margin-left: -15px;
diff --git a/content/css/theme-blue.css b/content/css/theme-blue.css
index f9aa248..9a923ef 100644
--- a/content/css/theme-blue.css
+++ b/content/css/theme-blue.css
@@ -95,11 +95,10 @@ div.sidebarTitle {
}
li.sidebarTitle {
- margin-top:40px;
+ margin-top:80px;
font-weight:normal;
font-size:130%;
color: #333;
margin-bottom:10px;
margin-left: 5px;
-
}
diff --git a/content/feed.xml b/content/feed.xml
index 3a620b8..b21704e 100644
--- a/content/feed.xml
+++ b/content/feed.xml
@@ -2,14 +2,28 @@
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
<channel>
<title></title>
- <description>Apache Hudi (pronounced “Hoodie”) is a Spark Library, that provides upserts and incremental processing capaibilities on Hadoop datasets</description>
+ <description>Apache Hudi (pronounced “Hoodie”) provides upserts and incremental processing capaibilities on Big Data</description>
<link>http://0.0.0.0:4000/</link>
<atom:link href="http://0.0.0.0:4000/feed.xml" rel="self" type="application/rss+xml"/>
- <pubDate>Sat, 16 Feb 2019 04:53:14 +0000</pubDate>
- <lastBuildDate>Sat, 16 Feb 2019 04:53:14 +0000</lastBuildDate>
+ <pubDate>Mon, 25 Feb 2019 20:49:33 +0000</pubDate>
+ <lastBuildDate>Mon, 25 Feb 2019 20:49:33 +0000</lastBuildDate>
<generator>Jekyll v3.3.1</generator>
<item>
+ <title>Hudi entered Apache Incubator</title>
+ <description><p>In the coming weeks, we will be moving in our new home on the Apache Incubator.</p>
+
+</description>
+ <pubDate>Fri, 18 Jan 2019 00:00:00 +0000</pubDate>
+ <link>http://0.0.0.0:4000/strata-talk.html</link>
+ <guid isPermaLink="true">http://0.0.0.0:4000/strata-talk.html</guid>
+
+ <category>news</category>
+
+
+ </item>
+
+ <item>
<title>Connect with us at Strata San Jose March 2017</title>
<description><p>We will be presenting Hoodie &amp; general concepts around how incremental processing works at Uber.
Catch our talk <strong>“Incremental Processing on Hadoop At Uber”</strong></p>
diff --git a/content/gcs_hoodie.html b/content/gcs_hoodie.html
index 847b72b..f90992d 100644
--- a/content/gcs_hoodie.html
+++ b/content/gcs_hoodie.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -415,9 +416,19 @@
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/images/asf_logo.svg b/content/images/asf_logo.svg
new file mode 100644
index 0000000..620694c
--- /dev/null
+++ b/content/images/asf_logo.svg
@@ -0,0 +1,210 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0) -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
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diff --git a/content/images/hoodie_cow.png b/content/images/hoodie_cow.png
deleted file mode 100644
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diff --git a/content/images/hoodie_intro_1.png b/content/images/hoodie_intro_1.png
index dd8977a..6220b46 100644
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diff --git a/content/images/hoodie_mor.png b/content/images/hoodie_mor.png
deleted file mode 100644
index 8d7d902..0000000
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diff --git a/content/images/hudi_cow.png b/content/images/hudi_cow.png
new file mode 100644
index 0000000..40aca71
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diff --git a/content/images/hudi_mor.png b/content/images/hudi_mor.png
new file mode 100644
index 0000000..100b8f0
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diff --git a/content/images/hoodie_timeline.png b/content/images/hudi_timeline.png
similarity index 100%
rename from content/images/hoodie_timeline.png
rename to content/images/hudi_timeline.png
diff --git a/content/implementation.html b/content/implementation.html
index 1e9c4d6..d649a70 100644
--- a/content/implementation.html
+++ b/content/implementation.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -362,7 +363,7 @@ Hudi upsert/insert is merely a Spark DAG, that can be broken into two big pieces
<p>Hudi currently provides two choices for indexes : <code class="highlighter-rouge">BloomIndex</code> and <code class="highlighter-rouge">HBaseIndex</code> to map a record key into the file id to which it belongs to. This enables
us to speed up upserts significantly, without scanning over every record in the dataset. Hudi Indices can be classified based on
-their ability to lookup records across partition. A <code class="highlighter-rouge">global</code> index does not need partition information for finding the file-id for a record key
+their ability to lookup records across partition. A <code class="highlighter-rouge">global</code> index does not need partition information for finding the file-id for a record key
but a <code class="highlighter-rouge">non-global</code> does.</p>
<h4 id="hbase-index-global">HBase Index (global)</h4>
@@ -402,7 +403,7 @@ Any remaining records after that, are again packed into new file id groups, agai
<p>In this storage, index updation is a no-op, since the bloom filters are already written as a part of committing data.</p>
-<p>In the case of Copy-On-Write, a single parquet file constitutes one <code class="highlighter-rouge">file slice</code> which contains one complete version of
+<p>In the case of Copy-On-Write, a single parquet file constitutes one <code class="highlighter-rouge">file slice</code> which contains one complete version of
the file</p>
<figure><img class="docimage" src="images/hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" style="max-width: 1000px" /></figure>
@@ -416,7 +417,7 @@ the file</p>
<h5 id="merge-on-read-writer">Merge On Read Writer</h5>
<p>At a high level, Merge-On-Read Writer goes through same stages as Copy-On-Write writer in ingesting data.
- The key difference here is that updates are appended to latest log (delta) file belonging to the latest file slice
+ The key difference here is that updates are appended to latest log (delta) file belonging to the latest file slice
without merging. For inserts, Hudi supports 2 modes:</p>
<ol>
@@ -425,7 +426,7 @@ the file</p>
embedded in parquer files. Hudi treats writing new records in the same way as inserting to Copy-On-Write files.</li>
</ol>
-<p>As in the case of Copy-On-Write, the input tagged records are partitioned such that all upserts destined to
+<p>As in the case of Copy-On-Write, the input tagged records are partitioned such that all upserts destined to
a <code class="highlighter-rouge">file id</code> are grouped together. This upsert-batch is written as one or more log-blocks written to log-files.
Hudi allows clients to control log file sizes (See <a href="../configurations">Storage Configs</a>)</p>
@@ -448,54 +449,55 @@ compacting these log-files asynchronously to create read-optimized views.</p>
to be compacted atomically in a single compaction commit. Hudi allows pluggable strategies for choosing
file slices for each compaction runs. This step is typically done inline by Writer process as Hudi expects
only one schedule is being generated at a time which allows Hudi to enforce the constraint that pending compaction
-plans do not step on each other file-slices. This constraint allows for multiple concurrent <code class="highlighter-rouge">Compactors</code> to run at
+plans do not step on each other file-slices. This constraint allows for multiple concurrent <code class="highlighter-rouge">Compactors</code> to run at
the same time. Some of the common strategies used for choosing <code class="highlighter-rouge">file slice</code> for compaction are:
<ul>
- <li>BoundedIO - Limit the number of file slices chosen for a compaction plan by expected total IO (read + write)
+ <li>BoundedIO - Limit the number of file slices chosen for a compaction plan by expected total IO (read + write)
needed to complete compaction run</li>
<li>Log File Size - Prefer file-slices with larger amounts of delta log data to be merged</li>
- <li>Day Based - Prefer file slice belonging to latest day partitions
-<code class="highlighter-rouge">
- API for scheduling compaction
- /**
- * Schedules a new compaction instant
- * @param extraMetadata
- * @return Compaction Instant timestamp if a new compaction plan is scheduled
- */
- Optional<String> scheduleCompaction(Optional<Map<String, String>> extraMetadata) throws IOException;
-</code></li>
+ <li>Day Based - Prefer file slice belonging to latest day partitions</li>
</ul>
</li>
- <li>
- <p><code class="highlighter-rouge">Compactor</code> : Hudi provides a separate API in Write Client to execute a compaction plan. The compaction
+ <li><code class="highlighter-rouge">Compactor</code> : Hudi provides a separate API in Write Client to execute a compaction plan. The compaction
plan (just like a commit) is identified by a timestamp. Most of the design and implementation complexities for Async
Compaction is for guaranteeing snapshot isolation to readers and writer when
multiple concurrent compactors are running. Typical compactor deployment involves launching a separate
spark application which executes pending compactions when they become available. The core logic of compacting
file slices in the Compactor is very similar to that of merging updates in a Copy-On-Write table. The only
-difference being in the case of compaction, there is an additional step of merging the records in delta log-files.</p>
+difference being in the case of compaction, there is an additional step of merging the records in delta log-files.</li>
+</ul>
- <p>Here are the main API to lookup and execute a compaction plan.
-```
- Main API in HoodieWriteClient for running Compaction:
+<p>Here are the main API to lookup and execute a compaction plan.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code> Main API in HoodieWriteClient for running Compaction:
/**
* Performs Compaction corresponding to instant-time
* @param compactionInstantTime Compaction Instant Time
* @return
* @throws IOException
*/
- public JavaRDD<WriteStatus> compact(String compactionInstantTime) throws IOException;</WriteStatus></p>
+ public JavaRDD<WriteStatus> compact(String compactionInstantTime) throws IOException;
- <p>To lookup all pending compactions, use the API defined in HoodieReadClient</p>
+ To lookup all pending compactions, use the API defined in HoodieReadClient
- <p>/**
+ /**
* Return all pending compactions with instant time for clients to decide what to compact next.
* @return
*/
- public List<Pair<String, HoodieCompactionPlan» getPendingCompactions();
-```</p>
- </li>
-</ul>
+ public List<Pair<String, HoodieCompactionPlan>> getPendingCompactions();
+</code></pre>
+</div>
+<p>API for scheduling compaction</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>
+ /**
+ * Schedules a new compaction instant
+ * @param extraMetadata
+ * @return Compaction Instant timestamp if a new compaction plan is scheduled
+ */
+ Optional<String> scheduleCompaction(Optional<Map<String, String>> extraMetadata) throws IOException;
+</code></pre>
+</div>
<p>Refer to <strong>hoodie-client/src/test/java/HoodieClientExample.java</strong> class for an example of how compaction
is scheduled and executed.</p>
@@ -525,61 +527,61 @@ plan to be run to figure out the number of file slices being compacted and choos
<p>For the purpose of this section, it is important to distinguish between 2 types of commits as pertaining to the file-group:</p>
<p>A commit which generates a merged and read-optimized file-slice is called <code class="highlighter-rouge">snapshot commit</code> (SC) with respect to that file-group.
-A commit which merely appended the new/updated records assigned to the file-group into a new log block is called <code class="highlighter-rouge">delta commit</code> (DC)
+A commit which merely appended the new/updated records assigned to the file-group into a new log block is called <code class="highlighter-rouge">delta commit</code> (DC)
with respect to that file-group.</p>
<h3 id="algorithm">Algorithm</h3>
<p>The algorithm is described with an illustration. Let us assume a scenario where there are commits SC1, DC2, DC3 that have
-already completed on a data-set. Commit DC4 is currently ongoing with the writer (ingestion) process using it to upsert data.
-Let us also imagine there are a set of file-groups (FG1 … FGn) in the data-set whose latest version (<code class="highlighter-rouge">File-Slice</code>)
-contains the base file created by commit SC1 (snapshot-commit in columnar format) and a log file containing row-based
+already completed on a data-set. Commit DC4 is currently ongoing with the writer (ingestion) process using it to upsert data.
+Let us also imagine there are a set of file-groups (FG1 … FGn) in the data-set whose latest version (<code class="highlighter-rouge">File-Slice</code>)
+contains the base file created by commit SC1 (snapshot-commit in columnar format) and a log file containing row-based
log blocks of 2 delta-commits (DC2 and DC3).</p>
<figure><img class="docimage" src="images/async_compac_1.png" alt="async_compac_1.png" style="max-width: 1000px" /></figure>
<ul>
- <li>Writer (Ingestion) that is going to commit “DC4” starts. The record updates in this batch are grouped by file-groups
-and appended in row formats to the corresponding log file as delta commit. Let us imagine a subset of file-groups has
+ <li>Writer (Ingestion) that is going to commit “DC4” starts. The record updates in this batch are grouped by file-groups
+and appended in row formats to the corresponding log file as delta commit. Let us imagine a subset of file-groups has
this new log block (delta commit) DC4 added.</li>
<li>
- <p>Before the writer job completes, it runs the compaction strategy to decide which file-group to compact by compactor
-and creates a new compaction-request commit SC5. This commit file is marked as “requested” with metadata denoting
+ <p>Before the writer job completes, it runs the compaction strategy to decide which file-group to compact by compactor
+and creates a new compaction-request commit SC5. This commit file is marked as “requested” with metadata denoting
which fileIds to compact (based on selection policy). Writer completes without running compaction (will be run async).</p>
<figure><img class="docimage" src="images/async_compac_2.png" alt="async_compac_2.png" style="max-width: 1000px" /></figure>
</li>
<li>
- <p>Writer job runs again ingesting next batch. It starts with commit DC6. It reads the earliest inflight compaction
-request marker commit in timeline order and collects the (fileId, Compaction Commit Id “CcId” ) pairs from meta-data.
-Ingestion DC6 ensures a new file-slice with base-commit “CcId” gets allocated for the file-group.
-The Writer will simply append records in row-format to the first log-file (as delta-commit) assuming the
+ <p>Writer job runs again ingesting next batch. It starts with commit DC6. It reads the earliest inflight compaction
+request marker commit in timeline order and collects the (fileId, Compaction Commit Id “CcId” ) pairs from meta-data.
+Ingestion DC6 ensures a new file-slice with base-commit “CcId” gets allocated for the file-group.
+The Writer will simply append records in row-format to the first log-file (as delta-commit) assuming the
base-file (“Phantom-Base-File”) will be created eventually by the compactor.</p>
<figure><img class="docimage" src="images/async_compac_3.png" alt="async_compac_3.png" style="max-width: 1000px" /></figure>
</li>
<li>
- <p>Compactor runs at some time and commits at “Tc” (concurrently or before/after Ingestion DC6). It reads the commit-timeline
-and finds the first unprocessed compaction request marker commit. Compactor reads the commit’s metadata finding the
-file-slices to be compacted. It compacts the file-slice and creates the missing base-file (“Phantom-Base-File”)
-with “CCId” as the commit-timestamp. Compactor then marks the compaction commit timestamp as completed.
-It is important to realize that at data-set level, there could be different file-groups requesting compaction at
+ <p>Compactor runs at some time and commits at “Tc” (concurrently or before/after Ingestion DC6). It reads the commit-timeline
+and finds the first unprocessed compaction request marker commit. Compactor reads the commit’s metadata finding the
+file-slices to be compacted. It compacts the file-slice and creates the missing base-file (“Phantom-Base-File”)
+with “CCId” as the commit-timestamp. Compactor then marks the compaction commit timestamp as completed.
+It is important to realize that at data-set level, there could be different file-groups requesting compaction at
different commit timestamps.</p>
<figure><img class="docimage" src="images/async_compac_4.png" alt="async_compac_4.png" style="max-width: 1000px" /></figure>
</li>
- <li>Near Real-time reader interested in getting the latest snapshot will have 2 cases. Let us assume that the
+ <li>Near Real-time reader interested in getting the latest snapshot will have 2 cases. Let us assume that the
incremental ingestion (writer at DC6) happened before the compaction (some time “Tc”’).<br />
The below description is with regards to compaction from file-group perspective.
<ul>
- <li><code class="highlighter-rouge">Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”</code>:
-Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
-merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
-a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
-For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
+ <li><code class="highlighter-rouge">Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”</code>:
+Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
+merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
+a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
+For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
and merge on the fly.</li>
- <li><code class="highlighter-rouge">Reader querying at time after compaction finished (> “Tc”)</code> : In this case, reader will not find any pending
-compactions in the timeline and will simply have the current behavior of reading the latest file-slice and
+ <li><code class="highlighter-rouge">Reader querying at time after compaction finished (> “Tc”)</code> : In this case, reader will not find any pending
+compactions in the timeline and will simply have the current behavior of reading the latest file-slice and
merging on-the-fly.</li>
</ul>
</li>
@@ -587,7 +589,7 @@ merging on-the-fly.</li>
</ul>
<p>The above algorithm explains Async compaction w.r.t a single compaction run on a single file-group. It is important
-to note that multiple compaction plans can be run concurrently as they are essentially operating on different
+to note that multiple compaction plans can be run concurrently as they are essentially operating on different
file-groups.</p>
<h2 id="performance">Performance</h2>
@@ -641,9 +643,19 @@ with no impact on queries. Following charts compare the Hudi vs non-Hudi dataset
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/incremental_processing.html b/content/incremental_processing.html
index f4d31da..a694881 100644
--- a/content/incremental_processing.html
+++ b/content/incremental_processing.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -421,7 +422,12 @@ Usage: <main class> [options]
exist first time around. If exists, expected to be a Hudi dataset)
* --target-table
name of the target table in Hive
-
+ --transformer-class
+ subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
+ transform raw source dataset to a target dataset (conforming to target
+ schema) before writing. Default : Not set. E:g -
+ com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
+ allows a SQL query template to be passed as a transformation function)
</code></pre>
</div>
@@ -655,9 +661,19 @@ is the lack of support for self-joining the same table in mixed mode (normal and
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/index.html b/content/index.html
index 4ffe717..bd31b4d 100644
--- a/content/index.html
+++ b/content/index.html
@@ -3,9 +3,9 @@
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
-<meta name="description" content="Hudi lowers data latency across the board, while simultaneously achieving orders of magnitude of efficiency over traditional batch processing.">
+<meta name="description" content="Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing.">
<meta name="keywords" content="getting_started, homepage">
-<title>Apache Hudi Overview | Hudi</title>
+<title>What is Hudi? | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -157,7 +158,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Apache Hudi Overview page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the What is Hudi? page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -175,7 +176,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="Apache Hudi Overview">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="What is Hudi?">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -326,7 +327,7 @@
<!-- Content Column -->
<div class="col-md-9">
<div class="post-header">
- <h1 class="post-title-main">Apache Hudi Overview</h1>
+ <h1 class="post-title-main">What is Hudi?</h1>
</div>
@@ -334,7 +335,7 @@
<div class="post-content">
- <div class="summary">Hudi lowers data latency across the board, while simultaneously achieving orders of magnitude of efficiency over traditional batch processing.</div>
+ <div class="summary">Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing.</div>
@@ -365,21 +366,19 @@ $('#toc').on('click', 'a', function() {
- <p>Hudi (pronounced “Hoodie”) manages storage of large analytical datasets on <a href="http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html">HDFS</a> or cloud and serves them out via two types of tables</p>
+ <p>Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets on <a href="http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html">HDFS</a> or cloud stores and provides three logical views for query access.</p>
<ul>
- <li><strong>Read Optimized Table</strong> - Provides excellent query performance via purely columnar storage (e.g. <a href="https://parquet.apache.org/">Parquet</a>)</li>
+ <li><strong>Read Optimized View</strong> - Provides excellent query performance on pure columnar storage, much like plain <a href="https://parquet.apache.org/">Parquet</a> tables.</li>
+ <li><strong>Incremental View</strong> - Provides a change stream out of the dataset to feed downstream jobs/ETLs.</li>
<li><strong>Near-Real time Table</strong> - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + <a href="http://avro.apache.org/docs/current/mr.html">Avro</a>)</li>
</ul>
<figure><img class="docimage" src="images/hoodie_intro_1.png" alt="hoodie_intro_1.png" /></figure>
-<p>By carefully managing how data is laid out in storage & how it’s exposed to queries, Hoodie is able to power a rich data ecosystem where external sources can be ingested into Hadoop in near real-time. The ingested data is then available for interactive SQL Engines like <a href="https://prestodb.io">Presto</a> & <a href="https://spark.apache.org/sql/">Spark</a>, while at the same time capable of being consumed incrementally from processing/ETL frameworks like <a href="https://h [...]
-
-<p>Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access.</p>
-
-<div class="bs-callout bs-callout-info">Hudi is a new project. Near Real-Time Table implementation is currently underway. Get involved <a href="https://github.com/uber/hoodie/projects/1">here</a></div>
+<p>By carefully managing how data is laid out in storage & how it’s exposed to queries, Hudi is able to power a rich data ecosystem where external sources can be ingested in near real-time and made available for interactive SQL Engines like <a href="https://prestodb.io">Presto</a> & <a href="https://spark.apache.org/sql/">Spark</a>, while at the same time capable of being consumed incrementally from processing/ETL frameworks like <a href="https://hive.apache.org/">Hive</a> & [...]
+<p>Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access. See <a href="quickstart.html">quickstart</a> for a demo.</p>
<div class="tags">
@@ -403,9 +402,19 @@ $('#toc').on('click', 'a', function() {
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/js/mydoc_scroll.html b/content/js/mydoc_scroll.html
index bc22ec4..b23a6ad 100644
--- a/content/js/mydoc_scroll.html
+++ b/content/js/mydoc_scroll.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -615,9 +616,19 @@ $('#small-box-links').localScroll({
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
-<span>Page last updated:</span> November 30, 2015<br/> Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/migration_guide.html b/content/migration_guide.html
index 8b1793e..7bcfa1d 100644
--- a/content/migration_guide.html
+++ b/content/migration_guide.html
@@ -3,9 +3,9 @@
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
-<meta name="description" content="">
-<meta name="keywords" content=" ">
-<title> | Hudi</title>
+<meta name="description" content="In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset">
+<meta name="keywords" content=" migration guide">
+<title>Migration Guide | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -157,7 +158,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Migration Guide page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -175,7 +176,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="Migration Guide">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -326,7 +327,7 @@
<!-- Content Column -->
<div class="col-md-9">
<div class="post-header">
- <h1 class="post-title-main"></h1>
+ <h1 class="post-title-main">Migration Guide</h1>
</div>
@@ -334,99 +335,72 @@
<div class="post-content">
-
-
-
-<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
-<script>
-$( document ).ready(function() {
- // Handler for .ready() called.
-
-$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
-
-/* this offset helps account for the space taken up by the floating toolbar. */
-$('#toc').on('click', 'a', function() {
- var target = $(this.getAttribute('href'))
- , scroll_target = target.offset().top
-
- $(window).scrollTop(scroll_target - 10);
- return false
-})
-
-});
-</script>
-
-<div id="toc"></div>
+ <div class="summary">In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset</div>
+
- <hr />
-<p>title: Migration Guide
-keywords: migration guide
-sidebar: mydoc_sidebar
-permalink: migration_guide.html
-toc: false
-summary: In this page, we will discuss some available tools for migrating your existing dataset into a Hudi managed
-dataset</p>
-
-<p>Hudi maintains metadata such as commit timeline and indexes to manage a dataset. The commit timelines helps to understand the actions happening on a dataset as well as the current state of a dataset. Indexes are used by Hudi to maintain a record key to file id mapping to efficiently locate a record. At the moment, Hudi supports writing only parquet columnar formats.
+ <p>Hudi maintains metadata such as commit timeline and indexes to manage a dataset. The commit timelines helps to understand the actions happening on a dataset as well as the current state of a dataset. Indexes are used by Hudi to maintain a record key to file id mapping to efficiently locate a record. At the moment, Hudi supports writing only parquet columnar formats.
To be able to start using Hudi for your existing dataset, you will need to migrate your existing dataset into a Hudi managed dataset. There are a couple of ways to achieve this.</p>
<h2 id="approaches">Approaches</h2>
-<h3 id="approach-1">Approach 1</h3>
+<h4 id="use-hudi-for-new-partitions-alone">Use Hudi for new partitions alone</h4>
-<p>Hudi can be used to manage an existing dataset without affecting/altering the historical data already present in the
-dataset. Hudi has been implemented to be compatible with such a mixed dataset with a caveat that either the complete
-Hive partition is Hudi managed or not. Thus the lowest granularity at which Hudi manages a dataset is a Hive
-partition. Start using the datasource API or the WriteClient to write to the dataset and make sure you start writing
+<p>Hudi can be used to manage an existing dataset without affecting/altering the historical data already present in the
+dataset. Hudi has been implemented to be compatible with such a mixed dataset with a caveat that either the complete
+Hive partition is Hudi managed or not. Thus the lowest granularity at which Hudi manages a dataset is a Hive
+partition. Start using the datasource API or the WriteClient to write to the dataset and make sure you start writing
to a new partition or convert your last N partitions into Hudi instead of the entire table. Note, since the historical
- partitions are not managed by HUDI, none of the primitives provided by HUDI work on the data in those partitions. More concretely, one cannot perform upserts or incremental pull on such older partitions not managed by the HUDI dataset.
+ partitions are not managed by HUDI, none of the primitives provided by HUDI work on the data in those partitions. More concretely, one cannot perform upserts or incremental pull on such older partitions not managed by the HUDI dataset.
Take this approach if your dataset is an append only type of dataset and you do not expect to perform any updates to existing (or non Hudi managed) partitions.</p>
-<h3 id="approach-2">Approach 2</h3>
+<h4 id="convert-existing-dataset-to-hudi">Convert existing dataset to Hudi</h4>
<p>Import your existing dataset into a Hudi managed dataset. Since all the data is Hudi managed, none of the limitations
- of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
- make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
+ of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
+ make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
there are other additional advantages of doing this. Hudi automatically manages file sizes of a Hudi managed dataset
- . You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
- adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
+ . You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
+ adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
small files rather than writing new small ones thus maintaining the health of your cluster.</p>
-<p>There are a few options when choosing this approach.
-#### Option 1
-Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
-parquet file
-format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.
-#### Option 2
-For huge datasets, this could be as simple as : for partition in [list of partitions in source dataset] {
+<p>There are a few options when choosing this approach.</p>
+
+<h4 id="option-1">Option 1</h4>
+<p>Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
+parquet file
+format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.</p>
+
+<h4 id="option-2">Option 2</h4>
+<p>For huge datasets, this could be as simple as : for partition in [list of partitions in source dataset] {
val inputDF = spark.read.format(“any_input_format”).load(“partition_path”)
inputDF.write.format(“com.uber.hoodie”).option()….save(“basePath”)
- } <br />
-#### Option 3
-Write your own custom logic of how to load an existing dataset into a Hudi managed one. Please read about the RDD API
- <a href="/quickstart.html">here</a>.</p>
+ }</p>
+
+<h4 id="option-3">Option 3</h4>
+<p>Write your own custom logic of how to load an existing dataset into a Hudi managed one. Please read about the RDD API
+ <a href="quickstart.html">here</a>.</p>
-<div class="highlighter-rouge"><pre class="highlight"><code>Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
+<div class="highlighter-rouge"><pre class="highlight"><code>Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
-hoodie->hdfsparquetimport
- --upsert false
- --srcPath /user/parquet/dataset/basepath
- --targetPath
- /user/hoodie/dataset/basepath
- --tableName hoodie_table
- --tableType COPY_ON_WRITE
- --rowKeyField _row_key
- --partitionPathField partitionStr
- --parallelism 1500
- --schemaFilePath /user/table/schema
- --format parquet
- --sparkMemory 6g
+hoodie->hdfsparquetimport
+ --upsert false
+ --srcPath /user/parquet/dataset/basepath
+ --targetPath
+ /user/hoodie/dataset/basepath
+ --tableName hoodie_table
+ --tableType COPY_ON_WRITE
+ --rowKeyField _row_key
+ --partitionPathField partitionStr
+ --parallelism 1500
+ --schemaFilePath /user/table/schema
+ --format parquet
+ --sparkMemory 6g
--retry 2
</code></pre>
</div>
@@ -445,9 +419,19 @@ hoodie->hdfsparquetimport
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/news.html b/content/news.html
index b124601..645bae0 100644
--- a/content/news.html
+++ b/content/news.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -244,6 +245,20 @@
+ <h2><a class="post-link" href="strata-talk.html">Hudi entered Apache Incubator</a></h2>
+ <span class="post-meta">Jan 18, 2019 /
+
+
+ <a href="tag_news.html">news</a>
+
+ </span>
+ <p> In the coming weeks, we will be moving in our new home on the Apache Incubator.
+
+ </p>
+
+
+
+
<h2><a class="post-link" href="strata-talk.html">Connect with us at Strata San Jose March 2017</a></h2>
<span class="post-meta">Dec 30, 2016 /
@@ -280,9 +295,19 @@ Catch our talk “Incremental Processing on Hadoop At Uber”
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/news_archive.html b/content/news_archive.html
index fd98f67..4d80715 100644
--- a/content/news_archive.html
+++ b/content/news_archive.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -351,6 +352,17 @@
<ul class="this">
+ <li><time>18 Jan</time><a href="strata-talk.html">Hudi entered Apache Incubator</a></li>
+
+
+
+
+
+ </ul>
+ <h3>2016</h3>
+ <ul class="past">
+
+
<li><time>30 Dec</time><a href="strata-talk.html">Connect with us at Strata San Jose March 2017</a></li>
</ul>
@@ -379,9 +391,19 @@
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/powered_by.html b/content/powered_by.html
index 2bced47..8f4b0d4 100644
--- a/content/powered_by.html
+++ b/content/powered_by.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -396,9 +397,19 @@ October 2018, Spark+AI Summit Europe, London, UK</p>
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/code_and_design.html b/content/privacy.html
similarity index 74%
rename from content/code_and_design.html
rename to content/privacy.html
index 90372b2..704bd3d 100644
--- a/content/code_and_design.html
+++ b/content/privacy.html
@@ -4,8 +4,8 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" usecases">
-<title>Code Structure | Hudi</title>
+<meta name="keywords" content=" privacy">
+<title>Privacy Policy | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li class="dropdownActive"><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -157,7 +158,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Code Structure page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Privacy Policy page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -175,7 +176,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="Code Structure">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="Privacy Policy">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -326,7 +327,7 @@
<!-- Content Column -->
<div class="col-md-9">
<div class="post-header">
- <h1 class="post-title-main">Code Structure</h1>
+ <h1 class="post-title-main">Privacy Policy</h1>
</div>
@@ -363,71 +364,24 @@ $('#toc').on('click', 'a', function() {
- <h2 id="code--project-structure">Code & Project Structure</h2>
+ <p>Information about your use of this website is collected using server access logs and a tracking cookie.
+The collected information consists of the following:</p>
<ul>
- <li>hoodie-client : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table</li>
- <li>hoodie-common : Common code shared between different artifacts of Hoodie</li>
+ <li>The IP address from which you access the website;</li>
+ <li>The type of browser and operating system you use to access our site;</li>
+ <li>The date and time you access our site;</li>
+ <li>The pages you visit;</li>
+ <li>The addresses of pages from where you followed a link to our site.</li>
</ul>
-<p>## HoodieLogFormat</p>
-
-<p>The following diagram depicts the LogFormat for Hoodie MergeOnRead. Each logfile consists of one or more log blocks.
- Each logblock follows the format shown below.</p>
-
-<table>
- <thead>
- <tr>
- <th>Field</th>
- <th>Description</th>
- </tr>
- </thead>
- <tbody>
- <tr>
- <td>MAGIC</td>
- <td>A magic header that marks the start of a block</td>
- </tr>
- <tr>
- <td>VERSION</td>
- <td>The version of the LogFormat, this helps define how to switch between different log format as it evolves</td>
- </tr>
- <tr>
- <td>TYPE</td>
- <td>The type of the log block</td>
- </tr>
- <tr>
- <td>HEADER LENGTH</td>
- <td>The length of the headers, 0 if no headers</td>
- </tr>
- <tr>
- <td>HEADER</td>
- <td>Metadata needed for a log block. For eg. INSTANT_TIME, TARGET_INSTANT_TIME, SCHEMA etc.</td>
- </tr>
- <tr>
- <td>CONTENT LENGTH</td>
- <td>The length of the content of the log block</td>
- </tr>
- <tr>
- <td>CONTENT</td>
- <td>The content of the log block, for example, for a DATA_BLOCK, the content is (number of records + actual records) in byte []</td>
- </tr>
- <tr>
- <td>FOOTER LENGTH</td>
- <td>The length of the footers, 0 if no footers</td>
- </tr>
- <tr>
- <td>FOOTER</td>
- <td>Metadata needed for a log block. For eg. index entries, a bloom filter for records in a DATA_BLOCK etc.</td>
- </tr>
- <tr>
- <td>LOGBLOCK LENGTH</td>
- <td>The total number of bytes written for a log block, typically the SUM(everything_above). This is a LONG. This acts as a reverse pointer to be able to traverse the log in reverse.</td>
- </tr>
- </tbody>
-</table>
-
-<figure><img class="docimage" src="images/hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" /></figure>
+<p>Part of this information is gathered using a tracking cookie set by the <a href="http://www.google.com/analytics">Google Analytics</a> service and handled by Google as described in their <a href="http://www.google.com/privacy.html">privacy policy</a>. See your browser documentation for instructions on how to disable the cookie if you prefer not to share this data with Google.</p>
+<p>We use the gathered information to help us make our site more useful to visitors and to better understand how and when our site is used. We do not track or collect personally identifiable information or associate gathered data with any personally identifying information from other sources.</p>
+
+<p>By using this website, you consent to the collection of this data in the manner and for the purpose described above.</p>
+
+<p>The Hudi development community welcomes your questions or comments regarding this Privacy Policy. Send them to dev@hudi.apache.org</p>
<div class="tags">
@@ -443,9 +397,19 @@ $('#toc').on('click', 'a', function() {
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/quickstart.html b/content/quickstart.html
index fcd4524..a73534d 100644
--- a/content/quickstart.html
+++ b/content/quickstart.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -344,44 +345,66 @@
<p>Check out code and pull it into Intellij as a normal maven project.</p>
-<p>Normally build the maven project, from command line
-```
-$ mvn clean install -DskipTests -DskipITs</p>
-
-<p>To work with older version of Hive (pre Hive-1.2.1), use</p>
-
-<p>$ mvn clean install -DskipTests -DskipITs -Dhive11</p>
-
-<div class="highlighter-rouge"><pre class="highlight"><code>
-<div markdown="span" class="bs-callout bs-callout-info">You might want to add your spark jars folder to project dependencies under 'Module Setttings', to be able to run Spark from IDE</div>
-
-
-<div markdown="span" class="alert alert-info" role="alert"><i class="fa fa-info-circle"></i> <b>Note:</b> Setup your local hadoop/hive test environment, so you can play with entire ecosystem. See [this](http://www.bytearray.io/2016/05/setting-up-hadoopyarnsparkhive-on-mac.html) for reference</div>
-
-
-
-## Version Compatibility
-
-Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We have verified that Hudi works with the following combination of Hadoop/Hive/Spark.
-
-| Hadoop | Hive | Spark | Instructions to Build Hudi |
-| ---- | ----- | ---- | ---- |
-| 2.6.0-cdh5.7.2 | 1.1.0-cdh5.7.2 | spark-2.[1-3].x | Use “mvn clean install -DskipTests -Dhadoop.version=2.6.0-cdh5.7.2 -Dhive.version=1.1.0-cdh5.7.2” |
-| Apache hadoop-2.8.4 | Apache hive-2.3.3 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
-| Apache hadoop-2.7.3 | Apache hive-1.2.1 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
-
-If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
-It would be of great help if you can reach out to us with your setup and experience with hoodie.
-
-## Generate a Hudi Dataset
-
-### Requirements & Environment Variable
-
-Please set the following environment variablies according to your setup. We have given an example setup with CDH version
+<p>Normally build the maven project, from command line</p>
+<div class="highlighter-rouge"><pre class="highlight"><code>$ mvn clean install -DskipTests -DskipITs
</code></pre>
</div>
-<p>export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre/
+
+<p>To work with older version of Hive (pre Hive-1.2.1), use
+<code class="highlighter-rouge">
+$ mvn clean install -DskipTests -DskipITs -Dhive11
+</code></p>
+
+<div class="bs-callout bs-callout-info">You might want to add your spark jars folder to project dependencies under ‘Module Setttings’, to be able to run Spark from IDE</div>
+
+<div class="alert alert-info" role="alert"><i class="fa fa-info-circle"></i> <b>Note:</b> Setup your local hadoop/hive test environment, so you can play with entire ecosystem. See <a href="http://www.bytearray.io/2016/05/setting-up-hadoopyarnsparkhive-on-mac.html">this</a> for reference</div>
+
+<h2 id="version-compatibility">Version Compatibility</h2>
+
+<p>Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We have verified that Hudi works with the following combination of Hadoop/Hive/Spark.</p>
+
+<table>
+ <thead>
+ <tr>
+ <th>Hadoop</th>
+ <th>Hive</th>
+ <th>Spark</th>
+ <th>Instructions to Build Hudi</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>2.6.0-cdh5.7.2</td>
+ <td>1.1.0-cdh5.7.2</td>
+ <td>spark-2.[1-3].x</td>
+ <td>Use “mvn clean install -DskipTests -Dhadoop.version=2.6.0-cdh5.7.2 -Dhive.version=1.1.0-cdh5.7.2”</td>
+ </tr>
+ <tr>
+ <td>Apache hadoop-2.8.4</td>
+ <td>Apache hive-2.3.3</td>
+ <td>spark-2.[1-3].x</td>
+ <td>Use “mvn clean install -DskipTests”</td>
+ </tr>
+ <tr>
+ <td>Apache hadoop-2.7.3</td>
+ <td>Apache hive-1.2.1</td>
+ <td>spark-2.[1-3].x</td>
+ <td>Use “mvn clean install -DskipTests”</td>
+ </tr>
+ </tbody>
+</table>
+
+<p>If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
+It would be of great help if you can reach out to us with your setup and experience with hoodie.</p>
+
+<h2 id="generate-a-hudi-dataset">Generate a Hudi Dataset</h2>
+
+<h3 id="requirements--environment-variable">Requirements & Environment Variable</h3>
+
+<p>Please set the following environment variablies according to your setup. We have given an example setup with CDH version</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>export JAVA_HOME=/usr/lib/jvm/java-8-openjdk-amd64/jre/
export HIVE_HOME=/var/hadoop/setup/apache-hive-1.1.0-cdh5.7.2-bin
export HADOOP_HOME=/var/hadoop/setup/hadoop-2.6.0-cdh5.7.2
export HADOOP_INSTALL=/var/hadoop/setup/hadoop-2.6.0-cdh5.7.2
@@ -390,11 +413,12 @@ export SPARK_HOME=/var/hadoop/setup/spark-2.3.1-bin-hadoop2.7
export SPARK_INSTALL=$SPARK_HOME
export SPARK_CONF_DIR=$SPARK_HOME/conf
export PATH=$JAVA_HOME/bin:$HIVE_HOME/bin:$HADOOP_HOME/bin:$SPARK_INSTALL/bin:$PATH
-```</p>
+</code></pre>
+</div>
<h3 id="supported-apis">Supported API’s</h3>
-<p>Use the DataSource API to quickly start reading or writing Hudi datasets in few lines of code. Ideal for most
+<p>Use the DataSource API to quickly start reading or writing Hudi datasets in few lines of code. Ideal for most
ingestion use-cases.
Use the RDD API to perform more involved actions on a Hudi dataset</p>
@@ -462,11 +486,11 @@ This can be run as frequently as the ingestion pipeline to make sure new partiti
<div class="highlighter-rouge"><pre class="highlight"><code>cd hoodie-hive
./run_sync_tool.sh
--user hive
- --pass hive
- --database default
- --jdbc-url "jdbc:hive2://localhost:10010/"
- --base-path tmp/hoodie/sample-table/
- --table hoodie_test
+ --pass hive
+ --database default
+ --jdbc-url "jdbc:hive2://localhost:10010/"
+ --base-path tmp/hoodie/sample-table/
+ --table hoodie_test
--partitioned-by field1,field2
</code></pre>
@@ -713,8 +737,8 @@ varadarb-C02SG7Q3G8WP:docker varadarb$ docker ps
<p>Stock Tracker data will be used to showcase both different Hudi Views and the effects of Compaction.</p>
-<p>Take a look at the directory <code class="highlighter-rouge">docker/demo/data</code>. There are 2 batches of stock data - each at 1 minute granularity.
-The first batch contains stocker tracker data for some stock symbols during the first hour of trading window
+<p>Take a look at the directory <code class="highlighter-rouge">docker/demo/data</code>. There are 2 batches of stock data - each at 1 minute granularity.
+The first batch contains stocker tracker data for some stock symbols during the first hour of trading window
(9:30 a.m to 10:30 a.m). The second batch contains tracker data for next 30 mins (10:30 - 11 a.m). Hudi will
be used to ingest these batches to a dataset which will contain the latest stock tracker data at hour level granularity.
The batches are windowed intentionally so that the second batch contains updates to some of the rows in the first batch.</p>
@@ -723,7 +747,7 @@ The batches are windowed intentionally so that the second batch contains updates
<p>Upload the first batch to Kafka topic ‘stock ticks’</p>
-<div class="highlighter-rouge"><pre class="highlight"><code>cat docker/demo/data/batch_1.json | kafkacat -b kafkabroker -t stock_ticks -P
+<div class="highlighter-rouge"><pre class="highlight"><code>cat docker/demo/data/batch_1.json | kafkacat -b kafkabroker -t stock_ticks -P
To check if the new topic shows up, use
kafkacat -b kafkabroker -L -J | jq .
@@ -771,7 +795,7 @@ kafkacat -b kafkabroker -L -J | jq .
<p>Hudi comes with a tool named DeltaStreamer. This tool can connect to variety of data sources (including Kafka) to
pull changes and apply to Hudi dataset using upsert/insert primitives. Here, we will use the tool to download
-json data from kafka topic and ingest to both COW and MOR tables we initialized in the previous step. This tool
+json data from kafka topic and ingest to both COW and MOR tables we initialized in the previous step. This tool
automatically initializes the datasets in the file-system if they do not exist yet.</p>
<div class="highlighter-rouge"><pre class="highlight"><code>docker exec -it adhoc-2 /bin/bash
@@ -796,7 +820,7 @@ exit
</code></pre>
</div>
-<p>You can use HDFS web-browser to look at the datasets
+<p>You can use HDFS web-browser to look at the datasets
<code class="highlighter-rouge">http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow</code>.</p>
<p>You can explore the new partition folder created in the dataset along with a “deltacommit”
@@ -839,7 +863,7 @@ provides the ReadOptimized view for the Hudi dataset and the later provides the
<h4 id="step-4-a-run-hive-queries">Step 4 (a): Run Hive Queries</h4>
<p>Run a hive query to find the latest timestamp ingested for stock symbol ‘GOOG’. You will notice that both read-optimized
-(for both COW and MOR dataset)and realtime views (for MOR dataset)give the same value “10:29 a.m” as Hudi create a
+(for both COW and MOR dataset)and realtime views (for MOR dataset)give the same value “10:29 a.m” as Hudi create a
parquet file for the first batch of data.</p>
<div class="highlighter-rouge"><pre class="highlight"><code>docker exec -it adhoc-2 /bin/bash
@@ -892,7 +916,7 @@ Now, run a projection query:
# Merge-On-Read Queries:
==========================
-Lets run similar queries against M-O-R dataset. Lets look at both
+Lets run similar queries against M-O-R dataset. Lets look at both
ReadOptimized and Realtime views supported by M-O-R dataset
# Run against ReadOptimized View. Notice that the latest timestamp is 10:29
@@ -997,7 +1021,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
# Merge-On-Read Queries:
==========================
-Lets run similar queries against M-O-R dataset. Lets look at both
+Lets run similar queries against M-O-R dataset. Lets look at both
ReadOptimized and Realtime views supported by M-O-R dataset
# Run against ReadOptimized View. Notice that the latest timestamp is 10:29
@@ -1044,7 +1068,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
<p>Upload the second batch of data and ingest this batch using delta-streamer. As this batch does not bring in any new
partitions, there is no need to run hive-sync</p>
-<div class="highlighter-rouge"><pre class="highlight"><code>cat docker/demo/data/batch_2.json | kafkacat -b kafkabroker -t stock_ticks -P
+<div class="highlighter-rouge"><pre class="highlight"><code>cat docker/demo/data/batch_2.json | kafkacat -b kafkabroker -t stock_ticks -P
# Within Docker container, run the ingestion command
docker exec -it adhoc-2 /bin/bash
@@ -1061,15 +1085,15 @@ exit
<p>With Copy-On-Write table, the second ingestion by DeltaStreamer resulted in a new version of Parquet file getting created.
See <code class="highlighter-rouge">http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_cow/2018/08/31</code></p>
-<p>With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
+<p>With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
Take a look at the HDFS filesystem to get an idea: <code class="highlighter-rouge">http://namenode:50070/explorer.html#/user/hive/warehouse/stock_ticks_mor/2018/08/31</code></p>
<h4 id="step-6a-run-hive-queries">Step 6(a): Run Hive Queries</h4>
-<p>With Copy-On-Write table, the read-optimized view immediately sees the changes as part of second batch once the batch
+<p>With Copy-On-Write table, the read-optimized view immediately sees the changes as part of second batch once the batch
got committed as each ingestion creates newer versions of parquet files.</p>
-<p>With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
+<p>With Merge-On-Read table, the second ingestion merely appended the batch to an unmerged delta (log) file.
This is the time, when ReadOptimized and Realtime views will provide different results. ReadOptimized view will still
return “10:29 am” as it will only read from the Parquet file. Realtime View will do on-the-fly merge and return
latest committed data which is “10:59 a.m”.</p>
@@ -1099,7 +1123,7 @@ WARNING: Hive-on-MR is deprecated in Hive 2 and may not be available in the futu
As you can notice, the above queries now reflect the changes that came as part of ingesting second batch.
-# Merge On Read Table:
+# Merge On Read Table:
# Read Optimized View
0: jdbc:hive2://hiveserver:10000> select symbol, max(ts) from stock_ticks_mor group by symbol HAVING symbol = 'GOOG';
@@ -1169,7 +1193,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
As you can notice, the above queries now reflect the changes that came as part of ingesting second batch.
-# Merge On Read Table:
+# Merge On Read Table:
# Read Optimized View
scala> spark.sql("select symbol, max(ts) from stock_ticks_mor group by symbol HAVING symbol = 'GOOG'").show(100, false)
@@ -1235,8 +1259,8 @@ To show the effects of incremental-query, let us assume that a reader has alread
ingesting first batch. Now, for the reader to see effect of the second batch, he/she has to keep the start timestamp to
the commit time of the first batch (20180924064621) and run incremental query
-`Hudi incremental mode` provides efficient scanning for incremental queries by filtering out files that do not have any
-candidate rows using hudi-managed metadata.
+`Hudi incremental mode` provides efficient scanning for incremental queries by filtering out files that do not have any
+candidate rows using hudi-managed metadata.
</code></pre>
</div>
@@ -1333,7 +1357,7 @@ hoodie:stock_ticks_mor->compactions show all
___________________________________________________________________
| Compaction Instant Time| State | Total FileIds to be Compacted|
|==================================================================|
-
+
# Schedule a compaction. This will use Spark Launcher to schedule compaction
hoodie:stock_ticks_mor->compaction schedule
....
@@ -1353,7 +1377,7 @@ hoodie:stock_ticks_mor->compactions show all
___________________________________________________________________
| Compaction Instant Time| State | Total FileIds to be Compacted|
|==================================================================|
- | 20180924070031 | REQUESTED| 1 |
+ | 20180924070031 | REQUESTED| 1 |
# Execute the compaction. The compaction instant value passed below must be the one displayed in the above "compactions show all" query
hoodie:stock_ticks_mor->compaction run --compactionInstant 20180924070031 --parallelism 2 --sparkMemory 1G --schemaFilePath /var/demo/config/schema.avsc --retry 1
@@ -1494,8 +1518,8 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
<code class="highlighter-rouge">
$ mvn pre-integration-test -DskipTests
</code>
-The above command builds docker images for all the services with
-current Hudi source installed at /var/hoodie/ws and also brings up the services using a compose file. We
+The above command builds docker images for all the services with
+current Hudi source installed at /var/hoodie/ws and also brings up the services using a compose file. We
currently use Hadoop (v2.8.4), Hive (v2.3.3) and Spark (v2.3.1) in docker images.</p>
<p>To bring down the containers
@@ -1510,9 +1534,9 @@ $ cd hoodie-integ-test
$ mvn docker-compose:up -DdetachedMode=true
</code></p>
-<p>Hudi is a library that is operated in a broader data analytics/ingestion environment
+<p>Hudi is a library that is operated in a broader data analytics/ingestion environment
involving Hadoop, Hive and Spark. Interoperability with all these systems is a key objective for us. We are
-actively adding integration-tests under <strong>hoodie-integ-test/src/test/java</strong> that makes use of this
+actively adding integration-tests under <strong>hoodie-integ-test/src/test/java</strong> that makes use of this
docker environment (See <strong>hoodie-integ-test/src/test/java/com/uber/hoodie/integ/ITTestHoodieSanity.java</strong> )</p>
<h4 id="building-local-docker-containers">Building Local Docker Containers:</h4>
@@ -1528,8 +1552,8 @@ inbuilt jars by mounting local HUDI workspace over the docker location</li>
</ol>
<p>This helps avoid maintaining separate docker images and avoids the costly step of building HUDI docker images locally.
-But if users want to test hudi from locations with lower network bandwidth, they can still build local images
-run the script
+But if users want to test hudi from locations with lower network bandwidth, they can still build local images
+run the script
<code class="highlighter-rouge">docker/build_local_docker_images.sh</code> to build local docker images before running <code class="highlighter-rouge">docker/setup_demo.sh</code></p>
<p>Here are the commands:</p>
@@ -1594,9 +1618,19 @@ run the script
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/roadmap.html b/content/roadmap.html
deleted file mode 100644
index be1affe..0000000
--- a/content/roadmap.html
+++ /dev/null
@@ -1,405 +0,0 @@
-<!DOCTYPE html>
-<head>
- <meta charset="utf-8">
-<meta http-equiv="X-UA-Compatible" content="IE=edge">
-<meta name="viewport" content="width=device-width, initial-scale=1">
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-<meta name="keywords" content=" usecases">
-<title>Roadmap | Hudi</title>
-<link rel="stylesheet" href="css/syntax.css">
-
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-<link rel="stylesheet" type="text/css" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css">
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- <script>
- $(function () {
- $('[data-toggle="tooltip"]').tooltip()
- })
- </script>
-
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-</head>
-<body>
-<!-- Navigation -->
-
-<nav class="navbar navbar-inverse navbar-fixed-top">
- <div class="container topnavlinks">
- <div class="navbar-header">
- <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
- <span class="sr-only">Toggle navigation</span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- <span class="icon-bar"></span>
- </button>
-
- <a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
- <img src="images/hudi_site_logo.png" alt="Hudi logo"/>
- <!--Hudi-->
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- </div>
- <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
- <ul class="nav navbar-nav navbar-right">
- <!-- entries without drop-downs appear here -->
-
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- <li><a href="news">News</a></li>
-
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- <li><a href="community.html">Community</a></li>
-
-
-
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
-
-
-
- <!-- entries with drop-downs appear here -->
- <!-- conditional logic to control which topnav appears for the audience defined in the configuration file.-->
-
-
- <li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
- <ul class="dropdown-menu">
-
-
- <li><a href="dev_setup.html">Setup</a></li>
-
-
-
- <li><a href="api_docs.html">API Docs</a></li>
-
-
-
- <li><a href="code_and_design.html">Code Structure</a></li>
-
-
-
- <li class="dropdownActive"><a href="roadmap.html">Roadmap</a></li>
-
-
- </ul>
- </li>
-
-
-
- <li>
-
-
-
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Roadmap page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
-
-<li>
-
-
- <!--comment out this block if you want to hide search-->
- <li>
- <!--start search-->
- <div id="search-demo-container">
- <input type="text" id="search-input" placeholder="search...">
- <ul id="results-container"></ul>
- </div>
- <script src="js/jekyll-search.js" type="text/javascript"></script>
- <script type="text/javascript">
- SimpleJekyllSearch.init({
- searchInput: document.getElementById('search-input'),
- resultsContainer: document.getElementById('results-container'),
- dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="Roadmap">{title}</a></li>',
- noResultsText: 'No results found.',
- limit: 10,
- fuzzy: true,
- })
- </script>
- <!--end search-->
- </li>
- </ul>
- </div>
- </div>
- <!-- /.container -->
-</nav>
-
-<!-- Page Content -->
-<div class="container">
- <div class="col-lg-12"> </div>
- <!-- Content Row -->
- <div class="row">
- <!-- Sidebar Column -->
- <div class="col-md-3">
-
-
-
-
-
-
-
-
-
-
-<ul id="mysidebar" class="nav">
- <li class="sidebarTitle">Latest Version</li>
-
-
-
- <li>
- <a href="#">Getting Started</a>
- <ul>
-
-
-
- <li><a href="index.html">Overview</a></li>
-
-
-
-
-
-
- <li><a href="quickstart.html">Quickstart</a></li>
-
-
-
-
-
-
- <li><a href="use_cases.html">Use Cases</a></li>
-
-
-
-
-
-
- <li><a href="powered_by.html">Talks & Powered By</a></li>
-
-
-
-
- </ul>
-
-
-
- <li>
- <a href="#">Documentation</a>
- <ul>
-
-
-
- <li><a href="concepts.html">Concepts</a></li>
-
-
-
-
-
-
- <li><a href="implementation.html">Implementation</a></li>
-
-
-
-
-
-
- <li><a href="configurations.html">Configurations</a></li>
-
-
-
-
-
-
- <li><a href="sql_queries.html">SQL Queries</a></li>
-
-
-
-
-
-
- <li><a href="migration_guide.html">Migration Guide</a></li>
-
-
-
-
-
-
- <li><a href="incremental_processing.html">Incremental Processing</a></li>
-
-
-
-
-
-
- <li><a href="admin_guide.html">Admin Guide</a></li>
-
-
-
-
-
-
- <li><a href="comparison.html">Comparison</a></li>
-
-
-
-
- </ul>
-
-
-
- <!-- if you aren't using the accordion, uncomment this block:
- <p class="external">
- <a href="#" id="collapseAll">Collapse All</a> | <a href="#" id="expandAll">Expand All</a>
- </p>
- -->
- </li>
-</ul>
-</div>
-
-<!-- this highlights the active parent class in the navgoco sidebar. this is critical so that the parent expands when you're viewing a page. This must appear below the sidebar code above. Otherwise, if placed inside customscripts.js, the script runs before the sidebar code runs and the class never gets inserted.-->
-<script>$("li.active").parents('li').toggleClass("active");</script>
-
- <!-- Content Column -->
- <div class="col-md-9">
- <div class="post-header">
- <h1 class="post-title-main">Roadmap</h1>
-</div>
-
-
-
-<div class="post-content">
-
-
-
-
-
-<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
-<script>
-$( document ).ready(function() {
- // Handler for .ready() called.
-
-$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
-
-/* this offset helps account for the space taken up by the floating toolbar. */
-$('#toc').on('click', 'a', function() {
- var target = $(this.getAttribute('href'))
- , scroll_target = target.offset().top
-
- $(window).scrollTop(scroll_target - 10);
- return false
-})
-
-});
-</script>
-
-<div id="toc"></div>
-
-
-
-
-
-
- <h2 id="planned-features">Planned Features</h2>
-
-<ul>
- <li>Support for Self Joins - As of now, you cannot incrementally consume the same table more than once, since the InputFormat does not understand the QueryPlan.</li>
- <li>Hudi Spark Datasource - Allows for reading and writing data back using Apache Spark natively (without falling back to InputFormat), which can be more performant</li>
- <li>Hudi Presto Connector - Allows for querying data managed by Hudi using Presto natively, which can again boost <a href="https://prestodb.io/docs/current/release/release-0.138.html">performance</a></li>
-</ul>
-
-
-
- <div class="tags">
-
- </div>
-
-
-
-</div>
-
-<hr class="shaded"/>
-
-<footer>
- <div class="row">
- <div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
- </div>
- </div>
-</footer>
-
-
- </div>
- <!-- /.row -->
-</div>
-<!-- /.container -->
- </div>
-
-</body>
-
-</html>
\ No newline at end of file
diff --git a/content/s3_hoodie.html b/content/s3_hoodie.html
index 7eadb35..217005c 100644
--- a/content/s3_hoodie.html
+++ b/content/s3_hoodie.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -428,9 +429,19 @@ export HOODIE_ENV_fs_DOT_s3n_DOT_impl=org.apache.hadoop.fs.s3a.S3AFileSystem
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/search.json b/content/search.json
index c77ec9b..3f7eb15 100644
--- a/content/search.json
+++ b/content/search.json
@@ -15,28 +15,6 @@
{
-"title": "API Docs",
-"tags": "",
-"keywords": "usecases",
-"url": "api_docs.html",
-"summary": ""
-}
-,
-
-
-
-{
-"title": "Code Structure",
-"tags": "",
-"keywords": "usecases",
-"url": "code_and_design.html",
-"summary": ""
-}
-,
-
-
-
-{
"title": "Community",
"tags": "",
"keywords": "usecases",
@@ -84,7 +62,7 @@
"title": "Developer Setup",
"tags": "",
"keywords": "developer setup",
-"url": "dev_setup.html",
+"url": "contributing.html",
"summary": ""
}
,
@@ -127,22 +105,22 @@
{
-"title": "Apache Hudi Overview",
+"title": "What is Hudi?",
"tags": "getting_started",
"keywords": "homepage",
"url": "index.html",
-"summary": "Hudi lowers data latency across the board, while simultaneously achieving orders of magnitude of efficiency over traditional batch processing."
+"summary": "Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing."
}
,
{
-"title": "",
+"title": "Migration Guide",
"tags": "",
-"keywords": "",
+"keywords": "migration guide",
"url": "migration_guide.html",
-"summary": ""
+"summary": "In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset"
}
,
@@ -193,10 +171,10 @@
{
-"title": "Quickstart",
-"tags": "quickstart",
-"keywords": "quickstart",
-"url": "quickstart.html",
+"title": "Privacy Policy",
+"tags": "",
+"keywords": "privacy",
+"url": "privacy.html",
"summary": ""
}
,
@@ -204,10 +182,10 @@
{
-"title": "Roadmap",
-"tags": "",
-"keywords": "usecases",
-"url": "roadmap.html",
+"title": "Quickstart",
+"tags": "quickstart",
+"keywords": "quickstart",
+"url": "quickstart.html",
"summary": ""
}
,
@@ -265,6 +243,16 @@
{
+"title": "Hudi entered Apache Incubator",
+"tags": "news",
+"keywords": "",
+"url": "/strata-talk.html",
+"summary": ""
+}
+,
+
+
+{
"title": "Connect with us at Strata San Jose March 2017",
"tags": "news",
"keywords": "",
diff --git a/content/sitemap.xml b/content/sitemap.xml
index fdf498e..14f34a7 100644
--- a/content/sitemap.xml
+++ b/content/sitemap.xml
@@ -7,26 +7,20 @@
</url>
-
-
-
-
-
<url>
- <loc>http://0.0.0.0:4000/admin_guide.html</loc>
+ <loc>http://0.0.0.0:4000/strata-talk.html</loc>
</url>
+
+
- <url>
- <loc>http://0.0.0.0:4000/api_docs.html</loc>
- </url>
<url>
- <loc>http://0.0.0.0:4000/code_and_design.html</loc>
+ <loc>http://0.0.0.0:4000/admin_guide.html</loc>
</url>
@@ -56,7 +50,7 @@
<url>
- <loc>http://0.0.0.0:4000/dev_setup.html</loc>
+ <loc>http://0.0.0.0:4000/contributing.html</loc>
</url>
@@ -118,13 +112,13 @@
<url>
- <loc>http://0.0.0.0:4000/quickstart.html</loc>
+ <loc>http://0.0.0.0:4000/privacy.html</loc>
</url>
<url>
- <loc>http://0.0.0.0:4000/roadmap.html</loc>
+ <loc>http://0.0.0.0:4000/quickstart.html</loc>
</url>
diff --git a/content/sql_queries.html b/content/sql_queries.html
index 079ce7f..6936191 100644
--- a/content/sql_queries.html
+++ b/content/sql_queries.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -393,11 +394,7 @@ reading Parquet files, just like queries on non-Hudi tables.</p>
<h2 id="presto">Presto</h2>
-<p>Presto requires a <a href="https://github.com/prestodb/presto/pull/7002">patch</a> (until the PR is merged) and the hoodie-hadoop-mr-bundle jar to be placed
-into <code class="highlighter-rouge"><presto_install>/plugin/hive-hadoop2/</code>.</p>
-
-<div class="bs-callout bs-callout-info">Get involved to improve this integration <a href="https://github.com/uber/hoodie/issues/81">here</a></div>
-
+<p>Presto requires the <code class="highlighter-rouge">hoodie-presto-bundle</code> jar to be placed into <code class="highlighter-rouge"><presto_install>/plugin/hive-hadoop2/</code>, across the installation.</p>
<div class="tags">
@@ -413,9 +410,19 @@ into <code class="highlighter-rouge"><presto_install>/plugin/hive-hadoop2/
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/strata-talk.html b/content/strata-talk.html
index 1af7fa4..13a8375 100644
--- a/content/strata-talk.html
+++ b/content/strata-talk.html
@@ -5,7 +5,7 @@
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
<meta name="keywords" content="news, ">
-<title>Connect with us at Strata San Jose March 2017 | Hudi</title>
+<title>Hudi entered Apache Incubator | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -157,7 +158,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Connect with us at Strata San Jose March 2017 page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Hudi entered Apache Incubator page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -175,7 +176,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="Connect with us at Strata San Jose March 2017">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="Hudi entered Apache Incubator">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -328,8 +329,8 @@
<article class="post" itemscope itemtype="http://schema.org/BlogPosting">
<header class="post-header">
- <h1 class="post-title" itemprop="name headline">Connect with us at Strata San Jose March 2017</h1>
- <p class="post-meta"><time datetime="2016-12-30T00:00:00+00:00" itemprop="datePublished">Dec 30, 2016</time> /
+ <h1 class="post-title" itemprop="name headline">Hudi entered Apache Incubator</h1>
+ <p class="post-meta"><time datetime="2019-01-18T00:00:00+00:00" itemprop="datePublished">Jan 18, 2019</time> /
@@ -347,8 +348,7 @@
- <p>We will be presenting Hoodie & general concepts around how incremental processing works at Uber.
-Catch our talk <strong>“Incremental Processing on Hadoop At Uber”</strong></p>
+ <p>In the coming weeks, we will be moving in our new home on the Apache Incubator.</p>
</div>
@@ -364,9 +364,19 @@ Catch our talk <strong>“Incremental Processing on Hadoop At Uber”</strong></
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/content/use_cases.html b/content/use_cases.html
index 32d840d..6df8c34 100644
--- a/content/use_cases.html
+++ b/content/use_cases.html
@@ -104,7 +104,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="images/hudi_site_logo.png" alt="Hudi logo"/>
<!--Hudi-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
@@ -120,7 +121,7 @@
- <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Code</a></li>
@@ -129,23 +130,23 @@
<li class="dropdown">
- <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developers<b class="caret"></b></a>
<ul class="dropdown-menu">
- <li><a href="dev_setup.html">Setup</a></li>
+ <li><a href="contributing.html">Contributing</a></li>
- <li><a href="api_docs.html">API Docs</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/display/HUDI" target="_blank">Wiki/Designs</a></li>
- <li><a href="code_and_design.html">Code Structure</a></li>
+ <li><a href="https://issues.apache.org/jira/projects/HUDI/summary" target="_blank">Issues</a></li>
- <li><a href="roadmap.html">Roadmap</a></li>
+ <li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
</ul>
@@ -413,9 +414,19 @@ each run into a Hudi dataset, which can then be incrementally tailed (just like
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©2019 . All rights reserved. <br />
- Site last generated: Feb 16, 2019 <br />
- <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
+ <p>
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
+ stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
+ reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
+ </p>
</div>
</div>
</footer>
diff --git a/docs/_includes/footer.html b/docs/_includes/footer.html
index c920c5c..ed02cf6 100755
--- a/docs/_includes/footer.html
+++ b/docs/_includes/footer.html
@@ -9,7 +9,7 @@
<img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
</p>
<p>
- Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the name of <a href="http://incubator.apache.org/">Apache Incubator</a>.
+ Apache Hudi is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the <a href="http://incubator.apache.org/">Apache Incubator</a>.
Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have
stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a
reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.
[incubator-hudi-site] 01/19: Placeholder to enable gitpubsub
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 6f02276d52baa438401c2a168cccb0a5e2d50887
Author: Thomas Weise <th...@apache.org>
AuthorDate: Tue Jan 22 08:57:47 2019 -0800
Placeholder to enable gitpubsub
---
content/index.html | 2 ++
1 file changed, 2 insertions(+)
diff --git a/content/index.html b/content/index.html
new file mode 100644
index 0000000..00bf16e
--- /dev/null
+++ b/content/index.html
@@ -0,0 +1,2 @@
+Coming soon!
+
[incubator-hudi-site] 16/19: Bunch of cleanups based on recent
issues/feedback
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 5507c617b96f6839ba37e20586391bd1e1124a31
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Fri Mar 8 18:12:55 2019 -0800
Bunch of cleanups based on recent issues/feedback
- Deltastreamer/quickstart mistake
- Clarify docker/windows support
- Remove confusing references to HDFS with DFS
- Remove all lingering use of "hoodie"
- Links to picking up newbie tickets
- Instructions on updating docs with code changes
---
docs/_posts/2016-12-30-strata-talk-2017.md | 2 +-
docs/admin_guide.md | 44 ++++++++++-----------
docs/community.md | 2 +-
docs/comparison.md | 8 ++--
docs/concepts.md | 2 +-
docs/configurations.md | 30 +++++++-------
docs/contributing.md | 2 +
docs/gcs_filesystem.md | 2 +-
...ommit_duration.png => hudi_commit_duration.png} | Bin
.../{hoodie_intro_1.png => hudi_intro_1.png} | Bin
...ie_log_format_v2.png => hudi_log_format_v2.png} | Bin
...uery_perf_hive.png => hudi_query_perf_hive.png} | Bin
..._perf_presto.png => hudi_query_perf_presto.png} | Bin
...ry_perf_spark.png => hudi_query_perf_spark.png} | Bin
.../{hoodie_upsert_dag.png => hudi_upsert_dag.png} | Bin
...odie_upsert_perf1.png => hudi_upsert_perf1.png} | Bin
...odie_upsert_perf2.png => hudi_upsert_perf2.png} | Bin
docs/implementation.md | 16 ++++----
docs/incremental_processing.md | 22 +++++------
docs/index.md | 4 +-
docs/migration_guide.md | 9 ++---
docs/quickstart.md | 20 +++++-----
docs/s3_filesystem.md | 2 +-
docs/sql_queries.md | 2 -
docs/use_cases.md | 12 +++---
25 files changed, 89 insertions(+), 90 deletions(-)
diff --git a/docs/_posts/2016-12-30-strata-talk-2017.md b/docs/_posts/2016-12-30-strata-talk-2017.md
index 88b923e..39cfb65 100644
--- a/docs/_posts/2016-12-30-strata-talk-2017.md
+++ b/docs/_posts/2016-12-30-strata-talk-2017.md
@@ -5,7 +5,7 @@ permalink: strata-talk.html
tags: [news]
---
-We will be presenting Hoodie & general concepts around how incremental processing works at Uber.
+We will be presenting Hudi & general concepts around how incremental processing works at Uber.
Catch our talk **"Incremental Processing on Hadoop At Uber"**
{% include links.html %}
diff --git a/docs/admin_guide.md b/docs/admin_guide.md
index 7757d04..58dbd15 100644
--- a/docs/admin_guide.md
+++ b/docs/admin_guide.md
@@ -17,11 +17,11 @@ This section provides a glimpse into each of these, with some general guidance o
## Admin CLI
-Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
-A hoodie dataset resides on HDFS, in a location referred to as the **basePath** and we would need this location in order to connect to a Hoodie dataset.
-Hoodie library effectively manages this HDFS dataset internally, using .hoodie subfolder to track all metadata
+Once hudi has been built, the shell can be fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
+A hudi dataset resides on DFS, in a location referred to as the **basePath** and we would need this location in order to connect to a Hudi dataset.
+Hudi library effectively manages this dataset internally, using .hoodie subfolder to track all metadata
-To initialize a hoodie table, use the following command.
+To initialize a hudi table, use the following command.
```
18/09/06 15:56:52 INFO annotation.AutowiredAnnotationBeanPostProcessor: JSR-330 'javax.inject.Inject' annotation found and supported for autowiring
@@ -42,7 +42,7 @@ hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1 --t
18/09/06 15:57:15 INFO table.HoodieTableMetaClient: Finished Loading Table of type COPY_ON_WRITE from ...
```
-To see the description of hoodie table, use the command:
+To see the description of hudi table, use the command:
```
@@ -60,7 +60,7 @@ hoodie:hoodie_table_1->desc
```
-Following is a sample command to connect to a Hoodie dataset contains uber trips.
+Following is a sample command to connect to a Hudi dataset contains uber trips.
```
hoodie:trips->connect --path /app/uber/trips
@@ -111,7 +111,7 @@ hoodie:trips->
#### Inspecting Commits
-The task of upserting or inserting a batch of incoming records is known as a **commit** in Hoodie. A commit provides basic atomicity guarantees such that only commited data is available for querying.
+The task of upserting or inserting a batch of incoming records is known as a **commit** in Hudi. A commit provides basic atomicity guarantees such that only commited data is available for querying.
Each commit has a monotonically increasing string/number called the **commit number**. Typically, this is the time at which we started the commit.
To view some basic information about the last 10 commits,
@@ -129,7 +129,7 @@ hoodie:trips->
```
-At the start of each write, Hoodie also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight
+At the start of each write, Hudi also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight
```
@@ -193,7 +193,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
#### Statistics
-Since Hoodie directly manages file sizes for HDFS dataset, it might be good to get an overall picture
+Since Hudi directly manages file sizes for DFS dataset, it might be good to get an overall picture
```
@@ -206,7 +206,7 @@ hoodie:trips->stats filesizes --partitionPath 2016/09/01 --sortBy "95th" --desc
....
```
-In case of Hoodie write taking much longer, it might be good to see the write amplification for any sudden increases
+In case of Hudi write taking much longer, it might be good to see the write amplification for any sudden increases
```
@@ -221,7 +221,7 @@ hoodie:trips->stats wa
#### Archived Commits
-In order to limit the amount of growth of .commit files on HDFS, Hoodie archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
+In order to limit the amount of growth of .commit files on DFS, Hudi archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
This is a sequence file that contains a mapping from commitNumber => json with raw information about the commit (same that is nicely rolled up above).
@@ -369,7 +369,7 @@ No File renames needed to unschedule pending compaction. Operation successful.
##### Repair Compaction
-The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
+The above compaction unscheduling operations could sometimes fail partially (e:g -> DFS temporarily unavailable). With
partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
`compaction validate`, you can notice invalid compaction operations if there is one. In these cases, the repair
command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
@@ -387,7 +387,7 @@ Compaction successfully repaired
## Metrics
-Once the Hoodie Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hoodie datasets
+Once the Hudi Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hudi datasets
- **Commit Duration** - This is amount of time it took to successfully commit a batch of records
- **Rollback Duration** - Similarly, amount of time taken to undo partial data left over by a failed commit (happens everytime automatically after a failing write)
@@ -397,29 +397,29 @@ Once the Hoodie Client is configured with the right datasetname and environment
These metrics can then be plotted on a standard tool like grafana. Below is a sample commit duration chart.
-{% include image.html file="hoodie_commit_duration.png" alt="hoodie_commit_duration.png" max-width="1000" %}
+{% include image.html file="hudi_commit_duration.png" alt="hudi_commit_duration.png" max-width="1000" %}
## Troubleshooting Failures
-Section below generally aids in debugging Hoodie failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)
+Section below generally aids in debugging Hudi failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)
- - **_hoodie_record_key** - Treated as a primary key within each HDFS partition, basis of all updates/inserts
+ - **_hoodie_record_key** - Treated as a primary key within each DFS partition, basis of all updates/inserts
- **_hoodie_commit_time** - Last commit that touched this record
- **_hoodie_file_name** - Actual file name containing the record (super useful to triage duplicates)
- **_hoodie_partition_path** - Path from basePath that identifies the partition containing this record
-{% include callout.html content="Note that as of now, Hoodie assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition" type="warning" %}
+{% include callout.html content="Note that as of now, Hudi assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition" type="warning" %}
#### Missing records
Please check if there were any write errors using the admin commands above, during the window at which the record could have been written.
-If you do find errors, then the record was not actually written by Hoodie, but handed back to the application to decide what to do with it.
+If you do find errors, then the record was not actually written by Hudi, but handed back to the application to decide what to do with it.
#### Duplicates
-First of all, please confirm if you do indeed have duplicates **AFTER** ensuring the query is accessing the Hoodie datasets [properly](sql_queries.html) .
+First of all, please confirm if you do indeed have duplicates **AFTER** ensuring the query is accessing the Hudi datasets [properly](sql_queries.html) .
- If confirmed, please use the metadata fields above, to identify the physical files & partition files containing the records .
- If duplicates span files across partitionpath, then this means your application is generating different partitionPaths for same recordKey, Please fix your app
@@ -427,11 +427,11 @@ First of all, please confirm if you do indeed have duplicates **AFTER** ensuring
#### Spark failures
-Typical upsert() DAG looks like below. Note that Hoodie client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
+Typical upsert() DAG looks like below. Note that Hudi client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
Also Spark UI shows sortByKey twice due to the probe job also being shown, nonetheless its just a single sort.
-{% include image.html file="hoodie_upsert_dag.png" alt="hoodie_upsert_dag.png" max-width="1000" %}
+{% include image.html file="hudi_upsert_dag.png" alt="hudi_upsert_dag.png" max-width="1000" %}
At a high level, there are two steps
@@ -448,5 +448,5 @@ At a high level, there are two steps
- Job 6 : Lazy join of incoming records against recordKey, location to provide a final set of HoodieRecord which now contain the information about which file/partitionpath they are found at (or null if insert). Then also profile the workload again to determine sizing of files
- Job 7 : Actual writing of data (update + insert + insert turned to updates to maintain file size)
-Depending on the exception source (Hoodie/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/HDFS temporary failures.
+Depending on the exception source (Hudi/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/DFS temporary failures.
In the future, a more sophisticated debug/management UI would be added to the project, that can help automate some of this debugging.
diff --git a/docs/community.md b/docs/community.md
index 5708f3d..dd6d8ea 100644
--- a/docs/community.md
+++ b/docs/community.md
@@ -33,7 +33,7 @@ Here are few ways, you can get involved.
- Author blogs on our wiki
- Testing; Improving out-of-box experience by reporting bugs
- Share new ideas/directions to pursue or propose a new HIP
- - Contributing code to the project
+ - Contributing code to the project ([newbie JIRAs](https://issues.apache.org/jira/issues/?jql=project+%3D+HUDI+AND+component+%3D+newbie))
#### Code Contributions
diff --git a/docs/comparison.md b/docs/comparison.md
index 0862c26..a606c94 100644
--- a/docs/comparison.md
+++ b/docs/comparison.md
@@ -6,7 +6,7 @@ permalink: comparison.html
toc: false
---
-Apache Hudi fills a big void for processing data on top of HDFS, and thus mostly co-exists nicely with these technologies. However,
+Apache Hudi fills a big void for processing data on top of DFS, and thus mostly co-exists nicely with these technologies. However,
it would be useful to understand how Hudi fits into the current big data ecosystem, contrasting it with a few related systems
and bring out the different tradeoffs these systems have accepted in their design.
@@ -47,12 +47,12 @@ just for analytics. Finally, HBase does not support incremental processing primi
A popular question, we get is : "How does Hudi relate to stream processing systems?", which we will try to answer here. Simply put, Hudi can integrate with
batch (`copy-on-write storage`) and streaming (`merge-on-read storage`) jobs of today, to store the computed results in Hadoop. For Spark apps, this can happen via direct
integration of Hudi library with Spark/Spark streaming DAGs. In case of Non-Spark processing systems (eg: Flink, Hive), the processing can be done in the respective systems
-and later sent into a Hudi table via a Kafka topic/HDFS intermediate file. In more conceptual level, data processing
+and later sent into a Hudi table via a Kafka topic/DFS intermediate file. In more conceptual level, data processing
pipelines just consist of three components : `source`, `processing`, `sink`, with users ultimately running queries against the sink to use the results of the pipeline.
-Hudi can act as either a source or sink, that stores data on HDFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
+Hudi can act as either a source or sink, that stores data on DFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
of Presto/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop), which effectively
uses Hudi even inside the `processing` engine to speed up typical batch pipelines. For e.g: Hudi can be used as a state store inside a processing DAG (similar
to how [rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend) is used by Flink). This is an item on the roadmap
-and will eventually happen as a [Beam Runner](https://github.com/uber/hoodie/issues/8)
+and will eventually happen as a [Beam Runner](https://issues.apache.org/jira/browse/HUDI-60)
diff --git a/docs/concepts.md b/docs/concepts.md
index 7532631..a2f4322 100644
--- a/docs/concepts.md
+++ b/docs/concepts.md
@@ -7,7 +7,7 @@ toc: false
summary: "Here we introduce some basic concepts & give a broad technical overview of Hudi"
---
-Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on HDFS
+Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on DFS
* Upsert (how do I change the dataset?)
* Incremental consumption (how do I fetch data that changed?)
diff --git a/docs/configurations.md b/docs/configurations.md
index 3a9b88e..dd2fa8a 100644
--- a/docs/configurations.md
+++ b/docs/configurations.md
@@ -22,9 +22,9 @@ Immaterial of whether RDD/WriteClient APIs or Datasource is used, the following
to cloud stores.
* [AWS S3](s3_hoodie.html) <br/>
- Configurations required for S3 and Hoodie co-operability.
+ Configurations required for S3 and Hudi co-operability.
* [Google Cloud Storage](gcs_hoodie.html) <br/>
- Configurations required for GCS and Hoodie co-operability.
+ Configurations required for GCS and Hudi co-operability.
### Spark Datasource Configs {#spark-datasource}
@@ -155,10 +155,10 @@ Following subsections go over different aspects of write configs, explaining mos
- [withPath](#withPath) (hoodie_base_path)
Property: `hoodie.base.path` [Required] <br/>
-<span style="color:grey">Base HDFS path under which all the data partitions are created. Always prefix it explicitly with the storage scheme (e.g hdfs://, s3:// etc). Hudi stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span>
+<span style="color:grey">Base DFS path under which all the data partitions are created. Always prefix it explicitly with the storage scheme (e.g hdfs://, s3:// etc). Hudi stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span>
- [withSchema](#withSchema) (schema_str) <br/>
Property: `hoodie.avro.schema` [Required]<br/>
-<span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span>
+<span style="color:grey">This is the current reader avro schema for the dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span>
- [forTable](#forTable) (table_name)<br/>
Property: `hoodie.table.name` [Required] <br/>
<span style="color:grey">Table name for the dataset, will be used for registering with Hive. Needs to be same across runs.</span>
@@ -170,7 +170,7 @@ Property: `hoodie.insert.shuffle.parallelism`, `hoodie.upsert.shuffle.parallelis
<span style="color:grey">Once data has been initially imported, this parallelism controls initial parallelism for reading input records. Ensure this value is high enough say: 1 partition for 1 GB of input data</span>
- [combineInput](#combineInput) (on_insert = false, on_update=true)<br/>
Property: `hoodie.combine.before.insert`, `hoodie.combine.before.upsert`<br/>
-<span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span>
+<span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in DFS</span>
- [withWriteStatusStorageLevel](#withWriteStatusStorageLevel) (level = MEMORY_AND_DISK_SER)<br/>
Property: `hoodie.write.status.storage.level`<br/>
<span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span>
@@ -215,7 +215,7 @@ Following configs control indexing behavior, which tags incoming records as eith
<span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span>
- [hbaseTableName](#hbaseTableName) (tableName) [Required]<br/>
Property: `hoodie.index.hbase.table` <br/>
- <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span>
+ <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hudi stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span>
#### Storage configs
Controls aspects around sizing parquet and log files.
@@ -223,7 +223,7 @@ Controls aspects around sizing parquet and log files.
- [withStorageConfig](#withStorageConfig) (HoodieStorageConfig) <br/>
- [limitFileSize](#limitFileSize) (size = 120MB) <br/>
Property: `hoodie.parquet.max.file.size` <br/>
- <span style="color:grey">Target size for parquet files produced by Hudi write phases. For HDFS, this needs to be aligned with the underlying filesystem block size for optimal performance. </span>
+ <span style="color:grey">Target size for parquet files produced by Hudi write phases. For DFS, this needs to be aligned with the underlying filesystem block size for optimal performance. </span>
- [parquetBlockSize](#parquetBlockSize) (rowgroupsize = 120MB) <br/>
Property: `hoodie.parquet.block.size` <br/>
<span style="color:grey">Parquet RowGroup size. Its better this is same as the file size, so that a single column within a file is stored continuously on disk</span>
@@ -249,13 +249,13 @@ Configs that control compaction (merging of log files onto a new parquet base fi
- [withCompactionConfig](#withCompactionConfig) (HoodieCompactionConfig) <br/>
- [withCleanerPolicy](#withCleanerPolicy) (policy = KEEP_LATEST_COMMITS) <br/>
Property: `hoodie.cleaner.policy` <br/>
- <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span>
+ <span style="color:grey"> Cleaning policy to be used. Hudi will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span>
- [retainCommits](#retainCommits) (no_of_commits_to_retain = 24) <br/>
Property: `hoodie.cleaner.commits.retained` <br/>
<span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span>
- [archiveCommitsWith](#archiveCommitsWith) (minCommits = 96, maxCommits = 128) <br/>
Property: `hoodie.keep.min.commits`, `hoodie.keep.max.commits` <br/>
- <span style="color:grey">Each commit is a small file in the `.hoodie` directory. Since HDFS is not designed to handle multiple small files, Hudi archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span>
+ <span style="color:grey">Each commit is a small file in the `.hoodie` directory. Since DFS typically does not favor lots of small files, Hudi archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span>
- [compactionSmallFileSize](#compactionSmallFileSize) (size = 0) <br/>
Property: `hoodie.parquet.small.file.limit` <br/>
<span style="color:grey">This should be less < maxFileSize and setting it to 0, turns off this feature. Small files can always happen because of the number of insert records in a partition in a batch. Hudi has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a "small file size".</span>
@@ -264,10 +264,10 @@ Configs that control compaction (merging of log files onto a new parquet base fi
<span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span>
- [autoTuneInsertSplits](#autoTuneInsertSplits) (true) <br/>
Property: `hoodie.copyonwrite.insert.auto.split` <br/>
- <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit's metadata. Turned off by default. </span>
+ <span style="color:grey">Should hudi dynamically compute the insertSplitSize based on the last 24 commit's metadata. Turned off by default. </span>
- [approxRecordSize](#approxRecordSize) () <br/>
Property: `hoodie.copyonwrite.record.size.estimate` <br/>
- <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit's metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span>
+ <span style="color:grey">The average record size. If specified, hudi will use this and not compute dynamically based on the last 24 commit's metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span>
- [withInlineCompaction](#withInlineCompaction) (inlineCompaction = false) <br/>
Property: `hoodie.compact.inline` <br/>
<span style="color:grey">When set to true, compaction is triggered by the ingestion itself, right after a commit/deltacommit action as part of insert/upsert/bulk_insert</span>
@@ -301,7 +301,7 @@ Configs that control compaction (merging of log files onto a new parquet base fi
Enables reporting of Hudi metrics to graphite.
- [withMetricsConfig](#withMetricsConfig) (HoodieMetricsConfig) <br/>
-<span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
+<span style="color:grey">Hudi publishes metrics on every commit, clean, rollback etc.</span>
- [on](#on) (metricsOn = true) <br/>
Property: `hoodie.metrics.on` <br/>
<span style="color:grey">Turn sending metrics on/off. on by default.</span>
@@ -335,11 +335,11 @@ Controls memory usage for compaction and merges, performed internally by Hudi
Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
-**Input Parallelism** : By default, Hoodie tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
+**Input Parallelism** : By default, Hudi tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
-**Off-heap memory** : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
+**Off-heap memory** : Hudi writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
-**Spark Memory** : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
+**Spark Memory** : Typically, hudi needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
**Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
diff --git a/docs/contributing.md b/docs/contributing.md
index 028ab00..cf449f3 100644
--- a/docs/contributing.md
+++ b/docs/contributing.md
@@ -42,6 +42,8 @@ Here's a typical lifecycle of events to contribute to Hudi.
- Add adequate tests for your new functionality
- [Optional] For involved changes, its best to also run the entire integration test suite using `mvn clean install`
- For website changes, please build the site locally & test navigation, formatting & links thoroughly
+ - If your code change changes some aspect of documentation (e.g new config, default value change),
+ please ensure there is a another PR to [update the docs](https://github.com/apache/incubator-hudi/blob/asf-site/docs/README.md) as well.
- Format commit messages and the pull request title like `[HUDI-XXX] Fixes bug in Spark Datasource`,
where you replace HUDI-XXX with the appropriate JIRA issue.
- Push your commit to your own fork/branch & create a pull request (PR) against the Hudi repo.
diff --git a/docs/gcs_filesystem.md b/docs/gcs_filesystem.md
index 26c4401..3919fdf 100644
--- a/docs/gcs_filesystem.md
+++ b/docs/gcs_filesystem.md
@@ -6,7 +6,7 @@ permalink: gcs_hoodie.html
toc: false
summary: In this page, we go over how to configure hudi with Google Cloud Storage.
---
-For Hudi storage on GCS, **regional** buckets provide an HDFS API with strong consistency.
+For Hudi storage on GCS, **regional** buckets provide an DFS API with strong consistency.
## GCS Configs
diff --git a/docs/images/hoodie_commit_duration.png b/docs/images/hudi_commit_duration.png
similarity index 100%
rename from docs/images/hoodie_commit_duration.png
rename to docs/images/hudi_commit_duration.png
diff --git a/docs/images/hoodie_intro_1.png b/docs/images/hudi_intro_1.png
similarity index 100%
rename from docs/images/hoodie_intro_1.png
rename to docs/images/hudi_intro_1.png
diff --git a/docs/images/hoodie_log_format_v2.png b/docs/images/hudi_log_format_v2.png
similarity index 100%
rename from docs/images/hoodie_log_format_v2.png
rename to docs/images/hudi_log_format_v2.png
diff --git a/docs/images/hoodie_query_perf_hive.png b/docs/images/hudi_query_perf_hive.png
similarity index 100%
rename from docs/images/hoodie_query_perf_hive.png
rename to docs/images/hudi_query_perf_hive.png
diff --git a/docs/images/hoodie_query_perf_presto.png b/docs/images/hudi_query_perf_presto.png
similarity index 100%
rename from docs/images/hoodie_query_perf_presto.png
rename to docs/images/hudi_query_perf_presto.png
diff --git a/docs/images/hoodie_query_perf_spark.png b/docs/images/hudi_query_perf_spark.png
similarity index 100%
rename from docs/images/hoodie_query_perf_spark.png
rename to docs/images/hudi_query_perf_spark.png
diff --git a/docs/images/hoodie_upsert_dag.png b/docs/images/hudi_upsert_dag.png
similarity index 100%
rename from docs/images/hoodie_upsert_dag.png
rename to docs/images/hudi_upsert_dag.png
diff --git a/docs/images/hoodie_upsert_perf1.png b/docs/images/hudi_upsert_perf1.png
similarity index 100%
rename from docs/images/hoodie_upsert_perf1.png
rename to docs/images/hudi_upsert_perf1.png
diff --git a/docs/images/hoodie_upsert_perf2.png b/docs/images/hudi_upsert_perf2.png
similarity index 100%
rename from docs/images/hoodie_upsert_perf2.png
rename to docs/images/hudi_upsert_perf2.png
diff --git a/docs/implementation.md b/docs/implementation.md
index cbf394e..54966e2 100644
--- a/docs/implementation.md
+++ b/docs/implementation.md
@@ -10,7 +10,7 @@ Hudi (pronounced “Hoodie”) is implemented as a Spark library, which makes it
libraries (which we will refer to as `Hudi clients`). Hudi Clients prepare an `RDD[HoodieRecord]` that contains the data to be upserted and
Hudi upsert/insert is merely a Spark DAG, that can be broken into two big pieces.
- - **Indexing** : A big part of Hoodie's efficiency comes from indexing the mapping from record keys to the file ids, to which they belong to.
+ - **Indexing** : A big part of Hudi's efficiency comes from indexing the mapping from record keys to the file ids, to which they belong to.
This index also helps the `HoodieWriteClient` separate upserted records into inserts and updates, so they can be treated differently.
`HoodieReadClient` supports operations such as `filterExists` (used for de-duplication of table) and an efficient batch `read(keys)` api, that
can read out the records corresponding to the keys using the index much quickly, than a typical scan via a query. The index is also atomically
@@ -66,7 +66,7 @@ In this storage, index updation is a no-op, since the bloom filters are already
In the case of Copy-On-Write, a single parquet file constitutes one `file slice` which contains one complete version of
the file
-{% include image.html file="hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" max-width="1000" %}
+{% include image.html file="hudi_log_format_v2.png" alt="hudi_log_format_v2.png" max-width="1000" %}
#### Merge On Read
@@ -222,7 +222,7 @@ log blocks of 2 delta-commits (DC2 and DC3).
incremental ingestion (writer at DC6) happened before the compaction (some time “Tc”’).
The below description is with regards to compaction from file-group perspective.
* `Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”`:
- Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
+ Hudi’s implementation will be changed to become aware of file-groups currently waiting for compaction and
merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
@@ -247,14 +247,14 @@ the conventional alternatives for achieving these tasks.
Following shows the speed up obtained for NoSQL ingestion, by switching from bulk loads off HBase to Parquet to incrementally upserting
on a Hudi dataset, on 5 tables ranging from small to huge.
-{% include image.html file="hoodie_upsert_perf1.png" alt="hoodie_upsert_perf1.png" max-width="1000" %}
+{% include image.html file="hudi_upsert_perf1.png" alt="hudi_upsert_perf1.png" max-width="1000" %}
Given Hudi can build the dataset incrementally, it opens doors for also scheduling ingesting more frequently thus reducing latency, with
significant savings on the overall compute cost.
-{% include image.html file="hoodie_upsert_perf2.png" alt="hoodie_upsert_perf2.png" max-width="1000" %}
+{% include image.html file="hudi_upsert_perf2.png" alt="hudi_upsert_perf2.png" max-width="1000" %}
Hudi upserts have been stress tested upto 4TB in a single commit across the t1 table.
@@ -267,12 +267,12 @@ with no impact on queries. Following charts compare the Hudi vs non-Hudi dataset
**Hive**
-{% include image.html file="hoodie_query_perf_hive.png" alt="hoodie_query_perf_hive.png" max-width="800" %}
+{% include image.html file="hudi_query_perf_hive.png" alt="hudi_query_perf_hive.png" max-width="800" %}
**Spark**
-{% include image.html file="hoodie_query_perf_spark.png" alt="hoodie_query_perf_spark.png" max-width="1000" %}
+{% include image.html file="hudi_query_perf_spark.png" alt="hudi_query_perf_spark.png" max-width="1000" %}
**Presto**
-{% include image.html file="hoodie_query_perf_presto.png" alt="hoodie_query_perf_presto.png" max-width="1000" %}
+{% include image.html file="hudi_query_perf_presto.png" alt="hudi_query_perf_presto.png" max-width="1000" %}
diff --git a/docs/incremental_processing.md b/docs/incremental_processing.md
index 7c97cc9..63f4f39 100644
--- a/docs/incremental_processing.md
+++ b/docs/incremental_processing.md
@@ -13,7 +13,7 @@ discusses a few tools that can be used to achieve these on different contexts.
## Incremental Ingestion
-Following means can be used to apply a delta or an incremental change to a Hudi dataset. For e.g, the incremental changes could be from a Kafka topic or files uploaded to HDFS or
+Following means can be used to apply a delta or an incremental change to a Hudi dataset. For e.g, the incremental changes could be from a Kafka topic or files uploaded to DFS or
even changes pulled from another Hudi dataset.
#### DeltaStreamer Tool
@@ -23,9 +23,10 @@ from different sources such as DFS or Kafka.
The tool is a spark job (part of hoodie-utilities), that provides the following functionality
- - Ability to consume new events from Kafka, incremental imports from Sqoop or output of `HiveIncrementalPuller` or files under a folder on HDFS
+ - Ability to consume new events from Kafka, incremental imports from Sqoop or output of `HiveIncrementalPuller` or files under a folder on DFS
- Support json, avro or a custom payload types for the incoming data
- - New data is written to a Hudi dataset, with support for checkpointing & schemas and registered onto Hive
+ - Pick up avro schemas from DFS or Confluent [schema registry](https://github.com/confluentinc/schema-registry).
+ - New data is written to a Hudi dataset, with support for checkpointing and registered onto Hive
Command line options describe capabilities in more detail (first build hoodie-utilities using `mvn clean package`).
@@ -116,7 +117,7 @@ and then ingest it as follows.
--op BULK_INSERT
```
-In some cases, you may want to convert your existing dataset into Hoodie, before you can begin ingesting new data. This can be accomplished using the `hdfsparquetimport` command on the `hoodie-cli`.
+In some cases, you may want to convert your existing dataset into Hudi, before you can begin ingesting new data. This can be accomplished using the `hdfsparquetimport` command on the `hoodie-cli`.
Currently, there is support for converting parquet datasets.
#### Via Custom Spark Job
@@ -167,9 +168,6 @@ Usage: <main class> [options]
```
-{% include callout.html content="Note that for now, due to jar mismatches between Spark & Hive, its recommended to run this as a separate Java task in your workflow manager/cron. This is getting fix [here](https://github.com/uber/hoodie/issues/123)" type="info" %}
-
-
## Incrementally Pulling
Hudi datasets can be pulled incrementally, which means you can get ALL and ONLY the updated & new rows since a specified commit timestamp.
@@ -196,10 +194,10 @@ A sample incremental pull, that will obtain all records written since `beginInst
Please refer to [configurations](configurations.html) section, to view all datasource options.
-Additionally, `HoodieReadClient` offers the following functionality using Hoodie's implicit indexing.
+Additionally, `HoodieReadClient` offers the following functionality using Hudi's implicit indexing.
| **API** | **Description** |
-| read(keys) | Read out the data corresponding to the keys as a DataFrame, using Hoodie's own index for faster lookup |
+| read(keys) | Read out the data corresponding to the keys as a DataFrame, using Hudi's own index for faster lookup |
| filterExists() | Filter out already existing records from the provided RDD[HoodieRecord]. Useful for de-duplication |
| checkExists(keys) | Check if the provided keys exist in a Hudi dataset |
@@ -217,12 +215,12 @@ The following are the configuration options for HiveIncrementalPuller
|hiveUser| Hive Server 2 Username | |
|hivePass| Hive Server 2 Password | |
|queue| YARN Queue name | |
-|tmp| Directory where the temporary delta data is stored in HDFS. The directory structure will follow conventions. Please see the below section. | |
+|tmp| Directory where the temporary delta data is stored in DFS. The directory structure will follow conventions. Please see the below section. | |
|extractSQLFile| The SQL to execute on the source table to extract the data. The data extracted will be all the rows that changed since a particular point in time. | |
|sourceTable| Source Table Name. Needed to set hive environment properties. | |
|targetTable| Target Table Name. Needed for the intermediate storage directory structure. | |
-|sourceDataPath| Source HDFS Base Path. This is where the Hudi metadata will be read. | |
-|targetDataPath| Target HDFS Base path. This is needed to compute the fromCommitTime. This is not needed if fromCommitTime is specified explicitly. | |
+|sourceDataPath| Source DFS Base Path. This is where the Hudi metadata will be read. | |
+|targetDataPath| Target DFS Base path. This is needed to compute the fromCommitTime. This is not needed if fromCommitTime is specified explicitly. | |
|tmpdb| The database to which the intermediate temp delta table will be created | hoodie_temp |
|fromCommitTime| This is the most important parameter. This is the point in time from which the changed records are pulled from. | |
|maxCommits| Number of commits to include in the pull. Setting this to -1 will include all the commits from fromCommitTime. Setting this to a value > 0, will include records that ONLY changed in the specified number of commits after fromCommitTime. This may be needed if you need to catch up say 2 commits at a time. | 3 |
diff --git a/docs/index.md b/docs/index.md
index 22e1174..0ae003c 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -7,14 +7,14 @@ permalink: index.html
summary: "Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing."
---
-Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud stores and provides three logical views for query access.
+Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets over DFS ([HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud stores) and provides three logical views for query access.
* **Read Optimized View** - Provides excellent query performance on pure columnar storage, much like plain [Parquet](https://parquet.apache.org/) tables.
* **Incremental View** - Provides a change stream out of the dataset to feed downstream jobs/ETLs.
* **Near-Real time Table** - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + [Avro](http://avro.apache.org/docs/current/mr.html))
-{% include image.html file="hoodie_intro_1.png" alt="hoodie_intro_1.png" %}
+{% include image.html file="hudi_intro_1.png" alt="hudi_intro_1.png" %}
By carefully managing how data is laid out in storage & how it’s exposed to queries, Hudi is able to power a rich data ecosystem where external sources can be ingested in near real-time and made available for interactive SQL Engines like [Presto](https://prestodb.io) & [Spark](https://spark.apache.org/sql/), while at the same time capable of being consumed incrementally from processing/ETL frameworks like [Hive](https://hive.apache.org/) & [Spark](https://spark.apache.org/docs/latest/) t [...]
diff --git a/docs/migration_guide.md b/docs/migration_guide.md
index f785251..e415ed3 100644
--- a/docs/migration_guide.md
+++ b/docs/migration_guide.md
@@ -29,7 +29,7 @@ Take this approach if your dataset is an append only type of dataset and you do
Import your existing dataset into a Hudi managed dataset. Since all the data is Hudi managed, none of the limitations
of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
- make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
+ make the update available to queries. Note that not only do you get to use all Hudi primitives on this dataset,
there are other additional advantages of doing this. Hudi automatically manages file sizes of a Hudi managed dataset
. You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
@@ -38,9 +38,8 @@ Import your existing dataset into a Hudi managed dataset. Since all the data is
There are a few options when choosing this approach.
#### Option 1
-Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
-parquet file
-format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.
+Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in parquet file format.
+This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.
#### Option 2
For huge datasets, this could be as simple as : for partition in [list of partitions in source dataset] {
@@ -53,7 +52,7 @@ Write your own custom logic of how to load an existing dataset into a Hudi manag
[here](quickstart.html).
```
-Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
+Using the HDFSParquetImporter Tool. Once hudi has been built via `mvn clean install -DskipTests`, the shell can be
fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
hoodie->hdfsparquetimport
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 5a9193a..e19bedf 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -30,7 +30,8 @@ $ mvn clean install -DskipTests -DskipITs -Dhive11
## Version Compatibility
-Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We have verified that Hudi works with the following combination of Hadoop/Hive/Spark.
+Hudi requires Java 8 to be installed on a *nix system. Hudi works with Spark-2.x versions.
+Further, we have verified that Hudi works with the following combination of Hadoop/Hive/Spark.
| Hadoop | Hive | Spark | Instructions to Build Hudi |
| ---- | ----- | ---- | ---- |
@@ -38,8 +39,9 @@ Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We hav
| Apache hadoop-2.8.4 | Apache hive-2.3.3 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
| Apache hadoop-2.7.3 | Apache hive-1.2.1 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
-If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
-It would be of great help if you can reach out to us with your setup and experience with hoodie.
+If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues.
+We are limited by our bandwidth to certify other combinations (e.g Docker on Windows).
+It would be of great help if you can reach out to us with your setup and experience with hudi.
## Generate a Hudi Dataset
@@ -67,7 +69,7 @@ Use the RDD API to perform more involved actions on a Hudi dataset
#### DataSource API
-Run __hoodie-spark/src/test/java/HoodieJavaApp.java__ class, to place a two commits (commit 1 => 100 inserts, commit 2 => 100 updates to previously inserted 100 records) onto your HDFS/local filesystem. Use the wrapper script
+Run __hoodie-spark/src/test/java/HoodieJavaApp.java__ class, to place a two commits (commit 1 => 100 inserts, commit 2 => 100 updates to previously inserted 100 records) onto your DFS/local filesystem. Use the wrapper script
to run from command-line
```
@@ -330,9 +332,9 @@ The steps assume you are using Mac laptop
### Setting up Docker Cluster
-#### Build Hoodie
+#### Build Hudi
-The first step is to build hoodie
+The first step is to build hudi
```
cd <HUDI_WORKSPACE>
mvn package -DskipTests
@@ -451,7 +453,7 @@ automatically initializes the datasets in the file-system if they do not exist y
docker exec -it adhoc-2 /bin/bash
# Run the following spark-submit command to execute the delta-streamer and ingest to stock_ticks_cow dataset in HDFS
-spark-submit --class com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer $HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts --target-base-path /user/hive/warehouse/stock_ticks_cow --target-table stock_ticks_cow --props /var/demo/config/kafka-source.properties
+spark-submit --class com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer $HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts --target-base-path /user/hive/warehouse/stock_ticks_cow --target-table stock_ticks_cow --props /var/demo/config/kafka-source.properties --schemaprovider-class com.uber.hoodie.utilities.schema.FilebasedSchemaProvider
....
....
2018-09-24 22:20:00 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint:54 - OutputCommitCoordinator stopped!
@@ -981,7 +983,7 @@ Again, You can use Hudi CLI to manually schedule and run compaction
```
docker exec -it adhoc-1 /bin/bash
-^[[Aroot@adhoc-1:/opt# /var/hoodie/ws/hoodie-cli/hoodie-cli.sh
+root@adhoc-1:/opt# /var/hoodie/ws/hoodie-cli/hoodie-cli.sh
============================================
* *
* _ _ _ _ *
@@ -1166,7 +1168,7 @@ This brings the demo to an end.
## Testing Hudi in Local Docker environment
-You can bring up a hadoop docker environment containing Hadoop, Hive and Spark services with support for hoodie.
+You can bring up a hadoop docker environment containing Hadoop, Hive and Spark services with support for hudi.
```
$ mvn pre-integration-test -DskipTests
```
diff --git a/docs/s3_filesystem.md b/docs/s3_filesystem.md
index 6c7b636..de16123 100644
--- a/docs/s3_filesystem.md
+++ b/docs/s3_filesystem.md
@@ -10,7 +10,7 @@ In this page, we explain how to get your Hudi spark job to store into AWS S3.
## AWS configs
-There are two configurations required for Hoodie-S3 compatibility:
+There are two configurations required for Hudi-S3 compatibility:
- Adding AWS Credentials for Hudi
- Adding required Jars to classpath
diff --git a/docs/sql_queries.md b/docs/sql_queries.md
index 4fa795f..4dc7493 100644
--- a/docs/sql_queries.md
+++ b/docs/sql_queries.md
@@ -34,8 +34,6 @@ to using the Hive Serde to read the data (planning/executions is still Spark). T
towards Parquet reading, which we will address in the next method based on path filters.
However benchmarks have not revealed any real performance degradation with Hudi & SparkSQL, compared to native support.
-{% include callout.html content="Get involved to improve this integration [here](https://github.com/uber/hoodie/issues/7) and [here](https://issues.apache.org/jira/browse/SPARK-19351) " type="info" %}
-
Sample command is provided below to spin up Spark Shell
```
diff --git a/docs/use_cases.md b/docs/use_cases.md
index 0040bc1..9846aa0 100644
--- a/docs/use_cases.md
+++ b/docs/use_cases.md
@@ -18,7 +18,7 @@ even though this data is arguably the most valuable for the entire organization.
For RDBMS ingestion, Hudi provides __faster loads via Upserts__, as opposed costly & inefficient bulk loads. For e.g, you can read the MySQL BIN log or [Sqoop Incremental Import](https://sqoop.apache.org/docs/1.4.2/SqoopUserGuide.html#_incremental_imports) and apply them to an
-equivalent Hudi table on HDFS. This would be much faster/efficient than a [bulk merge job](https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457)
+equivalent Hudi table on DFS. This would be much faster/efficient than a [bulk merge job](https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457)
or [complicated handcrafted merge workflows](http://hortonworks.com/blog/four-step-strategy-incremental-updates-hive/)
@@ -39,14 +39,14 @@ But, typically these systems end up getting abused for less interactive queries
On the other hand, interactive SQL solutions on Hadoop such as Presto & SparkSQL excel in __queries that finish within few seconds__.
-By bringing __data freshness to a few minutes__, Hudi can provide a much efficient alternative, as well unlock real-time analytics on __several magnitudes larger datasets__ stored in HDFS.
+By bringing __data freshness to a few minutes__, Hudi can provide a much efficient alternative, as well unlock real-time analytics on __several magnitudes larger datasets__ stored in DFS.
Also, Hudi has no external dependencies (like a dedicated HBase cluster, purely used for real-time analytics) and thus enables faster analytics on much fresher analytics, without increasing the operational overhead.
## Incremental Processing Pipelines
One fundamental ability Hadoop provides is to build a chain of datasets derived from each other via DAGs expressed as workflows.
-Workflows often depend on new data being output by multiple upstream workflows and traditionally, availability of new data is indicated by a new HDFS Folder/Hive Partition.
+Workflows often depend on new data being output by multiple upstream workflows and traditionally, availability of new data is indicated by a new DFS Folder/Hive Partition.
Let's take a concrete example to illustrate this. An upstream workflow `U` can create a Hive partition for every hour, with data for that hour (event_time) at the end of each hour (processing_time), providing effective freshness of 1 hour.
Then, a downstream workflow `D`, kicks off immediately after `U` finishes, and does its own processing for the next hour, increasing the effective latency to 2 hours.
@@ -63,14 +63,14 @@ like 15 mins, and providing an end-end latency of 30 mins at `HD`.
{% include callout.html content="To achieve this, Hudi has embraced similar concepts from stream processing frameworks like [Spark Streaming](https://spark.apache.org/docs/latest/streaming-programming-guide.html#join-operations) , Pub/Sub systems like [Kafka](http://kafka.apache.org/documentation/#theconsumer)
or database replication technologies like [Oracle XStream](https://docs.oracle.com/cd/E11882_01/server.112/e16545/xstrm_cncpt.htm#XSTRM187).
-For the more curious, a more detailed explanation of the benefits of Incremetal Processing (compared to Stream Processing & Batch Processing) can be found [here](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop)" type="info" %}
+For the more curious, a more detailed explanation of the benefits of Incremental Processing (compared to Stream Processing & Batch Processing) can be found [here](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop)" type="info" %}
-## Data Dispersal From Hadoop
+## Data Dispersal From DFS
A popular use-case for Hadoop, is to crunch data and then disperse it back to an online serving store, to be used by an application.
For e.g, a Spark Pipeline can [determine hard braking events on Hadoop](https://eng.uber.com/telematics/) and load them into a serving store like ElasticSearch, to be used by the Uber application to increase safe driving. Typical architectures for this employ a `queue` between Hadoop and serving store, to prevent overwhelming the target serving store.
-A popular choice for this queue is Kafka and this model often results in __redundant storage of same data on HDFS (for offline analysis on computed results) and Kafka (for dispersal)__
+A popular choice for this queue is Kafka and this model often results in __redundant storage of same data on DFS (for offline analysis on computed results) and Kafka (for dispersal)__
Once again Hudi can efficiently solve this problem, by having the Spark Pipeline upsert output from
each run into a Hudi dataset, which can then be incrementally tailed (just like a Kafka topic) for new data & written into the serving store.
[incubator-hudi-site] 19/19: Minor edits
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 3a9ffadfe436897a68b83315c162e60e68268773
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Wed Mar 13 15:36:37 2019 -0700
Minor edits
---
docs/community.md | 14 +++++++++++---
docs/quickstart.md | 11 ++++++-----
2 files changed, 17 insertions(+), 8 deletions(-)
diff --git a/docs/community.md b/docs/community.md
index dd6d8ea..fd39c0f 100644
--- a/docs/community.md
+++ b/docs/community.md
@@ -13,9 +13,9 @@ There are several ways to get in touch with the Hudi community.
| When? | Channel to use |
|-------|--------|
| For any general questions, user support, development discussions | Dev Mailing list ([Subscribe](mailto:dev-subscribe@hudi.apache.org), [Unsubscribe](mailto:dev-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?dev@hudi.apache.org)). Empty email works for subscribe/unsubscribe. Please use [gists](https://gist.github.com) to share code/stacktraces on the email. |
-| For reporting bugs or issues or discover known issues | Please use [ASF Hudi JIRA](https://issues.apache.org/jira/projects/HUDI/summary) |
+| For reporting bugs or issues or discover known issues | Please use [ASF Hudi JIRA](https://issues.apache.org/jira/projects/HUDI/summary). See [#here](#accounts) for access |
| For quick pings & 1-1 chats | Join our [slack group](https://join.slack.com/t/apache-hudi/signup) |
-| For proposing large features, changes | Start a Hudi Improvement Process (HIP). Instructions coming soon.|
+| For proposing large features, changes | Start a Hudi Improvement Process (HIP). Instructions coming soon. See [#here](#accounts) for access |
| For stream of commits, pull requests etc | Commits Mailing list ([Subscribe](mailto:commits-subscribe@hudi.apache.org), [Unsubscribe](mailto:commits-unsubscribe@hudi.apache.org), [Archives](https://lists.apache.org/list.html?commits@hudi.apache.org)) |
If you wish to report a security vulnerability, please contact [security@apache.org](mailto:security@apache.org).
@@ -35,7 +35,15 @@ Here are few ways, you can get involved.
- Share new ideas/directions to pursue or propose a new HIP
- Contributing code to the project ([newbie JIRAs](https://issues.apache.org/jira/issues/?jql=project+%3D+HUDI+AND+component+%3D+newbie))
-#### Code Contributions
+### Code Contributions
Useful resources for contributing can be found under the "Developers" top menu.
Specifically, please refer to the detailed [contribution guide](contributing.html).
+
+## Accounts {#accounts}
+
+It's useful to obtain few accounts to be able to effectively contribute to Hudi.
+
+ - Github account is needed to send pull requests to Hudi
+ - Sign-up/in to the Apache [JIRA](https://issues.apache.org/jira). Then please email the dev mailing list with your username, asking to be added as a contributor to the project. This enables you to assign/be-assigned tickets and comment on them.
+ - Sign-up/in to the Apache [cWiki](https://cwiki.apache.org/confluence/signup.action), to be able to contribute to the wiki pages/HIPs.
\ No newline at end of file
diff --git a/docs/quickstart.md b/docs/quickstart.md
index ff33184..317bb17 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -23,8 +23,7 @@ $ mvn clean install -DskipTests -DskipITs -Dhive11
```
{% include callout.html content="You might want to add your spark jars folder to project dependencies under 'Module Setttings', to be able to run Spark from IDE.
-Setup your local hadoop/hive test environment, so you can play with entire ecosystem.
-See [this](http://www.bytearray.io/2016/05/setting-up-hadoopyarnsparkhive-on-mac.html) for reference" type="info" %}
+Setup your local hadoop/hive test environment, so you can play with entire ecosystem." type="info" %}
<br/>Please refer to [migration guide](migration_guide.html), for recommended ways to migrate your existing dataset to Hudi.
@@ -264,7 +263,7 @@ You can also use the sample queries in __hoodie-utilities/src/test/java/HoodieSp
Checkout the 'master' branch on OSS Presto, build it, and place your installation somewhere.
-* Copy the hoodie-hadoop-mr-* jar into $PRESTO_INSTALL/plugin/hive-hadoop2/
+* Copy the hudi/packaging/hoodie-presto-bundle/target/hoodie-presto-bundle-*.jar into $PRESTO_INSTALL/plugin/hive-hadoop2/
* Startup your server and you should be able to query the same Hive table via Presto
```
@@ -923,10 +922,12 @@ No rows affected (0.009 seconds)
0: jdbc:hive2://hiveserver:10000> set hoodie.stock_ticks_cow.consume.max.commits=3;
No rows affected (0.009 seconds)
0: jdbc:hive2://hiveserver:10000> set hoodie.stock_ticks_cow.consume.start.timestamp=20180924064621;
+```
-# With the above setting, file-ids that do not have any updates from the commit 20180924065039 is filtered out without scanning.
-# Here is the incremental query :
+With the above setting, file-ids that do not have any updates from the commit 20180924065039 is filtered out without scanning.
+Here is the incremental query :
+```
0: jdbc:hive2://hiveserver:10000>
0: jdbc:hive2://hiveserver:10000> select `_hoodie_commit_time`, symbol, ts, volume, open, close from stock_ticks_cow where symbol = 'GOOG' and `_hoodie_commit_time` > '20180924064621';
+----------------------+---------+----------------------+---------+------------+-----------+--+
[incubator-hudi-site] 04/19: Update Quickstart with new CDH build
instructions
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 14855d45997b7e28fe700aef442b79a619cf49bd
Author: vinoth chandar <vi...@users.noreply.github.com>
AuthorDate: Tue Feb 12 10:43:39 2019 -0800
Update Quickstart with new CDH build instructions
---
docs/quickstart.md | 4 ++--
1 file changed, 2 insertions(+), 2 deletions(-)
diff --git a/docs/quickstart.md b/docs/quickstart.md
index d7e8dec..f1516ae 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -33,7 +33,7 @@ Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We hav
| Hadoop | Hive | Spark | Instructions to Build Hudi |
| ---- | ----- | ---- | ---- |
-| 2.6.0-cdh5.7.2 | 1.1.0-cdh5.7.2 | spark-2.[1-3].x | Use "mvn clean install -DskipTests -Dhive11". Jars will have ".hive11" as suffix |
+| 2.6.0-cdh5.7.2 | 1.1.0-cdh5.7.2 | spark-2.[1-3].x | Use “mvn clean install -DskipTests -Dhadoop.version=2.6.0-cdh5.7.2 -Dhive.version=1.1.0-cdh5.7.2” |
| Apache hadoop-2.8.4 | Apache hive-2.3.3 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
| Apache hadoop-2.7.3 | Apache hive-1.2.1 | spark-2.[1-3].x | Use "mvn clean install -DskipTests" |
@@ -1244,4 +1244,4 @@ cd docker
[INFO] Finished at: 2018-09-10T17:47:37-07:00
[INFO] Final Memory: 236M/1848M
[INFO] ------------------------------------------------------------------------
-```
\ No newline at end of file
+```
[incubator-hudi-site] 15/19: Restructured configurations page
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 9741172f40a441b255d27fc280ecefc5d7b511ec
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Fri Mar 8 11:21:54 2019 -0800
Restructured configurations page
- Listed actual property names in-place
- Picked up missed properties/fixed defaults
- CSS tweaks
- Minor edits to linked pages
---
.gitignore | 2 +
docs/configurations.md | 474 +++++++++++++++++++++++++++++++---------------
docs/css/customstyles.css | 4 +-
docs/css/theme-blue.css | 2 +-
docs/gcs_filesystem.md | 2 +-
docs/s3_filesystem.md | 2 +-
6 files changed, 328 insertions(+), 158 deletions(-)
diff --git a/.gitignore b/.gitignore
index e43b0f9..5d51d6c 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,3 @@
+.idea/
+*.iml
.DS_Store
diff --git a/docs/configurations.md b/docs/configurations.md
index ce45a3d..3a9b88e 100644
--- a/docs/configurations.md
+++ b/docs/configurations.md
@@ -6,166 +6,334 @@ permalink: configurations.html
toc: false
summary: "Here we list all possible configurations and what they mean"
---
+This page covers the different ways of configuring your job to write/read Hudi datasets.
+At a high level, you can control behaviour at few levels.
+- **[Spark Datasource Configs](#spark-datasource)** : These configs control the Hudi Spark Datasource, providing ability to define keys/partitioning, pick out the write operation, specify how to merge records or choosing view type to read.
+- **[WriteClient Configs](#writeclient-configs)** : Internally, the Hudi datasource uses a RDD based `HoodieWriteClient` api to actually perform writes to storage. These configs provide deep control over lower level aspects like
+ file sizing, compression, parallelism, compaction, write schema, cleaning etc. Although Hudi provides sane defaults, from time-time these configs may need to be tweaked to optimize for specific workloads.
+- **[RecordPayload Config](#PAYLOAD_CLASS_OPT_KEY)** : This is the lowest level of customization offered by Hudi. Record payloads define how to produce new values to upsert based on incoming new record and
+ stored old record. Hudi provides default implementations such as `OverwriteWithLatestAvroPayload` which simply update storage with the latest/last-written record.
+ This can be overridden to a custom class extending `HoodieRecordPayload` class, on both datasource and WriteClient levels.
+
+### Talking to Cloud Storage
-#### Talking to Cloud Storage
+Immaterial of whether RDD/WriteClient APIs or Datasource is used, the following information helps configure access
+to cloud stores.
* [AWS S3](s3_hoodie.html) <br/>
- <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span>
+ Configurations required for S3 and Hoodie co-operability.
* [Google Cloud Storage](gcs_hoodie.html) <br/>
- <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span>
-
-#### Spark Datasource Configs
-
-* [Hoodie Datasource](#datasource) <br/>
-<span style="color:grey">Configs for datasource</span>
- - [write options](#writeoptions) (write.format.option(...)) <br/>
- <span style="color:grey"> Options useful for writing datasets </span>
- - [OPERATION_OPT_KEY](#OPERATION_OPT_KEY) (Default: upsert) <br/>
- <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span>
- - [STORAGE_TYPE_OPT_KEY](#STORAGE_TYPE_OPT_KEY) (Default: COPY_ON_WRITE) <br/>
- <span style="color:grey">The storage type for the underlying data, for this write. This can't change between writes.</span>
- - [TABLE_NAME_OPT_KEY](#TABLE_NAME_OPT_KEY) (Default: None (mandatory)) <br/>
- <span style="color:grey">Hive table name, to register the dataset into.</span>
- - [PRECOMBINE_FIELD_OPT_KEY](#PRECOMBINE_FIELD_OPT_KEY) (Default: ts) <br/>
- <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
- we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span>
- - [PAYLOAD_CLASS_OPT_KEY](#PAYLOAD_CLASS_OPT_KEY) (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br/>
- <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
- This will render any value set for `PRECOMBINE_FIELD_OPT_VAL` in-effective</span>
- - [RECORDKEY_FIELD_OPT_KEY](#RECORDKEY_FIELD_OPT_KEY) (Default: uuid) <br/>
- <span style="color:grey">Record key field. Value to be used as the `recordKey` component of `HoodieKey`. Actual value
- will be obtained by invoking .toString() on the field value. Nested fields can be specified using
- the dot notation eg: `a.b.c`</span>
- - [PARTITIONPATH_FIELD_OPT_KEY](#PARTITIONPATH_FIELD_OPT_KEY) (Default: partitionpath) <br/>
- <span style="color:grey">Partition path field. Value to be used at the `partitionPath` component of `HoodieKey`.
- Actual value ontained by invoking .toString()</span>
- - [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY) (Default: com.uber.hoodie.SimpleKeyGenerator) <br/>
- <span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
- - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: `_`) <br/>
- <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
- This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span>
-
- - [read options](#readoptions) (read.format.option(...)) <br/>
- <span style="color:grey">Options useful for reading datasets</span>
- - [VIEW_TYPE_OPT_KEY](#VIEW_TYPE_OPT_KEY) (Default: = read_optimized) <br/>
- <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
- (or) Read Optimized mode (obtain latest view, based on columnar data)
- (or) Real time mode (obtain latest view, based on row & columnar data)</span>
- - [BEGIN_INSTANTTIME_OPT_KEY](#BEGIN_INSTANTTIME_OPT_KEY) (Default: None (Mandatory in incremental mode)) <br/>
- <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
- necessarily correspond to an instant on the timeline. New data written with an
- `instant_time > BEGIN_INSTANTTIME` are fetched out. For e.g: '20170901080000' will get
- all new data written after Sep 1, 2017 08:00AM.</span>
- - [END_INSTANTTIME_OPT_KEY](#END_INSTANTTIME_OPT_KEY) (Default: latest instant (i.e fetches all new data since begin instant time)) <br/>
- <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
- `instant_time <= END_INSTANTTIME` are fetched out.</span>
-
-#### Write Client Configuration
-
-* [HoodieWriteConfig](#HoodieWriteConfig) <br/>
-<span style="color:grey">Top Level Config which is passed in when HoodieWriteClent is created.</span>
- - [withPath](#withPath) (hoodie_base_path) <br/>
- <span style="color:grey">Base HDFS path under which all the data partitions are created. Hoodie stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span>
- - [withSchema](#withSchema) (schema_str) <br/>
- <span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span>
- - [withParallelism](#withParallelism) (insert_shuffle_parallelism = 200, upsert_shuffle_parallelism = 200) <br/>
- <span style="color:grey">Insert DAG uses the insert_parallelism in every shuffle. Upsert DAG uses the upsert_parallelism in every shuffle. Typical workload is profiled and once a min parallelism is established, trade off between latency and cluster usage optimizations this is tuned and have a conservatively high number to optimize for latency and </span>
- - [combineInput](#combineInput) (on_insert = false, on_update=true) <br/>
- <span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span>
- - [withWriteStatusStorageLevel](#withWriteStatusStorageLevel) (level = MEMORY_AND_DISK_SER) <br/>
- <span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span>
- - [withAutoCommit](#withAutoCommit) (autoCommit = true) <br/>
- <span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a "defined success condition"</span>
- - [withAssumeDatePartitioning](#withAssumeDatePartitioning) (assumeDatePartitioning = false) <br/>
- <span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span>
- - [withConsistencyCheckEnabled](#withConsistencyCheckEnabled) (enabled = false) <br/>
- <span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files' are listable on the underlying filesystem/storage. Set this to true, to workaround S3's eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span>
-
- - [withIndexConfig](#withIndexConfig) (HoodieIndexConfig) <br/>
- <span style="color:grey">Hoodie uses a index to help find the FileID which contains an incoming record key. This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
- - [withIndexType](#withIndexType) (indexType = BLOOM) <br/>
- <span style="color:grey">Type of index to use. Default is Bloom filter. Possible options are [BLOOM | HBASE | INMEMORY]. Bloom filters removes the dependency on a external system and is stored in the footer of the Parquet Data Files</span>
- - [bloomFilterNumEntries](#bloomFilterNumEntries) (60000) <br/>
- <span style="color:grey">Only applies if index type is BLOOM. <br/>This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. [#70](https://github.com/uber/hoodie/issues/70) tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positives and index lo [...]
- - [bloomFilterFPP](#bloomFilterFPP) (0.000000001) <br/>
- <span style="color:grey">Only applies if index type is BLOOM. <br/> Error rate allowed given the number of entries. This is used to calculate how many bits should be assigned for the bloom filter and the number of hash functions. This is usually set very low (default: 0.000000001), we like to tradeoff disk space for lower false positives</span>
- - [bloomIndexPruneByRanges](#bloomIndexPruneByRanges) (true) <br/>
- <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, range information from files to leveraged speed up index lookups. Particularly helpful, if the key has a monotonously increasing prefix, such as timestamp.</span>
- - [bloomIndexUseCaching](#bloomIndexUseCaching) (true) <br/>
- <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, the input RDD will cached to speed up index lookup by reducing IO for computing parallelism or affected partitions</span>
- - [bloomIndexParallelism](#bloomIndexParallelism) (0) <br/>
- <span style="color:grey">Only applies if index type is BLOOM. <br/> This is the amount of parallelism for index lookup, which involves a Spark Shuffle. By default, this is auto computed based on input workload characteristics</span>
- - [hbaseZkQuorum](#hbaseZkQuorum) (zkString) <br/>
- <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum url to connect to.</span>
- - [hbaseZkPort](#hbaseZkPort) (port) <br/>
- <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span>
- - [hbaseTableName](#hbaseTableName) (tableName) <br/>
- <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span>
-
- - [withStorageConfig](#withStorageConfig) (HoodieStorageConfig) <br/>
- <span style="color:grey">Storage related configs</span>
- - [limitFileSize](#limitFileSize) (size = 120MB) <br/>
- <span style="color:grey">Hoodie re-writes a single file during update (copy_on_write) or a compaction (merge_on_read). This is fundamental unit of parallelism. It is important that this is aligned with the underlying filesystem block size. </span>
- - [parquetBlockSize](#parquetBlockSize) (rowgroupsize = 120MB) <br/>
- <span style="color:grey">Parquet RowGroup size. Its better than this is aligned with the file size, so that a single column within a file is stored continuously on disk</span>
- - [parquetPageSize](#parquetPageSize) (pagesize = 1MB) <br/>
- <span style="color:grey">Parquet page size. Page is the unit of read within a parquet file. Within a block, pages are compressed seperately. </span>
- - [logFileMaxSize](#logFileMaxSize) (logFileSize = 1GB) <br/>
- <span style="color:grey">LogFile max size. This is the maximum size allowed for a log file before it is rolled over to the next version. </span>
- - [logFileDataBlockMaxSize](#logFileDataBlockMaxSize) (dataBlockSize = 256MB) <br/>
- <span style="color:grey">LogFile Data block max size. This is the maximum size allowed for a single data block to be appended to a log file. This helps to make sure the data appended to the log file is broken up into sizable blocks to prevent from OOM errors. This size should be greater than the JVM memory. </span>
-
- - [withCompactionConfig](#withCompactionConfig) (HoodieCompactionConfig) <br/>
- <span style="color:grey">Cleaning and configurations related to compaction techniques</span>
- - [withCleanerPolicy](#withCleanerPolicy) (policy = KEEP_LATEST_COMMITS) <br/>
- <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span>
- - [retainCommits](#retainCommits) (no_of_commits_to_retain = 24) <br/>
- <span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span>
- - [archiveCommitsWith](#archiveCommitsWith) (minCommits = 96, maxCommits = 128) <br/>
- <span style="color:grey">Each commit is a small file in the .hoodie directory. Since HDFS is not designed to handle multiple small files, hoodie archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span>
- - [compactionSmallFileSize](#compactionSmallFileSize) (size = 0) <br/>
- <span style="color:grey">Small files can always happen because of the number of insert records in a paritition in a batch. Hoodie has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a "small file size". This should be less < maxFileSize and setting it to 0, turns off this feature. </span>
- - [insertSplitSize](#insertSplitSize) (size = 500000) <br/>
- <span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span>
- - [autoTuneInsertSplits](#autoTuneInsertSplits) (true) <br/>
- <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit's metadata. Turned off by default. </span>
- - [approxRecordSize](#approxRecordSize) () <br/>
- <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit's metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span>
- - [withCompactionLazyBlockReadEnabled](#withCompactionLazyBlockReadEnabled) (true) <br/>
- <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span>
- - [withMaxNumDeltaCommitsBeforeCompaction](#withMaxNumDeltaCommitsBeforeCompaction) (maxNumDeltaCommitsBeforeCompaction = 10) <br/>
- <span style="color:grey">Number of max delta commits to keep before triggering an inline compaction</span>
- - [withCompactionReverseLogReadEnabled](#withCompactionReverseLogReadEnabled) (false) <br/>
- <span style="color:grey">HoodieLogFormatReader reads a logfile in the forward direction starting from pos=0 to pos=file_length. If this config is set to true, the Reader reads the logfile in reverse direction, from pos=file_length to pos=0</span>
-
- - [withMetricsConfig](#withMetricsConfig) (HoodieMetricsConfig) <br/>
- <span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
- - [on](#on) (true) <br/>
- <span style="color:grey">Turn sending metrics on/off. on by default.</span>
- - [withReporterType](#withReporterType) (GRAPHITE) <br/>
- <span style="color:grey">Type of metrics reporter. Graphite is the default and the only value suppported.</span>
- - [toGraphiteHost](#toGraphiteHost) () <br/>
- <span style="color:grey">Graphite host to connect to</span>
- - [onGraphitePort](#onGraphitePort) () <br/>
- <span style="color:grey">Graphite port to connect to</span>
- - [usePrefix](#usePrefix) () <br/>
- <span style="color:grey">Standard prefix for all metrics</span>
-
- - [withMemoryConfig](#withMemoryConfig) (HoodieMemoryConfig) <br/>
- <span style="color:grey">Memory related configs</span>
- - [withMaxMemoryFractionPerPartitionMerge](#withMaxMemoryFractionPerPartitionMerge) (maxMemoryFractionPerPartitionMerge = 0.6) <br/>
- <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span>
- - [withMaxMemorySizePerCompactionInBytes](#withMaxMemorySizePerCompactionInBytes) (maxMemorySizePerCompactionInBytes = 1GB) <br/>
- <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span>
-
-
-#### Tuning
+ Configurations required for GCS and Hoodie co-operability.
-Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
+### Spark Datasource Configs {#spark-datasource}
+
+Spark jobs using the datasource can be configured by passing the below options into the `option(k,v)` method as usual.
+The actual datasource level configs are listed below.
+
+#### Write Options
+
+Additionally, you can pass down any of the WriteClient level configs directly using `options()` or `option(k,v)` methods.
+
+```
+inputDF.write()
+.format("com.uber.hoodie")
+.options(clientOpts) // any of the Hudi client opts can be passed in as well
+.option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY(), "_row_key")
+.option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY(), "partition")
+.option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY(), "timestamp")
+.option(HoodieWriteConfig.TABLE_NAME, tableName)
+.mode(SaveMode.Append)
+.save(basePath);
+```
+
+Options useful for writing datasets via `write.format.option(...)`
-**Write operations** : Use `bulkinsert` to load new data into a table, and there on use `upsert`/`insert`.
- Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.
+- [TABLE_NAME_OPT_KEY](#TABLE_NAME_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.table.name` [Required]<br/>
+ <span style="color:grey">Hive table name, to register the dataset into.</span>
+- [OPERATION_OPT_KEY](#OPERATION_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.operation`, Default: `upsert`<br/>
+ <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation. Use `bulkinsert` to load new data into a table, and there on use `upsert`/`insert`.
+ bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</span>
+- [STORAGE_TYPE_OPT_KEY](#STORAGE_TYPE_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.storage.type`, Default: `COPY_ON_WRITE` <br/>
+ <span style="color:grey">The storage type for the underlying data, for this write. This can't change between writes.</span>
+- [PRECOMBINE_FIELD_OPT_KEY](#PRECOMBINE_FIELD_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.precombine.field`, Default: `ts` <br/>
+ <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
+we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span>
+- [PAYLOAD_CLASS_OPT_KEY](#PAYLOAD_CLASS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.payload.class`, Default: `com.uber.hoodie.OverwriteWithLatestAvroPayload` <br/>
+ <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
+ This will render any value set for `PRECOMBINE_FIELD_OPT_VAL` in-effective</span>
+- [RECORDKEY_FIELD_OPT_KEY](#RECORDKEY_FIELD_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.recordkey.field`, Default: `uuid` <br/>
+ <span style="color:grey">Record key field. Value to be used as the `recordKey` component of `HoodieKey`. Actual value
+will be obtained by invoking .toString() on the field value. Nested fields can be specified using
+the dot notation eg: `a.b.c`</span>
+- [PARTITIONPATH_FIELD_OPT_KEY](#PARTITIONPATH_FIELD_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.partitionpath.field`, Default: `partitionpath` <br/>
+ <span style="color:grey">Partition path field. Value to be used at the `partitionPath` component of `HoodieKey`.
+Actual value ontained by invoking .toString()</span>
+- [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.keygenerator.class`, Default: `com.uber.hoodie.SimpleKeyGenerator` <br/>
+ <span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
+- [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.commitmeta.key.prefix`, Default: `_` <br/>
+ <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
+This is useful to store checkpointing information, in a consistent way with the hudi timeline</span>
+- [INSERT_DROP_DUPS_OPT_KEY](#INSERT_DROP_DUPS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.write.insert.drop.duplicates`, Default: `false` <br/>
+ <span style="color:grey">If set to true, filters out all duplicate records from incoming dataframe, during insert operations. </span>
+- [HIVE_SYNC_ENABLED_OPT_KEY](#HIVE_SYNC_ENABLED_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.enable`, Default: `false` <br/>
+ <span style="color:grey">When set to true, register/sync the dataset to Apache Hive metastore</span>
+- [HIVE_DATABASE_OPT_KEY](#HIVE_DATABASE_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.database`, Default: `default` <br/>
+ <span style="color:grey">database to sync to</span>
+- [HIVE_TABLE_OPT_KEY](#HIVE_TABLE_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.table`, [Required] <br/>
+ <span style="color:grey">table to sync to</span>
+- [HIVE_USER_OPT_KEY](#HIVE_USER_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.username`, Default: `hive` <br/>
+ <span style="color:grey">hive user name to use</span>
+- [HIVE_PASS_OPT_KEY](#HIVE_PASS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.password`, Default: `hive` <br/>
+ <span style="color:grey">hive password to use</span>
+- [HIVE_URL_OPT_KEY](#HIVE_URL_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.jdbcurl`, Default: `jdbc:hive2://localhost:10000` <br/>
+ <span style="color:grey">Hive metastore url</span>
+- [HIVE_PARTITION_FIELDS_OPT_KEY](#HIVE_PARTITION_FIELDS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.partition_fields`, Default: ` ` <br/>
+ <span style="color:grey">field in the dataset to use for determining hive partition columns.</span>
+- [HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY](#HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.partition_extractor_class`, Default: `com.uber.hoodie.hive.SlashEncodedDayPartitionValueExtractor` <br/>
+ <span style="color:grey">Class used to extract partition field values into hive partition columns.</span>
+- [HIVE_ASSUME_DATE_PARTITION_OPT_KEY](#HIVE_ASSUME_DATE_PARTITION_OPT_KEY)<br/>
+ Property: `hoodie.datasource.hive_sync.assume_date_partitioning`, Default: `false` <br/>
+ <span style="color:grey">Assume partitioning is yyyy/mm/dd</span>
+
+#### Read Options
+
+Options useful for reading datasets via `read.format.option(...)`
+
+- [VIEW_TYPE_OPT_KEY](#VIEW_TYPE_OPT_KEY) <br/>
+Property: `hoodie.datasource.view.type`, Default: `read_optimized` <br/>
+<span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
+(or) Read Optimized mode (obtain latest view, based on columnar data)
+(or) Real time mode (obtain latest view, based on row & columnar data)</span>
+- [BEGIN_INSTANTTIME_OPT_KEY](#BEGIN_INSTANTTIME_OPT_KEY) <br/>
+Property: `hoodie.datasource.read.begin.instanttime`, [Required in incremental mode] <br/>
+<span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
+necessarily correspond to an instant on the timeline. New data written with an
+ `instant_time > BEGIN_INSTANTTIME` are fetched out. For e.g: '20170901080000' will get
+ all new data written after Sep 1, 2017 08:00AM.</span>
+- [END_INSTANTTIME_OPT_KEY](#END_INSTANTTIME_OPT_KEY) <br/>
+Property: `hoodie.datasource.read.end.instanttime`, Default: latest instant (i.e fetches all new data since begin instant time) <br/>
+<span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
+`instant_time <= END_INSTANTTIME` are fetched out.</span>
+
+### WriteClient Configs {#writeclient-configs}
+
+Jobs programming directly against the RDD level apis can build a `HoodieWriteConfig` object and pass it in to the `HoodieWriteClient` constructor.
+HoodieWriteConfig can be built using a builder pattern as below.
+
+```
+HoodieWriteConfig cfg = HoodieWriteConfig.newBuilder()
+ .withPath(basePath)
+ .forTable(tableName)
+ .withSchema(schemaStr)
+ .withProps(props) // pass raw k,v pairs from a property file.
+ .withCompactionConfig(HoodieCompactionConfig.newBuilder().withXXX(...).build())
+ .withIndexConfig(HoodieIndexConfig.newBuilder().withXXX(...).build())
+ ...
+ .build();
+```
+
+Following subsections go over different aspects of write configs, explaining most important configs with their property names, default values.
+
+- [withPath](#withPath) (hoodie_base_path)
+Property: `hoodie.base.path` [Required] <br/>
+<span style="color:grey">Base HDFS path under which all the data partitions are created. Always prefix it explicitly with the storage scheme (e.g hdfs://, s3:// etc). Hudi stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span>
+- [withSchema](#withSchema) (schema_str) <br/>
+Property: `hoodie.avro.schema` [Required]<br/>
+<span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span>
+- [forTable](#forTable) (table_name)<br/>
+Property: `hoodie.table.name` [Required] <br/>
+ <span style="color:grey">Table name for the dataset, will be used for registering with Hive. Needs to be same across runs.</span>
+- [withBulkInsertParallelism](#withBulkInsertParallelism) (bulk_insert_parallelism = 1500) <br/>
+Property: `hoodie.bulkinsert.shuffle.parallelism`<br/>
+<span style="color:grey">Bulk insert is meant to be used for large initial imports and this parallelism determines the initial number of files in your dataset. Tune this to achieve a desired optimal size during initial import.</span>
+- [withParallelism](#withParallelism) (insert_shuffle_parallelism = 1500, upsert_shuffle_parallelism = 1500)<br/>
+Property: `hoodie.insert.shuffle.parallelism`, `hoodie.upsert.shuffle.parallelism`<br/>
+<span style="color:grey">Once data has been initially imported, this parallelism controls initial parallelism for reading input records. Ensure this value is high enough say: 1 partition for 1 GB of input data</span>
+- [combineInput](#combineInput) (on_insert = false, on_update=true)<br/>
+Property: `hoodie.combine.before.insert`, `hoodie.combine.before.upsert`<br/>
+<span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span>
+- [withWriteStatusStorageLevel](#withWriteStatusStorageLevel) (level = MEMORY_AND_DISK_SER)<br/>
+Property: `hoodie.write.status.storage.level`<br/>
+<span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span>
+- [withAutoCommit](#withAutoCommit) (autoCommit = true)<br/>
+Property: `hoodie.auto.commit`<br/>
+<span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a "defined success condition"</span>
+- [withAssumeDatePartitioning](#withAssumeDatePartitioning) (assumeDatePartitioning = false)<br/>
+Property: ` hoodie.assume.date.partitioning`<br/>
+<span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span>
+- [withConsistencyCheckEnabled](#withConsistencyCheckEnabled) (enabled = false)<br/>
+Property: `hoodie.consistency.check.enabled`<br/>
+<span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files' are listable on the underlying filesystem/storage. Set this to true, to workaround S3's eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span>
+
+#### Index configs
+Following configs control indexing behavior, which tags incoming records as either inserts or updates to older records.
+
+- [withIndexConfig](#withIndexConfig) (HoodieIndexConfig) <br/>
+ <span style="color:grey">This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
+ - [withIndexType](#withIndexType) (indexType = BLOOM) <br/>
+ Property: `hoodie.index.type` <br/>
+ <span style="color:grey">Type of index to use. Default is Bloom filter. Possible options are [BLOOM | HBASE | INMEMORY]. Bloom filters removes the dependency on a external system and is stored in the footer of the Parquet Data Files</span>
+ - [bloomFilterNumEntries](#bloomFilterNumEntries) (numEntries = 60000) <br/>
+ Property: `hoodie.index.bloom.num_entries` <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/>This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. [HUDI-56](https://issues.apache.org/jira/browse/HUDI-56) tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positives and ind [...]
+ - [bloomFilterFPP](#bloomFilterFPP) (fpp = 0.000000001) <br/>
+ Property: `hoodie.index.bloom.fpp` <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> Error rate allowed given the number of entries. This is used to calculate how many bits should be assigned for the bloom filter and the number of hash functions. This is usually set very low (default: 0.000000001), we like to tradeoff disk space for lower false positives</span>
+ - [bloomIndexPruneByRanges](#bloomIndexPruneByRanges) (pruneRanges = true) <br/>
+ Property: `hoodie.bloom.index.prune.by.ranges` <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, range information from files to leveraged speed up index lookups. Particularly helpful, if the key has a monotonously increasing prefix, such as timestamp.</span>
+ - [bloomIndexUseCaching](#bloomIndexUseCaching) (useCaching = true) <br/>
+ Property: `hoodie.bloom.index.use.caching` <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, the input RDD will cached to speed up index lookup by reducing IO for computing parallelism or affected partitions</span>
+ - [bloomIndexParallelism](#bloomIndexParallelism) (0) <br/>
+ Property: `hoodie.bloom.index.parallelism` <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> This is the amount of parallelism for index lookup, which involves a Spark Shuffle. By default, this is auto computed based on input workload characteristics</span>
+ - [hbaseZkQuorum](#hbaseZkQuorum) (zkString) [Required]<br/>
+ Property: `hoodie.index.hbase.zkquorum` <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum url to connect to.</span>
+ - [hbaseZkPort](#hbaseZkPort) (port) [Required]<br/>
+ Property: `hoodie.index.hbase.zkport` <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span>
+ - [hbaseTableName](#hbaseTableName) (tableName) [Required]<br/>
+ Property: `hoodie.index.hbase.table` <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span>
+
+#### Storage configs
+Controls aspects around sizing parquet and log files.
+
+- [withStorageConfig](#withStorageConfig) (HoodieStorageConfig) <br/>
+ - [limitFileSize](#limitFileSize) (size = 120MB) <br/>
+ Property: `hoodie.parquet.max.file.size` <br/>
+ <span style="color:grey">Target size for parquet files produced by Hudi write phases. For HDFS, this needs to be aligned with the underlying filesystem block size for optimal performance. </span>
+ - [parquetBlockSize](#parquetBlockSize) (rowgroupsize = 120MB) <br/>
+ Property: `hoodie.parquet.block.size` <br/>
+ <span style="color:grey">Parquet RowGroup size. Its better this is same as the file size, so that a single column within a file is stored continuously on disk</span>
+ - [parquetPageSize](#parquetPageSize) (pagesize = 1MB) <br/>
+ Property: `hoodie.parquet.page.size` <br/>
+ <span style="color:grey">Parquet page size. Page is the unit of read within a parquet file. Within a block, pages are compressed seperately. </span>
+ - [parquetCompressionRatio](#parquetCompressionRatio) (parquetCompressionRatio = 0.1) <br/>
+ Property: `hoodie.parquet.compression.ratio` <br/>
+ <span style="color:grey">Expected compression of parquet data used by Hudi, when it tries to size new parquet files. Increase this value, if bulk_insert is producing smaller than expected sized files</span>
+ - [logFileMaxSize](#logFileMaxSize) (logFileSize = 1GB) <br/>
+ Property: `hoodie.logfile.max.size` <br/>
+ <span style="color:grey">LogFile max size. This is the maximum size allowed for a log file before it is rolled over to the next version. </span>
+ - [logFileDataBlockMaxSize](#logFileDataBlockMaxSize) (dataBlockSize = 256MB) <br/>
+ Property: `hoodie.logfile.data.block.max.size` <br/>
+ <span style="color:grey">LogFile Data block max size. This is the maximum size allowed for a single data block to be appended to a log file. This helps to make sure the data appended to the log file is broken up into sizable blocks to prevent from OOM errors. This size should be greater than the JVM memory. </span>
+ - [logFileToParquetCompressionRatio](#logFileToParquetCompressionRatio) (logFileToParquetCompressionRatio = 0.35) <br/>
+ Property: `hoodie.logfile.to.parquet.compression.ratio` <br/>
+ <span style="color:grey">Expected additional compression as records move from log files to parquet. Used for merge_on_read storage to send inserts into log files & control the size of compacted parquet file.</span>
+
+#### Compaction configs
+Configs that control compaction (merging of log files onto a new parquet base file), cleaning (reclamation of older/unused file groups).
+
+- [withCompactionConfig](#withCompactionConfig) (HoodieCompactionConfig) <br/>
+ - [withCleanerPolicy](#withCleanerPolicy) (policy = KEEP_LATEST_COMMITS) <br/>
+ Property: `hoodie.cleaner.policy` <br/>
+ <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span>
+ - [retainCommits](#retainCommits) (no_of_commits_to_retain = 24) <br/>
+ Property: `hoodie.cleaner.commits.retained` <br/>
+ <span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span>
+ - [archiveCommitsWith](#archiveCommitsWith) (minCommits = 96, maxCommits = 128) <br/>
+ Property: `hoodie.keep.min.commits`, `hoodie.keep.max.commits` <br/>
+ <span style="color:grey">Each commit is a small file in the `.hoodie` directory. Since HDFS is not designed to handle multiple small files, Hudi archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span>
+ - [compactionSmallFileSize](#compactionSmallFileSize) (size = 0) <br/>
+ Property: `hoodie.parquet.small.file.limit` <br/>
+ <span style="color:grey">This should be less < maxFileSize and setting it to 0, turns off this feature. Small files can always happen because of the number of insert records in a partition in a batch. Hudi has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a "small file size".</span>
+ - [insertSplitSize](#insertSplitSize) (size = 500000) <br/>
+ Property: `hoodie.copyonwrite.insert.split.size` <br/>
+ <span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span>
+ - [autoTuneInsertSplits](#autoTuneInsertSplits) (true) <br/>
+ Property: `hoodie.copyonwrite.insert.auto.split` <br/>
+ <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit's metadata. Turned off by default. </span>
+ - [approxRecordSize](#approxRecordSize) () <br/>
+ Property: `hoodie.copyonwrite.record.size.estimate` <br/>
+ <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit's metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span>
+ - [withInlineCompaction](#withInlineCompaction) (inlineCompaction = false) <br/>
+ Property: `hoodie.compact.inline` <br/>
+ <span style="color:grey">When set to true, compaction is triggered by the ingestion itself, right after a commit/deltacommit action as part of insert/upsert/bulk_insert</span>
+ - [withMaxNumDeltaCommitsBeforeCompaction](#withMaxNumDeltaCommitsBeforeCompaction) (maxNumDeltaCommitsBeforeCompaction = 10) <br/>
+ Property: `hoodie.compact.inline.max.delta.commits` <br/>
+ <span style="color:grey">Number of max delta commits to keep before triggering an inline compaction</span>
+ - [withCompactionLazyBlockReadEnabled](#withCompactionLazyBlockReadEnabled) (true) <br/>
+ Property: `hoodie.compaction.lazy.block.read` <br/>
+ <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span>
+ - [withCompactionReverseLogReadEnabled](#withCompactionReverseLogReadEnabled) (false) <br/>
+ Property: `hoodie.compaction.reverse.log.read` <br/>
+ <span style="color:grey">HoodieLogFormatReader reads a logfile in the forward direction starting from pos=0 to pos=file_length. If this config is set to true, the Reader reads the logfile in reverse direction, from pos=file_length to pos=0</span>
+ - [withCleanerParallelism](#withCleanerParallelism) (cleanerParallelism = 200) <br/>
+ Property: `hoodie.cleaner.parallelism` <br/>
+ <span style="color:grey">Increase this if cleaning becomes slow.</span>
+ - [withCompactionStrategy](#withCompactionStrategy) (compactionStrategy = com.uber.hoodie.io.compact.strategy.LogFileSizeBasedCompactionStrategy) <br/>
+ Property: `hoodie.compaction.strategy` <br/>
+ <span style="color:grey">Compaction strategy decides which file groups are picked up for compaction during each compaction run. By default. Hudi picks the log file with most accumulated unmerged data</span>
+ - [withTargetIOPerCompactionInMB](#withTargetIOPerCompactionInMB) (targetIOPerCompactionInMB = 500000) <br/>
+ Property: `hoodie.compaction.target.io` <br/>
+ <span style="color:grey">Amount of MBs to spend during compaction run for the LogFileSizeBasedCompactionStrategy. This value helps bound ingestion latency while compaction is run inline mode.</span>
+ - [withTargetPartitionsPerDayBasedCompaction](#withTargetPartitionsPerDayBasedCompaction) (targetPartitionsPerCompaction = 10) <br/>
+ Property: `hoodie.compaction.daybased.target` <br/>
+ <span style="color:grey">Used by com.uber.hoodie.io.compact.strategy.DayBasedCompactionStrategy to denote the number of latest partitions to compact during a compaction run.</span>
+ - [withPayloadClass](#payloadClassName) (payloadClassName = com.uber.hoodie.common.model.HoodieAvroPayload) <br/>
+ Property: `hoodie.compaction.payload.class` <br/>
+ <span style="color:grey">This needs to be same as class used during insert/upserts. Just like writing, compaction also uses the record payload class to merge records in the log against each other, merge again with the base file and produce the final record to be written after compaction.</span>
+
+
+#### Metrics configs
+Enables reporting of Hudi metrics to graphite.
+
+- [withMetricsConfig](#withMetricsConfig) (HoodieMetricsConfig) <br/>
+<span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
+ - [on](#on) (metricsOn = true) <br/>
+ Property: `hoodie.metrics.on` <br/>
+ <span style="color:grey">Turn sending metrics on/off. on by default.</span>
+ - [withReporterType](#withReporterType) (reporterType = GRAPHITE) <br/>
+ Property: `hoodie.metrics.reporter.type` <br/>
+ <span style="color:grey">Type of metrics reporter. Graphite is the default and the only value suppported.</span>
+ - [toGraphiteHost](#toGraphiteHost) (host = localhost) <br/>
+ Property: `hoodie.metrics.graphite.host` <br/>
+ <span style="color:grey">Graphite host to connect to</span>
+ - [onGraphitePort](#onGraphitePort) (port = 4756) <br/>
+ Property: `hoodie.metrics.graphite.port` <br/>
+ <span style="color:grey">Graphite port to connect to</span>
+ - [usePrefix](#usePrefix) (prefix = "") <br/>
+ Property: `hoodie.metrics.graphite.metric.prefix` <br/>
+ <span style="color:grey">Standard prefix applied to all metrics. This helps to add datacenter, environment information for e.g</span>
+
+#### Memory configs
+Controls memory usage for compaction and merges, performed internally by Hudi
+
+- [withMemoryConfig](#withMemoryConfig) (HoodieMemoryConfig) <br/>
+<span style="color:grey">Memory related configs</span>
+ - [withMaxMemoryFractionPerPartitionMerge](#withMaxMemoryFractionPerPartitionMerge) (maxMemoryFractionPerPartitionMerge = 0.6) <br/>
+ Property: `hoodie.memory.merge.fraction` <br/>
+ <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span>
+ - [withMaxMemorySizePerCompactionInBytes](#withMaxMemorySizePerCompactionInBytes) (maxMemorySizePerCompactionInBytes = 1GB) <br/>
+ Property: `hoodie.memory.compaction.fraction` <br/>
+ <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span>
+
+
+### Tuning
+
+Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
**Input Parallelism** : By default, Hoodie tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
diff --git a/docs/css/customstyles.css b/docs/css/customstyles.css
index d6667a5..56dcdba 100644
--- a/docs/css/customstyles.css
+++ b/docs/css/customstyles.css
@@ -1,5 +1,5 @@
body {
- font-size:15px;
+ font-size:14px;
}
.bs-callout {
@@ -607,7 +607,7 @@ a.fa.fa-envelope-o.mailto {
font-weight: 600;
}
-h3 {color: #ED1951; font-weight:normal; font-size:130%;}
+h3 {color: #545253; font-weight:normal; font-size:130%;}
h4 {color: #808080; font-weight:normal; font-size:120%; font-style:italic;}
.alert, .callout {
diff --git a/docs/css/theme-blue.css b/docs/css/theme-blue.css
index 9a923ef..46fbd0d 100644
--- a/docs/css/theme-blue.css
+++ b/docs/css/theme-blue.css
@@ -5,7 +5,7 @@
}
-h3 {color: #ED1951; }
+h3 {color: #545253; }
h4 {color: #808080; }
.nav-tabs > li.active > a, .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus {
diff --git a/docs/gcs_filesystem.md b/docs/gcs_filesystem.md
index 8cc82da..26c4401 100644
--- a/docs/gcs_filesystem.md
+++ b/docs/gcs_filesystem.md
@@ -1,5 +1,5 @@
---
-title: GCS Filesystem (experimental)
+title: GCS Filesystem
keywords: hudi, hive, google cloud, storage, spark, presto
sidebar: mydoc_sidebar
permalink: gcs_hoodie.html
diff --git a/docs/s3_filesystem.md b/docs/s3_filesystem.md
index 9bbe068..6c7b636 100644
--- a/docs/s3_filesystem.md
+++ b/docs/s3_filesystem.md
@@ -1,5 +1,5 @@
---
-title: S3 Filesystem (experimental)
+title: S3 Filesystem
keywords: hudi, hive, aws, s3, spark, presto
sidebar: mydoc_sidebar
permalink: s3_hoodie.html
[incubator-hudi-site] 10/19: Content for first version of
hudi.apache.org
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit db5b61ad36b4411cc6373c3dce9cc7baa14845b5
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Fri Feb 15 21:17:26 2019 -0800
Content for first version of hudi.apache.org
---
content/.gitignore | 1 +
content/404.html | 398 ++
content/Gemfile | 10 +
content/Gemfile.lock | 156 +
content/admin_guide.html | 804 +++
content/api_docs.html | 399 ++
content/code_and_design.html | 462 ++
content/community.html | 388 ++
content/comparison.html | 423 ++
content/concepts.html | 586 +++
content/configurations.html | 601 +++
content/css/bootstrap.min.css | 5 +
content/css/customstyles.css | 1181 +++++
content/css/font-awesome.min.css | 4 +
content/css/fonts/FontAwesome.otf | Bin 0 -> 93888 bytes
content/css/fonts/fontawesome-webfont.eot | Bin 0 -> 60767 bytes
content/css/fonts/fontawesome-webfont.svg | 565 +++
content/css/fonts/fontawesome-webfont.ttf | Bin 0 -> 122092 bytes
content/css/fonts/fontawesome-webfont.woff | Bin 0 -> 71508 bytes
content/css/fonts/fontawesome-webfont.woff2 | Bin 0 -> 56780 bytes
content/css/lavish-bootstrap.css | 5899 ++++++++++++++++++++++
content/css/modern-business.css | 93 +
content/css/printstyles.css | 160 +
content/css/syntax.css | 60 +
content/css/theme-blue.css | 105 +
content/css/theme-green.css | 99 +
content/dev_setup.html | 403 ++
content/feed.xml | 28 +
content/feed.xslt.xml | 4 +
content/fonts/FontAwesome.otf | Bin 0 -> 85908 bytes
content/fonts/fontawesome-webfont.eot | Bin 0 -> 56006 bytes
content/fonts/fontawesome-webfont.svg | 520 ++
content/fonts/fontawesome-webfont.ttf | Bin 0 -> 112160 bytes
content/fonts/fontawesome-webfont.woff | Bin 0 -> 65452 bytes
content/fonts/glyphicons-halflings-regular.eot | Bin 0 -> 20127 bytes
content/fonts/glyphicons-halflings-regular.svg | 288 ++
content/fonts/glyphicons-halflings-regular.ttf | Bin 0 -> 45404 bytes
content/fonts/glyphicons-halflings-regular.woff | Bin 0 -> 23424 bytes
content/fonts/glyphicons-halflings-regular.woff2 | Bin 0 -> 18028 bytes
content/gcs_hoodie.html | 434 ++
content/images/async_compac_1.png | Bin 0 -> 60344 bytes
content/images/async_compac_2.png | Bin 0 -> 54164 bytes
content/images/async_compac_3.png | Bin 0 -> 70516 bytes
content/images/async_compac_4.png | Bin 0 -> 66932 bytes
content/images/favicon.ico | Bin 0 -> 1150 bytes
content/images/hoodie_commit_duration.png | Bin 0 -> 869144 bytes
content/images/hoodie_cow.png | Bin 0 -> 31136 bytes
content/images/hoodie_intro_1.png | Bin 0 -> 23478 bytes
content/images/hoodie_log_format_v2.png | Bin 0 -> 223676 bytes
content/images/hoodie_mor.png | Bin 0 -> 56002 bytes
content/images/hoodie_query_perf_hive.png | Bin 0 -> 158481 bytes
content/images/hoodie_query_perf_presto.png | Bin 0 -> 33727 bytes
content/images/hoodie_query_perf_spark.png | Bin 0 -> 29384 bytes
content/images/hoodie_timeline.png | Bin 0 -> 23093 bytes
content/images/hoodie_upsert_dag.png | Bin 0 -> 503771 bytes
content/images/hoodie_upsert_perf1.png | Bin 0 -> 15984 bytes
content/images/hoodie_upsert_perf2.png | Bin 0 -> 18954 bytes
content/images/hudi_site_logo.png | Bin 0 -> 13170 bytes
content/images/workflowarrow.png | Bin 0 -> 3595 bytes
content/implementation.html | 660 +++
content/incremental_processing.html | 674 +++
content/index.html | 422 +-
content/js/customscripts.js | 55 +
content/js/jekyll-search.js | 1 +
content/js/jquery.ba-throttle-debounce.min.js | 9 +
content/js/jquery.localScroll.min.js | 7 +
content/js/jquery.navgoco.min.js | 8 +
content/js/jquery.scrollTo.min.js | 7 +
content/js/jquery.shuffle.min.js | 1588 ++++++
content/js/mydoc_scroll.html | 634 +++
content/js/toc.js | 82 +
content/licenses/LICENSE | 21 +
content/licenses/LICENSE-BSD-NAVGOCO.txt | 27 +
content/migration_guide.html | 464 ++
content/news.html | 299 ++
content/news_archive.html | 398 ++
content/powered_by.html | 415 ++
content/quickstart.html | 1613 ++++++
content/roadmap.html | 405 ++
content/s3_hoodie.html | 447 ++
content/search.json | 277 +
content/sitemap.xml | 159 +
content/sql_queries.html | 432 ++
content/strata-talk.html | 383 ++
content/use_cases.html | 432 ++
85 files changed, 23994 insertions(+), 1 deletion(-)
diff --git a/content/.gitignore b/content/.gitignore
new file mode 100644
index 0000000..e43b0f9
--- /dev/null
+++ b/content/.gitignore
@@ -0,0 +1 @@
+.DS_Store
diff --git a/content/404.html b/content/404.html
new file mode 100644
index 0000000..5c95e2c
--- /dev/null
+++ b/content/404.html
@@ -0,0 +1,398 @@
+<!DOCTYPE html>
+<head>
+ <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<meta name="description" content="">
+<meta name="keywords" content=" ">
+<title>Page Not Found | Hudi</title>
+<link rel="stylesheet" href="css/syntax.css">
+
+
+<link rel="stylesheet" type="text/css" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css">
+<!--<link rel="stylesheet" type="text/css" href="css/bootstrap.min.css">-->
+<link rel="stylesheet" href="css/modern-business.css">
+<link rel="stylesheet" href="css/lavish-bootstrap.css">
+<link rel="stylesheet" href="css/customstyles.css">
+<link rel="stylesheet" href="css/theme-blue.css">
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.1.4/jquery.min.js"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery-cookie/1.4.1/jquery.cookie.min.js"></script>
+<script src="js/jquery.navgoco.min.js"></script>
+
+
+<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/js/bootstrap.min.js"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/2.0.0/anchor.min.js"></script>
+<script src="js/toc.js"></script>
+<script src="js/customscripts.js"></script>
+
+<script>
+ (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
+ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
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+ })(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
+
+ ga('create', 'UA-93561550-1', 'auto');
+ ga('send', 'pageview');
+
+</script>
+
+<link rel="shortcut icon" href="images/favicon.ico">
+
+<!-- HTML5 Shim and Respond.js IE8 support of HTML5 elements and media queries -->
+<!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/libs/html5shiv/3.7.0/html5shiv.js"></script>
+<script src="https://oss.maxcdn.com/libs/respond.js/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+<link rel="alternate" type="application/rss+xml" title="" href="http://0.0.0.0:4000feed.xml">
+
+ <script>
+ $(document).ready(function() {
+ // Initialize navgoco with default options
+ $("#mysidebar").navgoco({
+ caretHtml: '',
+ accordion: true,
+ openClass: 'active', // open
+ save: false, // leave false or nav highlighting doesn't work right
+ cookie: {
+ name: 'navgoco',
+ expires: false,
+ path: '/'
+ },
+ slide: {
+ duration: 400,
+ easing: 'swing'
+ }
+ });
+
+ $("#collapseAll").click(function(e) {
+ e.preventDefault();
+ $("#mysidebar").navgoco('toggle', false);
+ });
+
+ $("#expandAll").click(function(e) {
+ e.preventDefault();
+ $("#mysidebar").navgoco('toggle', true);
+ });
+
+ });
+
+ </script>
+ <script>
+ $(function () {
+ $('[data-toggle="tooltip"]').tooltip()
+ })
+ </script>
+
+
+</head>
+<body>
+<!-- Navigation -->
+
+<nav class="navbar navbar-inverse navbar-fixed-top">
+ <div class="container topnavlinks">
+ <div class="navbar-header">
+ <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
+ <span class="sr-only">Toggle navigation</span>
+ <span class="icon-bar"></span>
+ <span class="icon-bar"></span>
+ <span class="icon-bar"></span>
+ </button>
+
+ <a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
+ <img src="images/hudi_site_logo.png" alt="Hudi logo"/>
+ <!--Hudi-->
+ </span></a>
+ </div>
+ <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
+ <ul class="nav navbar-nav navbar-right">
+ <!-- entries without drop-downs appear here -->
+
+
+
+ <li><a href="news">News</a></li>
+
+
+
+ <li><a href="community.html">Community</a></li>
+
+
+
+ <li><a href="https://github.com/uber/hoodie" target="_blank">Github</a></li>
+
+
+
+ <!-- entries with drop-downs appear here -->
+ <!-- conditional logic to control which topnav appears for the audience defined in the configuration file.-->
+
+
+ <li class="dropdown">
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">Developer Resources<b class="caret"></b></a>
+ <ul class="dropdown-menu">
+
+
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+
+
+ <li><a href="code_and_design.html">Code Structure</a></li>
+
+
+
+ <li><a href="roadmap.html">Roadmap</a></li>
+
+
+ </ul>
+ </li>
+
+
+
+ <li>
+
+
+
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Page Not Found page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+
+<li>
+
+
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+ <li>
+ <!--start search-->
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+ <input type="text" id="search-input" placeholder="search...">
+ <ul id="results-container"></ul>
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+ <script src="js/jekyll-search.js" type="text/javascript"></script>
+ <script type="text/javascript">
+ SimpleJekyllSearch.init({
+ searchInput: document.getElementById('search-input'),
+ resultsContainer: document.getElementById('results-container'),
+ dataSource: 'search.json',
+ searchResultTemplate: '<li><a href="{url}" title="Page Not Found">{title}</a></li>',
+ noResultsText: 'No results found.',
+ limit: 10,
+ fuzzy: true,
+ })
+ </script>
+ <!--end search-->
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+ <!-- /.container -->
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+
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+<div class="container">
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+ <!-- Content Row -->
+ <div class="row">
+ <!-- Sidebar Column -->
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+
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+
+
+
+
+<ul id="mysidebar" class="nav">
+ <li class="sidebarTitle">Latest Version</li>
+
+
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+ <li>
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+ <ul>
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+</div>
+
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+<script>$("li.active").parents('li').toggleClass("active");</script>
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+</div>
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+$( document ).ready(function() {
+ // Handler for .ready() called.
+
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+
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+$('#toc').on('click', 'a', function() {
+ var target = $(this.getAttribute('href'))
+ , scroll_target = target.offset().top
+
+ $(window).scrollTop(scroll_target - 10);
+ return false
+})
+
+});
+</script>
+
+<div id="toc"></div>
+
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+ <p>Sorry, but the page you were trying to view does not exist. Try searching for it or looking at the URL to see if it looks correct.</p>
+
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+ <div class="tags">
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+
+<hr class="shaded"/>
+
+<footer>
+ <div class="row">
+ <div class="col-lg-12 footer">
+ ©2019 . All rights reserved. <br />
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diff --git a/content/Gemfile b/content/Gemfile
new file mode 100644
index 0000000..b301eda
--- /dev/null
+++ b/content/Gemfile
@@ -0,0 +1,10 @@
+source "https://rubygems.org"
+
+
+gem "jekyll", "3.3.1"
+
+
+group :jekyll_plugins do
+ gem "jekyll-feed", "~> 0.6"
+ gem 'github-pages', '~> 106'
+end
diff --git a/content/Gemfile.lock b/content/Gemfile.lock
new file mode 100644
index 0000000..b72b9b1
--- /dev/null
+++ b/content/Gemfile.lock
@@ -0,0 +1,156 @@
+GEM
+ remote: https://rubygems.org/
+ specs:
+ activesupport (4.2.7)
+ i18n (~> 0.7)
+ json (~> 1.7, >= 1.7.7)
+ minitest (~> 5.1)
+ thread_safe (~> 0.3, >= 0.3.4)
+ tzinfo (~> 1.1)
+ addressable (2.4.0)
+ coffee-script (2.4.1)
+ coffee-script-source
+ execjs
+ coffee-script-source (1.12.2)
+ colorator (1.1.0)
+ concurrent-ruby (1.1.4)
+ ethon (0.12.0)
+ ffi (>= 1.3.0)
+ execjs (2.7.0)
+ faraday (0.15.4)
+ multipart-post (>= 1.2, < 3)
+ ffi (1.10.0)
+ forwardable-extended (2.6.0)
+ gemoji (2.1.0)
+ github-pages (106)
+ activesupport (= 4.2.7)
+ github-pages-health-check (= 1.2.0)
+ jekyll (= 3.3.1)
+ jekyll-avatar (= 0.4.2)
+ jekyll-coffeescript (= 1.0.1)
+ jekyll-feed (= 0.8.0)
+ jekyll-gist (= 1.4.0)
+ jekyll-github-metadata (= 2.2.0)
+ jekyll-mentions (= 1.2.0)
+ jekyll-paginate (= 1.1.0)
+ jekyll-redirect-from (= 0.11.0)
+ jekyll-relative-links (= 0.2.1)
+ jekyll-sass-converter (= 1.3.0)
+ jekyll-seo-tag (= 2.1.0)
+ jekyll-sitemap (= 0.12.0)
+ jekyll-swiss (= 0.4.0)
+ jemoji (= 0.7.0)
+ kramdown (= 1.11.1)
+ liquid (= 3.0.6)
+ listen (= 3.0.6)
+ mercenary (~> 0.3)
+ minima (= 2.0.0)
+ rouge (= 1.11.1)
+ terminal-table (~> 1.4)
+ github-pages-health-check (1.2.0)
+ addressable (~> 2.3)
+ net-dns (~> 0.8)
+ octokit (~> 4.0)
+ public_suffix (~> 1.4)
+ typhoeus (~> 0.7)
+ html-pipeline (2.10.0)
+ activesupport (>= 2)
+ nokogiri (>= 1.4)
+ i18n (0.9.5)
+ concurrent-ruby (~> 1.0)
+ jekyll (3.3.1)
+ addressable (~> 2.4)
+ colorator (~> 1.0)
+ jekyll-sass-converter (~> 1.0)
+ jekyll-watch (~> 1.1)
+ kramdown (~> 1.3)
+ liquid (~> 3.0)
+ mercenary (~> 0.3.3)
+ pathutil (~> 0.9)
+ rouge (~> 1.7)
+ safe_yaml (~> 1.0)
+ jekyll-avatar (0.4.2)
+ jekyll (~> 3.0)
+ jekyll-coffeescript (1.0.1)
+ coffee-script (~> 2.2)
+ jekyll-feed (0.8.0)
+ jekyll (~> 3.3)
+ jekyll-gist (1.4.0)
+ octokit (~> 4.2)
+ jekyll-github-metadata (2.2.0)
+ jekyll (~> 3.1)
+ octokit (~> 4.0, != 4.4.0)
+ jekyll-mentions (1.2.0)
+ activesupport (~> 4.0)
+ html-pipeline (~> 2.3)
+ jekyll (~> 3.0)
+ jekyll-paginate (1.1.0)
+ jekyll-redirect-from (0.11.0)
+ jekyll (>= 2.0)
+ jekyll-relative-links (0.2.1)
+ jekyll (~> 3.3)
+ jekyll-sass-converter (1.3.0)
+ sass (~> 3.2)
+ jekyll-seo-tag (2.1.0)
+ jekyll (~> 3.3)
+ jekyll-sitemap (0.12.0)
+ jekyll (~> 3.3)
+ jekyll-swiss (0.4.0)
+ jekyll-watch (1.5.1)
+ listen (~> 3.0)
+ jemoji (0.7.0)
+ activesupport (~> 4.0)
+ gemoji (~> 2.0)
+ html-pipeline (~> 2.2)
+ jekyll (>= 3.0)
+ json (2.1.0)
+ kramdown (1.11.1)
+ liquid (3.0.6)
+ listen (3.0.6)
+ rb-fsevent (>= 0.9.3)
+ rb-inotify (>= 0.9.7)
+ mercenary (0.3.6)
+ mini_portile2 (2.4.0)
+ minima (2.0.0)
+ minitest (5.11.3)
+ multipart-post (2.0.0)
+ net-dns (0.9.0)
+ nokogiri (1.10.1)
+ mini_portile2 (~> 2.4.0)
+ octokit (4.13.0)
+ sawyer (~> 0.8.0, >= 0.5.3)
+ pathutil (0.16.2)
+ forwardable-extended (~> 2.6)
+ public_suffix (1.5.3)
+ rb-fsevent (0.10.3)
+ rb-inotify (0.10.0)
+ ffi (~> 1.0)
+ rouge (1.11.1)
+ safe_yaml (1.0.4)
+ sass (3.7.3)
+ sass-listen (~> 4.0.0)
+ sass-listen (4.0.0)
+ rb-fsevent (~> 0.9, >= 0.9.4)
+ rb-inotify (~> 0.9, >= 0.9.7)
+ sawyer (0.8.1)
+ addressable (>= 2.3.5, < 2.6)
+ faraday (~> 0.8, < 1.0)
+ terminal-table (1.8.0)
+ unicode-display_width (~> 1.1, >= 1.1.1)
+ thread_safe (0.3.6)
+ typhoeus (0.8.0)
+ ethon (>= 0.8.0)
+ tzinfo (1.2.5)
+ thread_safe (~> 0.1)
+ unicode-display_width (1.4.1)
+
+PLATFORMS
+ ruby
+
+DEPENDENCIES
+ github-pages (~> 106)
+ jekyll (= 3.3.1)
+ jekyll-feed (~> 0.6)
+
+BUNDLED WITH
+ 1.14.3
diff --git a/content/admin_guide.html b/content/admin_guide.html
new file mode 100644
index 0000000..72e5af4
--- /dev/null
+++ b/content/admin_guide.html
@@ -0,0 +1,804 @@
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+ <h1 class="post-title-main">Admin Guide</h1>
+</div>
+
+
+
+<div class="post-content">
+
+
+ <div class="summary">This section offers an overview of tools available to operate an ecosystem of Hudi datasets</div>
+
+
+
+
+
+
+
+ <p>Admins/ops can gain visibility into Hudi datasets/pipelines in the following ways</p>
+
+<ul>
+ <li>Administering via the Admin CLI</li>
+ <li>Graphite metrics</li>
+ <li>Spark UI of the Hudi Application</li>
+</ul>
+
+<p>This section provides a glimpse into each of these, with some general guidance on troubleshooting</p>
+
+<h2 id="admin-cli">Admin CLI</h2>
+
+<p>Once hoodie has been built via <code class="highlighter-rouge">mvn clean install -DskipTests</code>, the shell can be fired by via <code class="highlighter-rouge">cd hoodie-cli && ./hoodie-cli.sh</code>.
+A hoodie dataset resides on HDFS, in a location referred to as the <strong>basePath</strong> and we would need this location in order to connect to a Hoodie dataset.
+Hoodie library effectively manages this HDFS dataset internally, using .hoodie subfolder to track all metadata</p>
+
+<p>To initialize a hoodie table, use the following command.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>18/09/06 15:56:52 INFO annotation.AutowiredAnnotationBeanPostProcessor: JSR-330 'javax.inject.Inject' annotation found and supported for autowiring
+============================================
+* *
+* _ _ _ _ *
+* | | | | | (_) *
+* | |__| | ___ ___ __| |_ ___ *
+* | __ |/ _ \ / _ \ / _` | |/ _ \ *
+* | | | | (_) | (_) | (_| | | __/ *
+* |_| |_|\___/ \___/ \__,_|_|\___| *
+* *
+============================================
+
+Welcome to Hoodie CLI. Please type help if you are looking for help.
+hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1 --tableType COPY_ON_WRITE
+.....
+18/09/06 15:57:15 INFO table.HoodieTableMetaClient: Finished Loading Table of type COPY_ON_WRITE from ...
+</code></pre>
+</div>
+
+<p>To see the description of hoodie table, use the command:
+<code class="highlighter-rouge">
+hoodie:hoodie_table_1->desc
+18/09/06 15:57:19 INFO timeline.HoodieActiveTimeline: Loaded instants []
+ _________________________________________________________
+ | Property | Value |
+ |========================================================|
+ | basePath | ... |
+ | metaPath | ... |
+ | fileSystem | hdfs |
+ | hoodie.table.name | hoodie_table_1 |
+ | hoodie.table.type | COPY_ON_WRITE |
+ | hoodie.archivelog.folder| |
+</code></p>
+
+<p>Following is a sample command to connect to a Hoodie dataset contains uber trips.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->connect --path /app/uber/trips
+
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: Attempting to load the commits under /app/uber/trips/.hoodie with suffix .commit
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: Attempting to load the commits under /app/uber/trips/.hoodie with suffix .inflight
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: All commits :HoodieCommits{commitList=[20161002045850, 20161002052915, 20161002055918, 20161002065317, 20161002075932, 20161002082904, 20161002085949, 20161002092936, 20161002105903, 20161002112938, 20161002123005, 20161002133002, 20161002155940, 20161002165924, 20161002172907, 20161002175905, 20161002190016, 20161002192954, 20161002195925, 20161002205935, 20161002215928, 20161002222938, 20161002225915, 20161002232906, 20161003003028, 201 [...]
+Metadata for table trips loaded
+hoodie:trips->
+</code></pre>
+</div>
+
+<p>Once connected to the dataset, a lot of other commands become available. The shell has contextual autocomplete help (press TAB) and below is a list of all commands, few of which are reviewed in this section
+are reviewed</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->help
+* ! - Allows execution of operating system (OS) commands
+* // - Inline comment markers (start of line only)
+* ; - Inline comment markers (start of line only)
+* addpartitionmeta - Add partition metadata to a dataset, if not present
+* clear - Clears the console
+* cls - Clears the console
+* commit rollback - Rollback a commit
+* commits compare - Compare commits with another Hoodie dataset
+* commit showfiles - Show file level details of a commit
+* commit showpartitions - Show partition level details of a commit
+* commits refresh - Refresh the commits
+* commits show - Show the commits
+* commits sync - Compare commits with another Hoodie dataset
+* connect - Connect to a hoodie dataset
+* date - Displays the local date and time
+* exit - Exits the shell
+* help - List all commands usage
+* quit - Exits the shell
+* records deduplicate - De-duplicate a partition path contains duplicates & produce repaired files to replace with
+* script - Parses the specified resource file and executes its commands
+* stats filesizes - File Sizes. Display summary stats on sizes of files
+* stats wa - Write Amplification. Ratio of how many records were upserted to how many records were actually written
+* sync validate - Validate the sync by counting the number of records
+* system properties - Shows the shell's properties
+* utils loadClass - Load a class
+* version - Displays shell version
+
+hoodie:trips->
+</code></pre>
+</div>
+
+<h4 id="inspecting-commits">Inspecting Commits</h4>
+
+<p>The task of upserting or inserting a batch of incoming records is known as a <strong>commit</strong> in Hoodie. A commit provides basic atomicity guarantees such that only commited data is available for querying.
+Each commit has a monotonically increasing string/number called the <strong>commit number</strong>. Typically, this is the time at which we started the commit.</p>
+
+<p>To view some basic information about the last 10 commits,</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->commits show --sortBy "Total Bytes Written" --desc true --limit 10
+ ________________________________________________________________________________________________________________________________________________________________________
+ | CommitTime | Total Bytes Written| Total Files Added| Total Files Updated| Total Partitions Written| Total Records Written| Total Update Records Written| Total Errors|
+ |=======================================================================================================================================================================|
+ ....
+ ....
+ ....
+hoodie:trips->
+
+</code></pre>
+</div>
+
+<p>At the start of each write, Hoodie also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>$ hdfs dfs -ls /app/uber/trips/.hoodie/*.inflight
+-rw-r--r-- 3 vinoth supergroup 321984 2016-10-05 23:18 /app/uber/trips/.hoodie/20161005225920.inflight
+</code></pre>
+</div>
+
+<h4 id="drilling-down-to-a-specific-commit">Drilling Down to a specific Commit</h4>
+
+<p>To understand how the writes spread across specific partiions,</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->commit showpartitions --commit 20161005165855 --sortBy "Total Bytes Written" --desc true --limit 10
+ __________________________________________________________________________________________________________________________________________
+ | Partition Path| Total Files Added| Total Files Updated| Total Records Inserted| Total Records Updated| Total Bytes Written| Total Errors|
+ |=========================================================================================================================================|
+ ....
+ ....
+</code></pre>
+</div>
+
+<p>If you need file level granularity , we can do the following</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->commit showfiles --commit 20161005165855 --sortBy "Partition Path"
+ ________________________________________________________________________________________________________________________________________________________
+ | Partition Path| File ID | Previous Commit| Total Records Updated| Total Records Written| Total Bytes Written| Total Errors|
+ |=======================================================================================================================================================|
+ ....
+ ....
+</code></pre>
+</div>
+
+<h4 id="filesystem-view">FileSystem View</h4>
+
+<p>Hudi views each partition as a collection of file-groups with each file-group containing a list of file-slices in commit
+order (See Concepts). The below commands allow users to view the file-slices for a data-set.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code> hoodie:stock_ticks_mor->show fsview all
+ ....
+ _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta File Size| Delta Files |
+ |==============================================================================================================================================================================================================================================================================================================================================================================================================|
+ | 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]|
+
+
+
+ hoodie:stock_ticks_mor->show fsview latest --partitionPath "2018/08/31"
+ ......
+ ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ [...]
+ | Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta Size| Delta Size - compaction scheduled| Delta Size - compaction unscheduled| Delta To Base Ratio - compaction scheduled| Delta To Base Ratio - compaction unscheduled| Delta Files - compaction scheduled | Delta Files - compaction unscheduled|
+ |========================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== [...]
+ | 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | 20.8 KB | 0.0 B | 0.0 B | 0.0 B | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]| [] |
+
+ hoodie:stock_ticks_mor->
+</code></pre>
+</div>
+
+<h4 id="statistics">Statistics</h4>
+
+<p>Since Hoodie directly manages file sizes for HDFS dataset, it might be good to get an overall picture</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->stats filesizes --partitionPath 2016/09/01 --sortBy "95th" --desc true --limit 10
+ ________________________________________________________________________________________________
+ | CommitTime | Min | 10th | 50th | avg | 95th | Max | NumFiles| StdDev |
+ |===============================================================================================|
+ | <COMMIT_ID> | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 2 | 2.3 KB |
+ ....
+ ....
+</code></pre>
+</div>
+
+<p>In case of Hoodie write taking much longer, it might be good to see the write amplification for any sudden increases</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->stats wa
+ __________________________________________________________________________
+ | CommitTime | Total Upserted| Total Written| Write Amplifiation Factor|
+ |=========================================================================|
+ ....
+ ....
+</code></pre>
+</div>
+
+<h4 id="archived-commits">Archived Commits</h4>
+
+<p>In order to limit the amount of growth of .commit files on HDFS, Hoodie archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
+This is a sequence file that contains a mapping from commitNumber => json with raw information about the commit (same that is nicely rolled up above).</p>
+
+<h4 id="compactions">Compactions</h4>
+
+<p>To get an idea of the lag between compaction and writer applications, use the below command to list down all
+pending compactions.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->compactions show all
+ ___________________________________________________________________
+ | Compaction Instant Time| State | Total FileIds to be Compacted|
+ |==================================================================|
+ | <INSTANT_1> | REQUESTED| 35 |
+ | <INSTANT_2> | INFLIGHT | 27 |
+
+</code></pre>
+</div>
+
+<p>To inspect a specific compaction plan, use</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->compaction show --instant <INSTANT_1>
+ _________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | Partition Path| File Id | Base Instant | Data File Path | Total Delta Files| getMetrics |
+ |================================================================================================================================================================================================================================================
+ | 2018/07/17 | <UUID> | <INSTANT_1> | viewfs://ns-default/.../../UUID_<INSTANT>.parquet | 1 | {TOTAL_LOG_FILES=1.0, TOTAL_IO_READ_MB=1230.0, TOTAL_LOG_FILES_SIZE=2.51255751E8, TOTAL_IO_WRITE_MB=991.0, TOTAL_IO_MB=2221.0}|
+
+</code></pre>
+</div>
+
+<p>To manually schedule or run a compaction, use the below command. This command uses spark launcher to perform compaction
+operations. NOTE : Make sure no other application is scheduling compaction for this dataset concurrently</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->help compaction schedule
+Keyword: compaction schedule
+Description: Schedule Compaction
+ Keyword: sparkMemory
+ Help: Spark executor memory
+ Mandatory: false
+ Default if specified: '__NULL__'
+ Default if unspecified: '1G'
+
+* compaction schedule - Schedule Compaction
+</code></pre>
+</div>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->help compaction run
+Keyword: compaction run
+Description: Run Compaction for given instant time
+ Keyword: tableName
+ Help: Table name
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: parallelism
+ Help: Parallelism for hoodie compaction
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: schemaFilePath
+ Help: Path for Avro schema file
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: sparkMemory
+ Help: Spark executor memory
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: retry
+ Help: Number of retries
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: compactionInstant
+ Help: Base path for the target hoodie dataset
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+* compaction run - Run Compaction for given instant time
+</code></pre>
+</div>
+
+<h5 id="validate-compaction">Validate Compaction</h5>
+
+<p>Validating a compaction plan : Check if all the files necessary for compactions are present and are valid</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:stock_ticks_mor->compaction validate --instant 20181005222611
+...
+
+ COMPACTION PLAN VALID
+
+ ___________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error|
+ |==========================================================================================================================================================================================================================|
+ | 05320e98-9a57-4c38-b809-a6beaaeb36bd| 20181005222445 | hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/05320e98-9a57-4c38-b809-a6beaaeb36bd_0_20181005222445.parquet| 1 | true | |
+
+
+
+hoodie:stock_ticks_mor->compaction validate --instant 20181005222601
+
+ COMPACTION PLAN INVALID
+
+ _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error |
+ |=====================================================================================================================================================================================================================================================================================================|
+ | 05320e98-9a57-4c38-b809-a6beaaeb36bd| 20181005222445 | hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/05320e98-9a57-4c38-b809-a6beaaeb36bd_0_20181005222445.parquet| 1 | false| All log files specified in compaction operation is not present. Missing .... |
+
+
+</code></pre>
+</div>
+
+<h5 id="note">NOTE</h5>
+
+<p>The following commands must be executed without any other writer/ingestion application running.</p>
+
+<p>Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
+operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
+so that are preserved. Hudi provides the following CLI to support it</p>
+
+<h5 id="unscheduling-compaction">UnScheduling Compaction</h5>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->compaction unscheduleFileId --fileId <FileUUID>
+....
+No File renames needed to unschedule file from pending compaction. Operation successful.
+
+</code></pre>
+</div>
+
+<p>In other cases, an entire compaction plan needs to be reverted. This is supported by the following CLI
+<code class="highlighter-rouge">
+hoodie:trips->compaction unschedule --compactionInstant <compactionInstant>
+.....
+No File renames needed to unschedule pending compaction. Operation successful.
+</code></p>
+
+<h5 id="repair-compaction">Repair Compaction</h5>
+
+<p>The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
+partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
+<code class="highlighter-rouge">compaction validate</code>, you can notice invalid compaction operations if there is one. In these cases, the repair
+command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
+consistent with the compaction plan</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:stock_ticks_mor->compaction repair --instant 20181005222611
+......
+Compaction successfully repaired
+.....
+</code></pre>
+</div>
+
+<h2 id="metrics">Metrics</h2>
+
+<p>Once the Hoodie Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hoodie datasets</p>
+
+<ul>
+ <li><strong>Commit Duration</strong> - This is amount of time it took to successfully commit a batch of records</li>
+ <li><strong>Rollback Duration</strong> - Similarly, amount of time taken to undo partial data left over by a failed commit (happens everytime automatically after a failing write)</li>
+ <li><strong>File Level metrics</strong> - Shows the amount of new files added, versions, deleted (cleaned) in each commit</li>
+ <li><strong>Record Level Metrics</strong> - Total records inserted/updated etc per commit</li>
+ <li><strong>Partition Level metrics</strong> - number of partitions upserted (super useful to understand sudden spikes in commit duration)</li>
+</ul>
+
+<p>These metrics can then be plotted on a standard tool like grafana. Below is a sample commit duration chart.</p>
+
+<figure><img class="docimage" src="images/hoodie_commit_duration.png" alt="hoodie_commit_duration.png" style="max-width: 1000px" /></figure>
+
+<h2 id="troubleshooting-failures">Troubleshooting Failures</h2>
+
+<p>Section below generally aids in debugging Hoodie failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)</p>
+
+<ul>
+ <li><strong>_hoodie_record_key</strong> - Treated as a primary key within each HDFS partition, basis of all updates/inserts</li>
+ <li><strong>_hoodie_commit_time</strong> - Last commit that touched this record</li>
+ <li><strong>_hoodie_file_name</strong> - Actual file name containing the record (super useful to triage duplicates)</li>
+ <li><strong>_hoodie_partition_path</strong> - Path from basePath that identifies the partition containing this record</li>
+</ul>
+
+<div class="bs-callout bs-callout-warning">Note that as of now, Hoodie assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition</div>
+
+<h4 id="missing-records">Missing records</h4>
+
+<p>Please check if there were any write errors using the admin commands above, during the window at which the record could have been written.
+If you do find errors, then the record was not actually written by Hoodie, but handed back to the application to decide what to do with it.</p>
+
+<h4 id="duplicates">Duplicates</h4>
+
+<p>First of all, please confirm if you do indeed have duplicates <strong>AFTER</strong> ensuring the query is accessing the Hoodie datasets <a href="sql_queries.html">properly</a> .</p>
+
+<ul>
+ <li>If confirmed, please use the metadata fields above, to identify the physical files & partition files containing the records .</li>
+ <li>If duplicates span files across partitionpath, then this means your application is generating different partitionPaths for same recordKey, Please fix your app</li>
+ <li>if duplicates span multiple files within the same partitionpath, please engage with mailing list. This should not happen. You can use the <code class="highlighter-rouge">records deduplicate</code> command to fix your data.</li>
+</ul>
+
+<h4 id="spark-failures">Spark failures</h4>
+
+<p>Typical upsert() DAG looks like below. Note that Hoodie client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
+Also Spark UI shows sortByKey twice due to the probe job also being shown, nonetheless its just a single sort.</p>
+
+<figure><img class="docimage" src="images/hoodie_upsert_dag.png" alt="hoodie_upsert_dag.png" style="max-width: 1000px" /></figure>
+
+<p>At a high level, there are two steps</p>
+
+<p><strong>Index Lookup to identify files to be changed</strong></p>
+
+<ul>
+ <li>Job 1 : Triggers the input data read, converts to HoodieRecord object and then stops at obtaining a spread of input records to target partition paths</li>
+ <li>Job 2 : Load the set of file names which we need check against</li>
+ <li>Job 3 & 4 : Actual lookup after smart sizing of spark join parallelism, by joining RDDs in 1 & 2 above</li>
+ <li>Job 5 : Have a tagged RDD of recordKeys with locations</li>
+</ul>
+
+<p><strong>Performing the actual writing of data</strong></p>
+
+<ul>
+ <li>Job 6 : Lazy join of incoming records against recordKey, location to provide a final set of HoodieRecord which now contain the information about which file/partitionpath they are found at (or null if insert). Then also profile the workload again to determine sizing of files</li>
+ <li>Job 7 : Actual writing of data (update + insert + insert turned to updates to maintain file size)</li>
+</ul>
+
+<p>Depending on the exception source (Hoodie/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/HDFS temporary failures.
+In the future, a more sophisticated debug/management UI would be added to the project, that can help automate some of this debugging.</p>
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+ -->
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+</ul>
+</div>
+
+<!-- this highlights the active parent class in the navgoco sidebar. this is critical so that the parent expands when you're viewing a page. This must appear below the sidebar code above. Otherwise, if placed inside customscripts.js, the script runs before the sidebar code runs and the class never gets inserted.-->
+<script>$("li.active").parents('li').toggleClass("active");</script>
+
+ <!-- Content Column -->
+ <div class="col-md-9">
+ <div class="post-header">
+ <h1 class="post-title-main">API Docs</h1>
+</div>
+
+
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+<div class="post-content">
+
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+<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
+<script>
+$( document ).ready(function() {
+ // Handler for .ready() called.
+
+$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
+
+/* this offset helps account for the space taken up by the floating toolbar. */
+$('#toc').on('click', 'a', function() {
+ var target = $(this.getAttribute('href'))
+ , scroll_target = target.offset().top
+
+ $(window).scrollTop(scroll_target - 10);
+ return false
+})
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new file mode 100644
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+<!DOCTYPE html>
+<head>
+ <meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<title>Code Structure | Hudi</title>
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+ // Initialize navgoco with default options
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+ <script>
+ $(function () {
+ $('[data-toggle="tooltip"]').tooltip()
+ })
+ </script>
+
+
+</head>
+<body>
+<!-- Navigation -->
+
+<nav class="navbar navbar-inverse navbar-fixed-top">
+ <div class="container topnavlinks">
+ <div class="navbar-header">
+ <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
+ <span class="sr-only">Toggle navigation</span>
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+ <span class="icon-bar"></span>
+ </button>
+
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+ <img src="images/hudi_site_logo.png" alt="Hudi logo"/>
+ <!--Hudi-->
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+ </div>
+ <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
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+
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+
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+ <!-- if you aren't using the accordion, uncomment this block:
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+ <a href="#" id="collapseAll">Collapse All</a> | <a href="#" id="expandAll">Expand All</a>
+ </p>
+ -->
+ </li>
+</ul>
+</div>
+
+<!-- this highlights the active parent class in the navgoco sidebar. this is critical so that the parent expands when you're viewing a page. This must appear below the sidebar code above. Otherwise, if placed inside customscripts.js, the script runs before the sidebar code runs and the class never gets inserted.-->
+<script>$("li.active").parents('li').toggleClass("active");</script>
+
+ <!-- Content Column -->
+ <div class="col-md-9">
+ <div class="post-header">
+ <h1 class="post-title-main">Code Structure</h1>
+</div>
+
+
+
+<div class="post-content">
+
+
+
+
+
+<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
+<script>
+$( document ).ready(function() {
+ // Handler for .ready() called.
+
+$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
+
+/* this offset helps account for the space taken up by the floating toolbar. */
+$('#toc').on('click', 'a', function() {
+ var target = $(this.getAttribute('href'))
+ , scroll_target = target.offset().top
+
+ $(window).scrollTop(scroll_target - 10);
+ return false
+})
+
+});
+</script>
+
+<div id="toc"></div>
+
+
+
+
+
+
+ <h2 id="code--project-structure">Code & Project Structure</h2>
+
+<ul>
+ <li>hoodie-client : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table</li>
+ <li>hoodie-common : Common code shared between different artifacts of Hoodie</li>
+</ul>
+
+<p>## HoodieLogFormat</p>
+
+<p>The following diagram depicts the LogFormat for Hoodie MergeOnRead. Each logfile consists of one or more log blocks.
+ Each logblock follows the format shown below.</p>
+
+<table>
+ <thead>
+ <tr>
+ <th>Field</th>
+ <th>Description</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>MAGIC</td>
+ <td>A magic header that marks the start of a block</td>
+ </tr>
+ <tr>
+ <td>VERSION</td>
+ <td>The version of the LogFormat, this helps define how to switch between different log format as it evolves</td>
+ </tr>
+ <tr>
+ <td>TYPE</td>
+ <td>The type of the log block</td>
+ </tr>
+ <tr>
+ <td>HEADER LENGTH</td>
+ <td>The length of the headers, 0 if no headers</td>
+ </tr>
+ <tr>
+ <td>HEADER</td>
+ <td>Metadata needed for a log block. For eg. INSTANT_TIME, TARGET_INSTANT_TIME, SCHEMA etc.</td>
+ </tr>
+ <tr>
+ <td>CONTENT LENGTH</td>
+ <td>The length of the content of the log block</td>
+ </tr>
+ <tr>
+ <td>CONTENT</td>
+ <td>The content of the log block, for example, for a DATA_BLOCK, the content is (number of records + actual records) in byte []</td>
+ </tr>
+ <tr>
+ <td>FOOTER LENGTH</td>
+ <td>The length of the footers, 0 if no footers</td>
+ </tr>
+ <tr>
+ <td>FOOTER</td>
+ <td>Metadata needed for a log block. For eg. index entries, a bloom filter for records in a DATA_BLOCK etc.</td>
+ </tr>
+ <tr>
+ <td>LOGBLOCK LENGTH</td>
+ <td>The total number of bytes written for a log block, typically the SUM(everything_above). This is a LONG. This acts as a reverse pointer to be able to traverse the log in reverse.</td>
+ </tr>
+ </tbody>
+</table>
+
+<figure><img class="docimage" src="images/hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" /></figure>
+
+
+
+ <div class="tags">
+
+ </div>
+
+
+
+</div>
+
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+
+<footer>
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+ </div>
+</footer>
+
+
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+ <!-- /.row -->
+</div>
+<!-- /.container -->
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+
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+
+</html>
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diff --git a/content/community.html b/content/community.html
new file mode 100644
index 0000000..de173be
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@@ -0,0 +1,388 @@
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+<head>
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+<meta http-equiv="X-UA-Compatible" content="IE=edge">
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+<meta name="keywords" content=" usecases">
+<title>Community | Hudi</title>
+<link rel="stylesheet" href="css/syntax.css">
+
+
+<link rel="stylesheet" type="text/css" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css">
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+
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+ // Initialize navgoco with default options
+ $("#mysidebar").navgoco({
+ caretHtml: '',
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+ <script>
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+ })
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+
+
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+<body>
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+<nav class="navbar navbar-inverse navbar-fixed-top">
+ <div class="container topnavlinks">
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+ <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
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+
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+ </ul>
+ </li>
+
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+
+ <li>
+
+
+
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the Community page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+
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+ <!--comment out this block if you want to hide search-->
+ <li>
+ <!--start search-->
+ <div id="search-demo-container">
+ <input type="text" id="search-input" placeholder="search...">
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+ <script type="text/javascript">
+ SimpleJekyllSearch.init({
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+ noResultsText: 'No results found.',
+ limit: 10,
+ fuzzy: true,
+ })
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+</nav>
+
+<!-- Page Content -->
+<div class="container">
+ <div class="col-lg-12"> </div>
+ <!-- Content Row -->
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+<ul id="mysidebar" class="nav">
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+</div>
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+
+
+
+
+
+
+
+
+ <h2 id="contributing">Contributing</h2>
+<p>We :heart: contributions. If you find a bug in the library or would like to add new features, go ahead and open
+issues or pull requests against this repo. Before you do so, please sign the
+<a href="https://www.apache.org/licenses/icla.pdf">Apache CLA</a>.
+Also, be sure to write unit tests for your bug fix or feature to show that it works as expected.
+If the reviewer feels this contributions needs to be in the release notes, please add it to CHANGELOG.md as well.</p>
+
+<p>If you want to participate in day-day conversations, please join our <a href="https://join.slack.com/t/apache-hudi/signup">slack group</a>.
+If you are from select pre-listed email domains, you can self signup. Others, please subscribe to dev@hudi.apache.org</p>
+
+<h2 id="becoming-a-committer">Becoming a Committer</h2>
+
+<p>Hoodie has adopted a lot of guidelines set forth in <a href="https://www.chromium.org/getting-involved/become-a-committer">Google Chromium project</a>, to determine committership proposals. However, given this is a much younger project, we would have the contribution bar to be 10-15 non-trivial patches instead.
+Additionally, we expect active engagement with the community over a few months, in terms of conference/meetup talks, helping out with issues/questions on slack/github.</p>
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+ <div class="post-header">
+ <h1 class="post-title-main">Comparison</h1>
+</div>
+
+
+
+<div class="post-content">
+
+
+
+
+
+
+
+
+ <p>Apache Hudi fills a big void for processing data on top of HDFS, and thus mostly co-exists nicely with these technologies. However,
+it would be useful to understand how Hudi fits into the current big data ecosystem, contrasting it with a few related systems
+and bring out the different tradeoffs these systems have accepted in their design.</p>
+
+<h2 id="kudu">Kudu</h2>
+
+<p><a href="https://kudu.apache.org">Apache Kudu</a> is a storage system that has similar goals as Hudi, which is to bring real-time analytics on petabytes of data via first
+class support for <code class="highlighter-rouge">upserts</code>. A key differentiator is that Kudu also attempts to serve as a datastore for OLTP workloads, something that Hudi does not aspire to be.
+Consequently, Kudu does not support incremental pulling (as of early 2017), something Hudi does to enable incremental processing use cases.</p>
+
+<p>Kudu diverges from a distributed file system abstraction and HDFS altogether, with its own set of storage servers talking to each other via RAFT.
+Hudi, on the other hand, is designed to work with an underlying Hadoop compatible filesystem (HDFS,S3 or Ceph) and does not have its own fleet of storage servers,
+instead relying on Apache Spark to do the heavy-lifting. Thu, Hudi can be scaled easily, just like other Spark jobs, while Kudu would require hardware
+& operational support, typical to datastores like HBase or Vertica. We have not at this point, done any head to head benchmarks against Kudu (given RTTable is WIP).
+But, if we were to go with results shared by <a href="https://db-blog.web.cern.ch/blog/zbigniew-baranowski/2017-01-performance-comparison-different-file-formats-and-storage-engines">CERN</a> ,
+we expect Hudi to positioned at something that ingests parquet with superior performance.</p>
+
+<h2 id="hive-transactions">Hive Transactions</h2>
+
+<p><a href="https://cwiki.apache.org/confluence/display/Hive/Hive+Transactions">Hive Transactions/ACID</a> is another similar effort, which tries to implement storage like
+<code class="highlighter-rouge">merge-on-read</code>, on top of ORC file format. Understandably, this feature is heavily tied to Hive and other efforts like <a href="https://cwiki.apache.org/confluence/display/Hive/LLAP">LLAP</a>.
+Hive transactions does not offer the read-optimized storage option or the incremental pulling, that Hudi does. In terms of implementation choices, Hudi leverages
+the full power of a processing framework like Spark, while Hive transactions feature is implemented underneath by Hive tasks/queries kicked off by user or the Hive metastore.
+Based on our production experience, embedding Hudi as a library into existing Spark pipelines was much easier and less operationally heavy, compared with the other approach.
+Hudi is also designed to work with non-hive enginers like Presto/Spark and will incorporate file formats other than parquet over time.</p>
+
+<h2 id="hbase">HBase</h2>
+
+<p>Even though <a href="https://hbase.apache.org">HBase</a> is ultimately a key-value store for OLTP workloads, users often tend to associate HBase with analytics given the proximity to Hadoop.
+Given HBase is heavily write-optimized, it supports sub-second upserts out-of-box and Hive-on-HBase lets users query that data. However, in terms of actual performance for analytical workloads,
+hybrid columnar storage formats like Parquet/ORC handily beat HBase, since these workloads are predominantly read-heavy. Hudi bridges this gap between faster data and having
+analytical storage formats. From an operational perspective, arming users with a library that provides faster data, is more scalable, than managing a big farm of HBase region servers,
+just for analytics. Finally, HBase does not support incremental processing primitives like <code class="highlighter-rouge">commit times</code>, <code class="highlighter-rouge">incremental pull</code> as first class citizens like Hudi.</p>
+
+<h2 id="stream-processing">Stream Processing</h2>
+
+<p>A popular question, we get is : “How does Hudi relate to stream processing systems?”, which we will try to answer here. Simply put, Hudi can integrate with
+batch (<code class="highlighter-rouge">copy-on-write storage</code>) and streaming (<code class="highlighter-rouge">merge-on-read storage</code>) jobs of today, to store the computed results in Hadoop. For Spark apps, this can happen via direct
+integration of Hudi library with Spark/Spark streaming DAGs. In case of Non-Spark processing systems (eg: Flink, Hive), the processing can be done in the respective systems
+and later sent into a Hudi table via a Kafka topic/HDFS intermediate file. In more conceptual level, data processing
+pipelines just consist of three components : <code class="highlighter-rouge">source</code>, <code class="highlighter-rouge">processing</code>, <code class="highlighter-rouge">sink</code>, with users ultimately running queries against the sink to use the results of the pipeline.
+Hudi can act as either a source or sink, that stores data on HDFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
+of Presto/SparkSQL/Hive for your queries.</p>
+
+<p>More advanced use cases revolve around the concepts of <a href="https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop">incremental processing</a>, which effectively
+uses Hudi even inside the <code class="highlighter-rouge">processing</code> engine to speed up typical batch pipelines. For e.g: Hudi can be used as a state store inside a processing DAG (similar
+to how <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend">rocksDB</a> is used by Flink). This is an item on the roadmap
+and will eventually happen as a <a href="https://github.com/uber/hoodie/issues/8">Beam Runner</a></p>
+
+
+
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diff --git a/content/concepts.html b/content/concepts.html
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+ <h1 class="post-title-main">Concepts</h1>
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+
+
+ <div class="summary">Here we introduce some basic concepts & give a broad technical overview of Hudi</div>
+
+
+
+
+
+
+
+ <p>Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on HDFS</p>
+
+<ul>
+ <li>Upsert (how do I change the dataset?)</li>
+ <li>Incremental consumption (how do I fetch data that changed?)</li>
+</ul>
+
+<p>In order to achieve this, Hudi maintains a <code class="highlighter-rouge">timeline</code> of all activity performed on the dataset, that helps provide <code class="highlighter-rouge">instantaenous</code> views of the dataset,
+while also efficiently supporting retrieval of data in the order of arrival into the dataset.
+Such key activities include</p>
+
+<ul>
+ <li><code class="highlighter-rouge">COMMITS</code> - A single commit captures information about an <strong>atomic write</strong> of a batch of records into a dataset.
+ Commits are identified by a monotonically increasing timestamp, denoting the start of the write operation.</li>
+ <li><code class="highlighter-rouge">CLEANS</code> - Background activity that gets rid of older versions of files in the dataset, that are no longer needed.</li>
+ <li><code class="highlighter-rouge">DELTA_COMMITS</code> - A single commit captures information about an <strong>atomic write</strong> of a batch of records into a
+ MergeOnRead storage type of dataset</li>
+ <li><code class="highlighter-rouge">COMPACTIONS</code> - Background activity to reconcile differential data structures within Hudi e.g: moving updates from row based log files to columnar formats.</li>
+</ul>
+
+<figure><img class="docimage" src="images/Hudi_timeline.png" alt="Hudi_timeline.png" /></figure>
+
+<p>Example above shows upserts happenings between 10:00 and 10:20 on a Hudi dataset, roughly every 5 mins, leaving commit metadata on the Hudi timeline, along
+with other background cleaning/compactions. One key observation to make is that the commit time indicates the <code class="highlighter-rouge">arrival time</code> of the data (10:20AM), while the actual data
+organization reflects the actual time or <code class="highlighter-rouge">event time</code>, the data was intended for (hourly buckets from 07:00). These are two key concepts when reasoning about tradeoffs between latency and completeness of data.</p>
+
+<p>When there is late arriving data (data intended for 9:00 arriving >1 hr late at 10:20), we can see the upsert producing new data into even older time buckets/folders.
+With the help of the timeline, an incremental query attempting to get all new data that was committed successfully since 10:00 hours, is able to very efficiently consume
+only the changed files without say scanning all the time buckets > 07:00.</p>
+
+<h2 id="terminologies">Terminologies</h2>
+
+<ul>
+ <li><code class="highlighter-rouge">Hudi Dataset</code>
+ A structured hive/spark dataset managed by Hudi. Hudi supports both partitioned and non-partitioned Hive tables.</li>
+ <li><code class="highlighter-rouge">Commit</code>
+ A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
+ published.</li>
+ <li><code class="highlighter-rouge">Commit Timeline</code>
+ Commit Timeline refers to the sequence of Commits that was applied in order on a dataset over its lifetime.</li>
+ <li><code class="highlighter-rouge">File Slice</code>
+ Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
+ Hudi uses MVCC to provide atomicity and isolation of readers from a writer. This means that a logical fileId will
+ have many physical versions of it. Each of these physical version of a file represents a complete view of the
+ file as of a commit and is called File Slice</li>
+ <li><code class="highlighter-rouge">File Group</code>
+ A file-group is a file-slice timeline. It is a list of file-slices in commit order. It is identified by <code class="highlighter-rouge">file id</code></li>
+</ul>
+
+<h2 id="storage-types">Storage Types</h2>
+
+<p>Hudi storage types capture how data is indexed & laid out on the filesystem, and how the above primitives and timeline activities are implemented on top of
+such organization (i.e how data is written). This is not to be confused with the notion of Read Optimized & Near-Real time tables, which are merely how the underlying data is exposed
+to the queries (i.e how data is read).</p>
+
+<p>Hudi (will) supports the following storage types.</p>
+
+<table>
+ <thead>
+ <tr>
+ <th>Storage Type</th>
+ <th>Supported Tables</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>Copy On Write</td>
+ <td>Read Optimized</td>
+ </tr>
+ <tr>
+ <td>Merge On Read</td>
+ <td>Read Optimized + Near Real-time</td>
+ </tr>
+ </tbody>
+</table>
+
+<ul>
+ <li>Copy On Write : A heavily read optimized storage type, that simply creates new versions of files corresponding to the records that changed.</li>
+ <li>Merge On Read : Also provides a near-real time datasets in the order of 5 mins, by shifting some of the write cost, to the reads and merging incoming and on-disk data on-the-fly</li>
+</ul>
+
+<div class="bs-callout bs-callout-info">Hudi is a young project. merge-on-read is currently underway. Get involved <a href="https://github.com/uber/Hudi/projects/1">here</a></div>
+
+<p>Regardless of the storage type, Hudi organizes a datasets into a directory structure under a <code class="highlighter-rouge">basepath</code>,
+very similar to Hive tables. Dataset is broken up into partitions, which are folders containing files for that partition.
+Each partition uniquely identified by its <code class="highlighter-rouge">partitionpath</code>, which is relative to the basepath.</p>
+
+<p>Within each partition, records are distributed into multiple files. Each file is identified by an unique <code class="highlighter-rouge">file id</code> and the <code class="highlighter-rouge">commit</code> that
+produced the file. Multiple files can share the same file id but written at different commits, in case of updates.</p>
+
+<p>Each record is uniquely identified by a <code class="highlighter-rouge">record key</code> and mapped to a file id forever. This mapping between record key
+and file id, never changes once the first version of a record has been written to a file. In short, the
+ <code class="highlighter-rouge">file id</code> identifies a group of files, that contain all versions of a group of records.</p>
+
+<h2 id="copy-on-write">Copy On Write</h2>
+
+<p>As mentioned above, each commit on Copy On Write storage, produces new versions of files. In other words, we implicitly compact every
+commit, such that only columnar data exists. As a result, the write amplification (number of bytes written for 1 byte of incoming data)
+ is much higher, where read amplification is close to zero. This is a much desired property for a system like Hadoop, which is predominantly read-heavy.</p>
+
+<p>Following illustrates how this works conceptually, when data written into copy-on-write storage and two queries running on top of it.</p>
+
+<figure><img class="docimage" src="images/Hudi_cow.png" alt="Hudi_cow.png" /></figure>
+
+<p>As data gets written, updates to existing file ids, produce a new version for that file id stamped with the commit and
+inserts allocate a new file id and write its first version for that file id. These file versions and their commits are color coded above.
+Normal SQL queries running against such dataset (eg: select count(*) counting the total records in that partition), first checks the timeline for latest commit
+and filters all but latest versions of each file id. As you can see, an old query does not see the current inflight commit’s files colored in pink,
+but a new query starting after the commit picks up the new data. Thus queries are immune to any write failures/partial writes and only run on committed data.</p>
+
+<p>The intention of copy on write storage, is to fundamentally improve how datasets are managed today on Hadoop through</p>
+
+<ul>
+ <li>First class support for atomically updating data at file-level, instead of rewriting whole tables/partitions</li>
+ <li>Ability to incremental consume changes, as opposed to wasteful scans or fumbling with heuristical approaches</li>
+ <li>Tight control file sizes to keep query performance excellent (small files hurt query performance considerably).</li>
+</ul>
+
+<h2 id="merge-on-read">Merge On Read</h2>
+
+<p>Merge on read storage is a superset of copy on write, in the sense it still provides a read optimized view of the dataset via the Read Optmized table.
+But, additionally stores incoming upserts for each file id, onto a <code class="highlighter-rouge">row based append log</code>, that enables providing near real-time data to the queries
+ by applying the append log, onto the latest version of each file id on-the-fly during query time. Thus, this storage type attempts to balance read and write amplication intelligently, to provide near real-time queries.
+The most significant change here, would be to the compactor, which now carefully chooses which append logs need to be compacted onto
+their columnar base data, to keep the query performance in check (larger append logs would incur longer merge times with merge data on query side)</p>
+
+<p>Following illustrates how the storage works, and shows queries on both near-real time table and read optimized table.</p>
+
+<figure><img class="docimage" src="images/Hudi_mor.png" alt="Hudi_mor.png" style="max-width: 1000px" /></figure>
+
+<p>There are lot of interesting things happening in this example, which bring out the subleties in the approach.</p>
+
+<ul>
+ <li>We now have commits every 1 minute or so, something we could not do in the other storage type.</li>
+ <li>Within each file id group, now there is an append log, which holds incoming updates to records in the base columnar files. In the example, the append logs hold
+ all the data from 10:05 to 10:10. The base columnar files are still versioned with the commit, as before.
+ Thus, if one were to simply look at base files alone, then the storage layout looks exactly like a copy on write table.</li>
+ <li>A periodic compaction process reconciles these changes from the append log and produces a new version of base file, just like what happened at 10:05 in the example.</li>
+ <li>There are two ways of querying the same underlying storage: ReadOptimized (RO) Table and Near-Realtime (RT) table, depending on whether we chose query performance or freshness of data.</li>
+ <li>The semantics around when data from a commit is available to a query changes in a subtle way for the RO table. Note, that such a query
+ running at 10:10, wont see data after 10:05 above, while a query on the RT table always sees the freshest data.</li>
+ <li>When we trigger compaction & what it decides to compact hold all the key to solving these hard problems. By implementing a compacting
+ strategy, where we aggressively compact the latest partitions compared to older partitions, we could ensure the RO Table sees data
+ published within X minutes in a consistent fashion.</li>
+</ul>
+
+<div class="bs-callout bs-callout-info">Hudi is a young project. merge-on-read is currently underway. Get involved <a href="https://github.com/uber/hoodie/projects/1">here</a></div>
+
+<p>The intention of merge on read storage, is to enable near real-time processing directly on top of Hadoop, as opposed to copying
+data out to specialized systems, which may not be able to handle the data volume.</p>
+
+<h2 id="trade-offs-when-choosing-different-storage-types-and-views">Trade offs when choosing different storage types and views</h2>
+
+<h3 id="storage-types-1">Storage Types</h3>
+
+<table>
+ <thead>
+ <tr>
+ <th>Trade-off</th>
+ <th>CopyOnWrite</th>
+ <th>MergeOnRead</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>Data Latency</td>
+ <td>Higher</td>
+ <td>Lower</td>
+ </tr>
+ <tr>
+ <td>Update cost (I/O)</td>
+ <td>Higher (rewrite entire parquet)</td>
+ <td>Lower (append to delta file)</td>
+ </tr>
+ <tr>
+ <td>Parquet File Size</td>
+ <td>Smaller (high update(I/0) cost)</td>
+ <td>Larger (low update cost)</td>
+ </tr>
+ <tr>
+ <td>Write Amplification</td>
+ <td>Higher</td>
+ <td>Lower (depending on compaction strategy)</td>
+ </tr>
+ </tbody>
+</table>
+
+<h3 id="hudi-views">Hudi Views</h3>
+
+<table>
+ <thead>
+ <tr>
+ <th>Trade-off</th>
+ <th>ReadOptimized</th>
+ <th>RealTime</th>
+ </tr>
+ </thead>
+ <tbody>
+ <tr>
+ <td>Data Latency</td>
+ <td>Higher</td>
+ <td>Lower</td>
+ </tr>
+ <tr>
+ <td>Query Latency</td>
+ <td>Lower (raw columnar performance)</td>
+ <td>Higher (merge columnar + row based delta)</td>
+ </tr>
+ </tbody>
+</table>
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+ <div class="post-header">
+ <h1 class="post-title-main">Configurations</h1>
+</div>
+
+
+
+<div class="post-content">
+
+
+ <div class="summary">Here we list all possible configurations and what they mean</div>
+
+
+
+
+
+
+
+ <h3 id="configuration">Configuration</h3>
+
+<ul>
+ <li><a href="#HoodieWriteConfig">HoodieWriteConfig</a> <br />
+<span style="color:grey">Top Level Config which is passed in when HoodieWriteClent is created.</span>
+ <ul>
+ <li><a href="#withPath">withPath</a> (hoodie_base_path) <br />
+ <span style="color:grey">Base HDFS path under which all the data partitions are created. Hoodie stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span></li>
+ <li><a href="#withSchema">withSchema</a> (schema_str) <br />
+ <span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span></li>
+ <li><a href="#withParallelism">withParallelism</a> (insert_shuffle_parallelism = 200, upsert_shuffle_parallelism = 200) <br />
+ <span style="color:grey">Insert DAG uses the insert_parallelism in every shuffle. Upsert DAG uses the upsert_parallelism in every shuffle. Typical workload is profiled and once a min parallelism is established, trade off between latency and cluster usage optimizations this is tuned and have a conservatively high number to optimize for latency and </span></li>
+ <li><a href="#combineInput">combineInput</a> (on_insert = false, on_update=true) <br />
+ <span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span></li>
+ <li><a href="#withWriteStatusStorageLevel">withWriteStatusStorageLevel</a> (level = MEMORY_AND_DISK_SER) <br />
+ <span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span></li>
+ <li><a href="#withAutoCommit">withAutoCommit</a> (autoCommit = true) <br />
+ <span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a “defined success condition”</span></li>
+ <li><a href="#withAssumeDatePartitioning">withAssumeDatePartitioning</a> (assumeDatePartitioning = false) <br />
+ <span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span></li>
+ <li>
+ <p><a href="#withConsistencyCheckEnabled">withConsistencyCheckEnabled</a> (enabled = false) <br />
+ <span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files’ are listable on the underlying filesystem/storage. Set this to true, to workaround S3’s eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span></p>
+ </li>
+ <li><a href="#withIndexConfig">withIndexConfig</a> (HoodieIndexConfig) <br />
+ <span style="color:grey">Hoodie uses a index to help find the FileID which contains an incoming record key. This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
+ <ul>
+ <li><a href="#withIndexType">withIndexType</a> (indexType = BLOOM) <br />
+ <span style="color:grey">Type of index to use. Default is Bloom filter. Possible options are [BLOOM | HBASE | INMEMORY]. Bloom filters removes the dependency on a external system and is stored in the footer of the Parquet Data Files</span></li>
+ <li><a href="#bloomFilterNumEntries">bloomFilterNumEntries</a> (60000) <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br />This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. <a href="https://github.com/uber/hoodie/issues/70">#70</a> tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positives and in [...]
+ <li><a href="#bloomFilterFPP">bloomFilterFPP</a> (0.000000001) <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br /> Error rate allowed given the number of entries. This is used to calculate how many bits should be assigned for the bloom filter and the number of hash functions. This is usually set very low (default: 0.000000001), we like to tradeoff disk space for lower false positives</span></li>
+ <li><a href="#bloomIndexPruneByRanges">bloomIndexPruneByRanges</a> (true) <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br /> When true, range information from files to leveraged speed up index lookups. Particularly helpful, if the key has a monotonously increasing prefix, such as timestamp.</span></li>
+ <li><a href="#bloomIndexUseCaching">bloomIndexUseCaching</a> (true) <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br /> When true, the input RDD will cached to speed up index lookup by reducing IO for computing parallelism or affected partitions</span></li>
+ <li><a href="#bloomIndexParallelism">bloomIndexParallelism</a> (0) <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br /> This is the amount of parallelism for index lookup, which involves a Spark Shuffle. By default, this is auto computed based on input workload characteristics</span></li>
+ <li><a href="#hbaseZkQuorum">hbaseZkQuorum</a> (zkString) <br />
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum url to connect to.</span></li>
+ <li><a href="#hbaseZkPort">hbaseZkPort</a> (port) <br />
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span></li>
+ <li><a href="#hbaseTableName">hbaseTableName</a> (tableName) <br />
+ <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span></li>
+ </ul>
+ </li>
+ <li><a href="#withStorageConfig">withStorageConfig</a> (HoodieStorageConfig) <br />
+ <span style="color:grey">Storage related configs</span>
+ <ul>
+ <li><a href="#limitFileSize">limitFileSize</a> (size = 120MB) <br />
+ <span style="color:grey">Hoodie re-writes a single file during update (copy_on_write) or a compaction (merge_on_read). This is fundamental unit of parallelism. It is important that this is aligned with the underlying filesystem block size. </span></li>
+ <li><a href="#parquetBlockSize">parquetBlockSize</a> (rowgroupsize = 120MB) <br />
+ <span style="color:grey">Parquet RowGroup size. Its better than this is aligned with the file size, so that a single column within a file is stored continuously on disk</span></li>
+ <li><a href="#parquetPageSize">parquetPageSize</a> (pagesize = 1MB) <br />
+ <span style="color:grey">Parquet page size. Page is the unit of read within a parquet file. Within a block, pages are compressed seperately. </span></li>
+ <li><a href="#logFileMaxSize">logFileMaxSize</a> (logFileSize = 1GB) <br />
+ <span style="color:grey">LogFile max size. This is the maximum size allowed for a log file before it is rolled over to the next version. </span></li>
+ <li><a href="#logFileDataBlockMaxSize">logFileDataBlockMaxSize</a> (dataBlockSize = 256MB) <br />
+ <span style="color:grey">LogFile Data block max size. This is the maximum size allowed for a single data block to be appended to a log file. This helps to make sure the data appended to the log file is broken up into sizable blocks to prevent from OOM errors. This size should be greater than the JVM memory. </span></li>
+ </ul>
+ </li>
+ <li><a href="#withCompactionConfig">withCompactionConfig</a> (HoodieCompactionConfig) <br />
+ <span style="color:grey">Cleaning and configurations related to compaction techniques</span>
+ <ul>
+ <li><a href="#withCleanerPolicy">withCleanerPolicy</a> (policy = KEEP_LATEST_COMMITS) <br />
+ <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span></li>
+ <li><a href="#retainCommits">retainCommits</a> (no_of_commits_to_retain = 24) <br />
+ <span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span></li>
+ <li><a href="#archiveCommitsWith">archiveCommitsWith</a> (minCommits = 96, maxCommits = 128) <br />
+ <span style="color:grey">Each commit is a small file in the .hoodie directory. Since HDFS is not designed to handle multiple small files, hoodie archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span></li>
+ <li><a href="#compactionSmallFileSize">compactionSmallFileSize</a> (size = 0) <br />
+ <span style="color:grey">Small files can always happen because of the number of insert records in a paritition in a batch. Hoodie has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a “small file size”. This should be less < maxFileSize and setting it to 0, turns off this feature. </span></li>
+ <li><a href="#insertSplitSize">insertSplitSize</a> (size = 500000) <br />
+ <span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span></li>
+ <li><a href="#autoTuneInsertSplits">autoTuneInsertSplits</a> (true) <br />
+ <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit’s metadata. Turned off by default. </span></li>
+ <li><a href="#approxRecordSize">approxRecordSize</a> () <br />
+ <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit’s metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span></li>
+ <li><a href="#withCompactionLazyBlockReadEnabled">withCompactionLazyBlockReadEnabled</a> (true) <br />
+ <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span></li>
+ <li><a href="#withMaxNumDeltaCommitsBeforeCompaction">withMaxNumDeltaCommitsBeforeCompaction</a> (maxNumDeltaCommitsBeforeCompaction = 10) <br />
+ <span style="color:grey">Number of max delta commits to keep before triggering an inline compaction</span></li>
+ <li><a href="#withCompactionReverseLogReadEnabled">withCompactionReverseLogReadEnabled</a> (false) <br />
+ <span style="color:grey">HoodieLogFormatReader reads a logfile in the forward direction starting from pos=0 to pos=file_length. If this config is set to true, the Reader reads the logfile in reverse direction, from pos=file_length to pos=0</span></li>
+ </ul>
+ </li>
+ <li><a href="#withMetricsConfig">withMetricsConfig</a> (HoodieMetricsConfig) <br />
+ <span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
+ <ul>
+ <li><a href="#on">on</a> (true) <br />
+ <span style="color:grey">Turn sending metrics on/off. on by default.</span></li>
+ <li><a href="#withReporterType">withReporterType</a> (GRAPHITE) <br />
+ <span style="color:grey">Type of metrics reporter. Graphite is the default and the only value suppported.</span></li>
+ <li><a href="#toGraphiteHost">toGraphiteHost</a> () <br />
+ <span style="color:grey">Graphite host to connect to</span></li>
+ <li><a href="#onGraphitePort">onGraphitePort</a> () <br />
+ <span style="color:grey">Graphite port to connect to</span></li>
+ <li><a href="#usePrefix">usePrefix</a> () <br />
+ <span style="color:grey">Standard prefix for all metrics</span></li>
+ </ul>
+ </li>
+ <li><a href="#withMemoryConfig">withMemoryConfig</a> (HoodieMemoryConfig) <br />
+ <span style="color:grey">Memory related configs</span>
+ <ul>
+ <li><a href="#withMaxMemoryFractionPerPartitionMerge">withMaxMemoryFractionPerPartitionMerge</a> (maxMemoryFractionPerPartitionMerge = 0.6) <br />
+ <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span></li>
+ <li><a href="#withMaxMemorySizePerCompactionInBytes">withMaxMemorySizePerCompactionInBytes</a> (maxMemorySizePerCompactionInBytes = 1GB) <br />
+ <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span></li>
+ </ul>
+ </li>
+ <li>
+ <p><a href="s3_hoodie.html">S3Configs</a> (Hoodie S3 Configs) <br />
+ <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span></p>
+ </li>
+ <li><a href="gcs_hoodie.html">GCSConfigs</a> (Hoodie GCS Configs) <br />
+ <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span></li>
+ </ul>
+ </li>
+ <li><a href="#datasource">Hoodie Datasource</a> <br />
+<span style="color:grey">Configs for datasource</span>
+ <ul>
+ <li><a href="#writeoptions">write options</a> (write.format.option(…)) <br />
+ <span style="color:grey"> Options useful for writing datasets </span>
+ <ul>
+ <li><a href="#OPERATION_OPT_KEY">OPERATION_OPT_KEY</a> (Default: upsert) <br />
+ <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span></li>
+ <li><a href="#STORAGE_TYPE_OPT_KEY">STORAGE_TYPE_OPT_KEY</a> (Default: COPY_ON_WRITE) <br />
+ <span style="color:grey">The storage type for the underlying data, for this write. This can’t change between writes.</span></li>
+ <li><a href="#TABLE_NAME_OPT_KEY">TABLE_NAME_OPT_KEY</a> (Default: None (mandatory)) <br />
+ <span style="color:grey">Hive table name, to register the dataset into.</span></li>
+ <li><a href="#PRECOMBINE_FIELD_OPT_KEY">PRECOMBINE_FIELD_OPT_KEY</a> (Default: ts) <br />
+ <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
+ we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span></li>
+ <li><a href="#PAYLOAD_CLASS_OPT_KEY">PAYLOAD_CLASS_OPT_KEY</a> (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br />
+ <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
+ This will render any value set for <code class="highlighter-rouge">PRECOMBINE_FIELD_OPT_VAL</code> in-effective</span></li>
+ <li><a href="#RECORDKEY_FIELD_OPT_KEY">RECORDKEY_FIELD_OPT_KEY</a> (Default: uuid) <br />
+ <span style="color:grey">Record key field. Value to be used as the <code class="highlighter-rouge">recordKey</code> component of <code class="highlighter-rouge">HoodieKey</code>. Actual value
+ will be obtained by invoking .toString() on the field value. Nested fields can be specified using
+ the dot notation eg: <code class="highlighter-rouge">a.b.c</code></span></li>
+ <li><a href="#PARTITIONPATH_FIELD_OPT_KEY">PARTITIONPATH_FIELD_OPT_KEY</a> (Default: partitionpath) <br />
+ <span style="color:grey">Partition path field. Value to be used at the <code class="highlighter-rouge">partitionPath</code> component of <code class="highlighter-rouge">HoodieKey</code>.
+ Actual value ontained by invoking .toString()</span></li>
+ <li><a href="#KEYGENERATOR_CLASS_OPT_KEY">KEYGENERATOR_CLASS_OPT_KEY</a> (Default: com.uber.hoodie.SimpleKeyGenerator) <br />
+ <span style="color:grey">Key generator class, that implements will extract the key out of incoming <code class="highlighter-rouge">Row</code> object</span></li>
+ <li><a href="#COMMIT_METADATA_KEYPREFIX_OPT_KEY">COMMIT_METADATA_KEYPREFIX_OPT_KEY</a> (Default: _) <br />
+ <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
+ This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span></li>
+ </ul>
+ </li>
+ <li><a href="#readoptions">read options</a> (read.format.option(…)) <br />
+ <span style="color:grey">Options useful for reading datasets</span>
+ <ul>
+ <li><a href="#VIEW_TYPE_OPT_KEY">VIEW_TYPE_OPT_KEY</a> (Default: = read_optimized) <br />
+ <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
+ (or) Read Optimized mode (obtain latest view, based on columnar data)
+ (or) Real time mode (obtain latest view, based on row & columnar data)</span></li>
+ <li><a href="#BEGIN_INSTANTTIME_OPT_KEY">BEGIN_INSTANTTIME_OPT_KEY</a> (Default: None (Mandatory in incremental mode)) <br />
+ <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
+ necessarily correspond to an instant on the timeline. New data written with an
+ <code class="highlighter-rouge">instant_time > BEGIN_INSTANTTIME</code> are fetched out. For e.g: ‘20170901080000’ will get
+ all new data written after Sep 1, 2017 08:00AM.</span></li>
+ <li><a href="#END_INSTANTTIME_OPT_KEY">END_INSTANTTIME_OPT_KEY</a> (Default: latest instant (i.e fetches all new data since begin instant time)) <br />
+ <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
+ <code class="highlighter-rouge">instant_time <= END_INSTANTTIME</code> are fetched out.</span></li>
+ </ul>
+ </li>
+ </ul>
+ </li>
+</ul>
+
+<h3 id="tuning">Tuning</h3>
+
+<p>Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.</p>
+
+<ul>
+ <li><strong>Write operations</strong> : Use <code class="highlighter-rouge">bulkinsert</code> to load new data into a table, and there on use <code class="highlighter-rouge">upsert</code>/<code class="highlighter-rouge">insert</code>.
+ Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</li>
+ <li><strong>Input Parallelism</strong> : By default, Hoodie tends to over-partition input (i.e <code class="highlighter-rouge">withParallelism(1500)</code>), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism <code class="highlighter-rouge">hoodie.[insert|upsert|bulkinsert].shuffle.parallelism</code> such that its atleast input_data_size/500MB</li>
+ <li><strong>Off-heap memory</strong> : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like <code class="highlighter-rouge">spark.yarn.executor.memoryOverhead</code> or <code class="highlighter-rouge">spark.yarn.driver.memoryOverhead</code>, if you are running into such failures.</li>
+ <li><strong>Spark Memory</strong> : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some <code class="highlighter-rouge">spark.storage.memoryFraction</code> will generally help boost performance.</li>
+ <li><strong>Sizing files</strong> : Set <code class="highlighter-rouge">limitFileSize</code> above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.</li>
+ <li><strong>Timeseries/Log data</strong> : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
+ <ul>
+ <li>Consider tuning the bloom filter accuracy via <code class="highlighter-rouge">.bloomFilterFPP()/bloomFilterNumEntries()</code> to achieve your target index look up time</li>
+ <li>Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.</li>
+ </ul>
+ </li>
+ <li><strong>GC Tuning</strong> : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
+ <ul>
+ <li>[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions : ``-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tm [...]
+ <li>If it keeps OOMing still, reduce spark memory conservatively: <code class="highlighter-rouge">spark.memory.fraction=0.2, spark.memory.storageFraction=0.2</code> allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)</li>
+ </ul>
+ </li>
+</ul>
+
+<p>Below is a full working production config</p>
+
+<p>```
+ spark.driver.extraClassPath /etc/hive/conf
+ spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.driver.maxResultSize 2g
+ spark.driver.memory 4g
+ spark.executor.cores 1
+ spark.executor.extraJavaOptions -XX:+PrintFlagsFinal -XX:+PrintReferenceGC -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintAdaptiveSizePolicy -XX:+UnlockDiagnosticVMOptions -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.executor.id driver
+ spark.executor.instances 300
+ spark.executor.memory 6g
+ spark.rdd.compress true</p>
+
+<p>spark.kryoserializer.buffer.max 512m
+ spark.serializer org.apache.spark.serializer.KryoSerializer
+ spark.shuffle.memoryFraction 0.2
+ spark.shuffle.service.enabled true
+ spark.sql.hive.convertMetastoreParquet false
+ spark.storage.memoryFraction 0.6
+ spark.submit.deployMode cluster
+ spark.task.cpus 1
+ spark.task.maxFailures 4</p>
+
+<p>spark.yarn.driver.memoryOverhead 1024
+ spark.yarn.executor.memoryOverhead 3072
+ spark.yarn.max.executor.failures 100
+ ```</p>
+
+
+ <div class="tags">
+
+ </div>
+
+
+
+</div>
+
+<hr class="shaded"/>
+
+<footer>
+ <div class="row">
+ <div class="col-lg-12 footer">
+ ©2019 . All rights reserved. <br />
+ Site last generated: Feb 16, 2019 <br />
+ <!--<p><img src="images/company_logo.png" alt="Company logo"/></p>-->
+ </div>
+ </div>
+</footer>
+
+
+ </div>
+ <!-- /.row -->
+</div>
+<!-- /.container -->
+ </div>
+
+</body>
+
+</html>
\ No newline at end of file
diff --git a/content/css/bootstrap.min.css b/content/css/bootstrap.min.css
new file mode 100755
index 0000000..7b4112f
--- /dev/null
+++ b/content/css/bootstrap.min.css
@@ -0,0 +1,5 @@
+/*!
+ * Bootstrap v3.3.2 (http://getbootstrap.com)
+ * Copyright 2011-2016 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ *//*! normalize.css v3.0.2 | MIT License | git.io/normalize */html{font-family:sans-serif;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%}body{margin:0}article,aside,details,figcaption,figure,footer,header,hgroup,main,menu,nav,section,summary{display:block}audio,canvas,progress,video{display:inline-block;vertical-align:baseline}audio:not([controls]){display:none;height:0}[hidden],template{display:none}a{background-color:transparent}a:active,a:hover{outline:0}abbr[title]{border-b [...]
\ No newline at end of file
diff --git a/content/css/customstyles.css b/content/css/customstyles.css
new file mode 100644
index 0000000..676c804
--- /dev/null
+++ b/content/css/customstyles.css
@@ -0,0 +1,1181 @@
+body {
+ font-size:15px;
+}
+
+.bs-callout {
+ padding: 20px;
+ margin: 20px 0;
+ border: 1px solid #eee;
+ border-left-width: 5px;
+ border-radius: 3px;
+}
+.bs-callout h4 {
+ margin-top: 0;
+ margin-bottom: 5px;
+}
+.bs-callout p:last-child {
+ margin-bottom: 0;
+}
+.bs-callout code {
+ border-radius: 3px;
+}
+.bs-callout+.bs-callout {
+ margin-top: -5px;
+}
+.bs-callout-default {
+ border-left-color: #777;
+}
+.bs-callout-default h4 {
+ color: #777;
+}
+.bs-callout-primary {
+ border-left-color: #428bca;
+}
+.bs-callout-primary h4 {
+ color: #428bca;
+}
+.bs-callout-success {
+ border-left-color: #5cb85c;
+}
+.bs-callout-success h4 {
+ color: #5cb85c;
+}
+.bs-callout-danger {
+ border-left-color: #d9534f;
+}
+.bs-callout-danger h4 {
+ color: #d9534f;
+}
+.bs-callout-warning {
+ border-left-color: #f0ad4e;
+}
+.bs-callout-warning h4 {
+ color: #f0ad4e;
+}
+.bs-callout-info {
+ border-left-color: #5bc0de;
+}
+.bs-callout-info h4 {
+ color: #5bc0de;
+}
+
+
+.gi-2x{font-size: 2em;}
+.gi-3x{font-size: 3em;}
+.gi-4x{font-size: 4em;}
+.gi-5x{font-size: 5em;}
+
+
+
+
+
+.breadcrumb > .active {color: #777 !important;}
+
+/* make room for the nav bar */
+h1[id],
+h2[id],
+h3[id],
+h4[id],
+h5[id],
+h6[id],
+dt[id]{
+padding-top: 60px;
+margin-top: -40px
+}
+
+body h1 {margin-top:40px;}
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+
+.post-content ol li, .post-content ul li {
+ margin: 10px 0px;
+}
+
+.pageSummary {
+ font-size:13px;
+ display:block;
+ margin-bottom:15px;
+ padding-left:20px;
+}
+
+.post-summary {
+ margin-bottom:12px;
+}
+
+.bs-example{
+ margin: 20px;
+}
+
+.breadcrumb li {
+ color: gray;
+}
+
+table {
+ background-color: transparent;
+}
+caption {
+ padding-top: 8px;
+ padding-bottom: 8px;
+ color: #777;
+ text-align: left;
+}
+th {
+ text-align: left;
+}
+table {
+ max-width: 90%;
+ margin-bottom: 20px;
+ border: 1px solid #dedede;
+}
+
+table > thead > tr > th,
+table > tbody > tr > th,
+table > tfoot > tr > th,
+table > thead > tr > td,
+table > tbody > tr > td,
+table > tfoot > tr > td {
+ padding: 8px;
+ line-height: 1.42857143;
+ vertical-align: top;
+ border-top: 1px solid #ddd;
+}
+table > thead > tr > th {
+ vertical-align: bottom;
+ border-bottom: 2px solid #ddd;
+ text-transform: none;
+ background-color: #777;
+ color: white;
+ text-align: left;
+}
+table > caption + thead > tr:first-child > th,
+table > colgroup + thead > tr:first-child > th,
+table > thead:first-child > tr:first-child > th,
+table > caption + thead > tr:first-child > td,
+table > colgroup + thead > tr:first-child > td,
+table > thead:first-child > tr:first-child > td {
+ border-top: 0;
+}
+table > tbody + tbody {
+ b
+}
+table > tbody > tr:nth-of-type(odd) {
+ background-color: #f9f9f9;
+}
+
+table col[class*="col-"] {
+ position: static;
+ display: table-column;
+ float: none;
+}
+table td[class*="col-"],
+table th[class*="col-"] {
+ position: static;
+ display: table-cell;
+ float: none;
+}
+
+
+table td:first-child {
+ width: 150px;
+ /*font-weight:bold;*/
+}
+
+table.boldFirstColumn td:first-child {
+ font-weight: bold;
+}
+
+table tr td {
+ hyphens: auto;
+}
+
+
+p.external a {
+ text-align:right;
+ font-size:12px;
+ font-color: #0088cc;
+ display:inline;
+}
+
+#definition-box-container div a.active {
+ font-weight: bold;
+}
+p.post-meta {font-size: 80%; color: #777;}
+
+.entry-date{font-size:14px;font-size:0.875rem;line-height:1.71429;margin-bottom:0;text-transform:uppercase;}
+
+/* search area */
+#search-demo-container ul#results-container {
+ list-style: none;
+ font-size: 12px;
+ background-color: white;
+ position: absolute;
+ top: 40px; /* if you change anything about the nav, you'll prob. need to reset the top and left values here.*/
+ left: 20px;
+ z-index: -1;
+ width:223px;
+ border-left: 1px solid #dedede;
+ box-shadow: 2px 3px 2px #dedede;
+}
+
+
+ul#results-container a {
+ background-color: transparent;
+}
+
+ul#results-container a: hover {
+ color: black;
+}
+
+
+#search-demo-container a:hover {
+ color: black;
+}
+#search-input {
+ padding: .5em;
+ margin-left:20px;
+ width:20em;
+ font-size: 0.8em;
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
+ float: right;
+ margin-top:10px;
+}
+/* end search */
+
+.filter-options {
+ margin-bottom: 20px;
+}
+.filter-options button {
+ margin: 3px;
+}
+
+div#toc ul li {
+ margin: 8px 0px 8px 22px;
+ font-size: 90%;
+ list-style: square;
+}
+div#toc ul {
+ background-color: whitesmoke;
+ padding: 5px;
+ border-radius: 5px;
+ max-width: 300px;
+ color: gray;
+}
+
+div#toc ul li ul {
+ padding-left:8px;
+
+}
+
+div#toc ul li ul li::before {
+ content: "– ";
+}
+
+div#toc >ul::before {
+ content: "Table of Contents";
+ font-weight: 500;
+ color: #555;
+ text-align:center;
+ margin-left:auto;
+ margin-right:auto;
+ width:70px;
+ padding-top:20px;
+ padding-bottom:20px;
+ padding-left:10px;
+}
+
+li.dropdownActive a {
+ font-weight: bold;
+}
+
+
+.post-content a.fa-rss {
+ color: orange;
+}
+
+
+.navbar-inverse .navbar-nav > li > a {
+ background-color: transparent;
+ margin-top:10px;
+}
+
+.post-content .rssfeedLink {
+ color: #248EC2;
+}
+
+footer {
+ font-size: smaller;
+}
+
+/* FAQ page */
+#accordion .panel-heading {
+ font-size: 12px;
+}
+
+a.accordion-toggle, a.accordion-collapsed {
+ font-size: 14px;
+ text-decoration: none;
+}
+
+/* navgoco sidebar styles (customized) */
+.nav, .nav ul, .nav li {
+ list-style: none;
+}
+
+.nav ul {
+ padding: 0;
+ /*margin: 0 0 0 18px;*/
+ margin:0px;
+}
+
+.nav {
+ /* padding: 4px;*/
+ padding:0px;
+ margin: 0px;
+}
+
+.nav > li {
+ margin: 1px 0;
+}
+
+.nav > li li {
+ margin: 2px 0;
+}
+
+.nav a {
+ color: #333;
+ display: block;
+ outline: none;
+ /*-webkit-border-radius: 4px;
+ -moz-border-radius: 4px;
+ border-radius: 4px;*/
+ text-decoration: none;
+}
+
+.nav li > a > span {
+ float: right;
+ font-size: 19px;
+ font-weight: bolder;
+}
+
+
+.nav li > a > span:after {
+ content: '\25be';
+}
+.nav li.open > a > span:after {
+ content: '\25b4';
+}
+
+.nav a:hover, .nav li.active > a {
+ background-color: #8D8D8D;
+ color: #f5f5f5;
+}
+
+.nav > li.active > a {
+background-color: #347DBE;
+}
+
+.nav li a {
+ font-size: 12px;
+ line-height: 18px;
+ padding: 2px 10px;
+ background-color: #f1f1f1;
+}
+
+.nav > li > a {
+ font-size: 14px;
+ line-height: 20px;
+ padding: 4px 10px;
+}
+
+ul#mysidebar {
+ border-radius:0px;
+}
+
+.nav ul li ul li a {
+ padding-left:40px;
+}
+
+.nav li.thirdlevel > a {
+ color: #248EC2;
+ font-weight:bold;
+ padding-left:20px;
+ background-color: whitesmoke !important;
+}
+
+
+.nav ul li a {
+ background-color: #FAFAFA;
+}
+
+.nav li a {
+ padding-right:10px;
+}
+
+.nav li a:hover {
+ background-color: #8D8D8D;
+}
+
+.nav ul li a {
+ border-top:1px solid whitesmoke;
+ padding-left:10px;
+}
+/* end sidebar */
+
+.navbar-inverse .navbar-nav > .active > a, .navbar-inverse .navbar-nav > .active > a:hover, .navbar-inverse .navbar-nav > .active > a:focus {
+ border-radius:5px;
+}
+
+.navbar-inverse .navbar-nav>.open>a, .navbar-inverse .navbar-nav>.open>a:focus, .navbar-inverse .navbar-nav>.open>a:hover {
+ border-radius: 5px;
+}
+
+span.projectTitle {
+ font-family: Helvetica;
+ font-weight: bold;
+}
+
+.footer {
+ text-align: right;
+}
+
+.footerMeta {
+ background-color: whitesmoke;
+ padding: 10px;
+ max-width: 250px;
+ border-radius: 5px;
+ margin-top: 50px;
+ font-style:italic;
+ font-size:12px;
+}
+
+img.screenshotSmall {
+ max-width: 300px;
+}
+
+
+dl dt p {
+ margin-left:20px;
+}
+
+
+dl dd {
+ margin-top:10px;
+ margin-bottom:10px;
+}
+
+dl.dl-horizontal dd {
+ padding-top: 20px;
+}
+
+figcaption {
+
+ padding-bottom:12px;
+ padding-top:6px;
+ max-width: 90%;
+ margin-bottom:20px;
+ font-style: italic;
+ color: gray;
+
+}
+
+.testing {
+ color: orange;
+}
+
+.preference {
+ color: red;
+}
+
+
+table.dataTable thead {
+ background-color: #444;
+}
+table td {
+ hyphens: auto;
+}
+
+section table tr.success {
+ background-color: #dff0d8 !important;
+}
+
+table tr.info {
+ background-color: #d9edf7 !important;
+}
+
+section table tr.warning, table tr.testing, table tr.testing > td.sorting_1 {
+ background-color: #fcf8e3 !important;
+}
+section table tr.danger, table tr.preference, table tr.preference > td.sorting_1 {
+ background-color: #f2dede !important;
+}
+
+.orange {
+ color: orange;
+}
+
+table.profile thead tr th {
+ background-color: #248ec2;
+}
+
+table.request thead tr th {
+ background-color: #ED1951;
+}
+
+.audienceLabel {
+ margin: 10px;
+ float: right;
+ border:1px solid #dedede;
+ padding:7px;
+}
+
+.prefaceAudienceLabel {
+ color: gray;
+ text-align: center;
+ margin:5px;
+}
+span.myLabel {
+ padding-left:10px;
+ padding-right:10px;
+}
+
+button.cursorNorm {
+ cursor: default;
+}
+
+a.dropdown-toggle, .navbar-inverse .navbar-nav > li > a {
+ margin-left: 10px;
+}
+
+hr.faded {
+ border: 0;
+ height: 1px;
+ background-image: -webkit-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -moz-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -ms-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -o-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+}
+
+hr.shaded {
+ height: 12px;
+ border: 0;
+ box-shadow: inset 0 6px 6px -6px rgba(0,0,0,0.5);
+ margin-top: 70px;
+ background: white;
+ width: 100%;
+ margin-bottom: 10px;
+}
+
+.fa-6x{font-size:900%;}
+.fa-7x{font-size:1100%;}
+.fa-8x{font-size:1300%;}
+.fa-9x{font-size:1500%;}
+.fa-10x{font-size:1700%;}
+
+i.border {
+ padding: 10px 20px;
+ background-color: whitesmoke;
+}
+
+a[data-toggle] {
+ color: #248EC2;
+}
+
+.summary {
+ font-size:120%;
+ color: #808080;
+ margin:20px 0px 20px 0px;
+ border-left: 5px solid #ED1951;
+ padding-left: 10px;
+
+}
+
+.summary:before {
+ content: "Summary: ";
+ font-weight: bold;
+}
+
+
+a.fa.fa-envelope-o.mailto {
+ font-weight: 600;
+}
+
+h3 {color: #ED1951; font-weight:normal; font-size:130%;}
+h4 {color: #808080; font-weight:normal; font-size:120%; font-style:italic;}
+
+.alert, .callout {
+ overflow: hidden;
+}
+
+.nav-tabs > li.active > a, .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus {
+ background-color: #248ec2;
+ color: white;
+}
+
+ol li ol li {list-style-type: lower-alpha;}
+ol li ul li {list-style-type: disc;}
+
+li img {clear:both; }
+
+div#toc ul li ul li {
+ list-style-type: none;
+ margin: 5px 0px 0px 0px;
+}
+
+.tab-content {
+ padding: 15px;
+ background-color: #FAFAFA;
+}
+
+span.tagTitle {font-weight: 500;}
+
+li.activeSeries {
+ font-weight: bold;
+}
+
+.seriesContext .dropdown-menu li.active {
+ font-weight: bold;
+ margin-left: 43px;
+ font-size:18px;
+}
+
+.alert-warning {
+ color: #444;
+}
+
+div.alert code, h2 code {
+ background-color: transparent !important;
+}
+/* without this, the links in these notes aren't visible.*/
+.alert a {
+ text-decoration: underline;
+}
+
+div.tags {padding: 10px 5px;}
+
+.tabLabel {
+ font-weight: normal;
+}
+
+hr {
+ background: #999;
+ margin: 30px 0px;
+ width: 90%;
+ margin-left: auto;
+ margin-right: auto;
+}
+
+button.cursorNorm {
+ cursor: pointer;
+}
+
+h2 {
+ font-size:24px;
+ line-height:29px;
+}
+span.otherProgrammingLanguages {
+ font-style: normal;
+}
+
+a[data-toggle="tooltip"] {
+ color: #649345;
+ font-style: italic;
+ cursor: default;
+}
+
+.seriesNext, .seriesContext {
+ margin-top: 15px;
+ margin-bottom: 15px;
+}
+
+.seriescontext ol li {
+ list-style-type: upper-roman;
+}
+
+ol.series li {
+ list-style-type: decimal;
+ margin-left: 40px;
+ padding-left: 0px;
+}
+
+.siteTagline {
+ font-size: 200%;
+ font-weight: bold;
+ color: silver;
+ font-family: monospace;
+ text-align: center;
+ line-height: 10px;
+ margin: 20px 0px;
+ display: block;
+}
+
+.versionTagline {
+ text-align: center;
+ margin-bottom: 20px;
+ font-family: courier;
+ font-color: silver;
+ color: #444;
+ display:block;
+}
+
+/* not sure if using this ...*/
+.navbar-inverse .navbar-collapse, .navbar-inverse .navbar-form {
+ border-color: #248ec2 !important;
+}
+
+#mysidebar .nav ul {
+ background-color: #FAFAFA;
+}
+.nav ul.series li {
+ list-style: decimal;
+ font-size:12px;
+}
+
+.nav ul.series li a:hover {
+ background-color: gray;
+}
+.nav ul.series {
+ padding-left: 30px;
+}
+
+.nav ul.series {
+ background-color: #FAFAFA;
+}
+
+/*
+a.dropdown-toggle.otherProgLangs {
+ color: #f7e68f !important;
+}
+*/
+
+span.muted {color: #666;}
+
+table code {background-color: transparent;}
+
+.highlight .err {
+ color: #a61717;
+ background-color: transparent !important;
+}
+
+table p {
+ margin-top: 12px;
+ margin-bottom: 12px;
+}
+
+pre, table code {
+ white-space: pre-wrap; /* css-3 */
+ white-space: -moz-pre-wrap; /* Mozilla, since 1999 */
+ white-space: -pre-wrap; /* Opera 4-6 */
+ white-space: -o-pre-wrap; /* Opera 7 */
+ word-wrap: break-word; /* Internet Explorer 5.5+ */
+}
+
+pre {
+ margin: 25px 0px;
+}
+
+#json-box-container pre {
+ margin: 0px;
+}
+
+.video-js {
+ margin: 30px 0px;
+}
+
+video {
+ display: block;
+ margin: 30px 0px;
+ border: 1px solid #c0c0c0;
+}
+
+
+p.required, p.dataType {display: block; color: #c0c0c0; font-size: 80%; margin-left:4px;}
+
+dd {margin-left:20px;}
+
+.post-content img.inline {
+ margin:0px;
+ margin-bottom:6px;
+}
+.panel-heading {
+ font-weight: bold;
+}
+
+.note code, .alert code, .warning code, div#toc code, h2 code, h3 code, h4 code {
+ color: inherit;
+ padding: 0px;
+}
+
+.alert {
+ margin-bottom:10px;
+ margin-top:10px;
+}
+
+a.accordion-toggle {
+ font-style: normal;
+}
+
+span.red {
+ color: red;
+ font-family: Monaco, Menlo, Consolas, "Courier New", monospace;
+}
+
+h3.codeExplanation {
+ font-size:18px;
+ font-style:normal;
+ color: black;
+ line-height: 24px;
+}
+
+span.soft {
+ color: #c0c0c0;
+}
+
+.githubEditButton {
+ margin-bottom:7px;
+}
+
+.endpoint {
+ padding: 15px;
+ background-color: #f0f0f0;
+ font-family: courier;
+ font-size: 110%;
+ margin: 20px 0px;
+ color: #444;
+}
+
+.parameter {
+ font-family: courier;
+ color: red !important;
+}
+
+.formBoundary {
+ border: 1px solid gray;
+ padding: 15px;
+ margin: 15px 0px;
+ background-color: whitesmoke;
+}
+
+@media (max-width: 767px) {
+ .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
+ color: #444;
+ }
+}
+
+@media (max-width: 990px) {
+ #mysidebar {
+ position: relative;
+ }
+}
+
+@media (min-width: 1000px) {
+
+ ul#mysidebar {
+ width: 225px;
+ }
+}
+
+@media (max-width: 900px) {
+
+ ul#mysidebar {
+ max-width: 100%;
+ }
+}
+
+.col-md-9 img {
+ max-width: 100%;
+ max-height: 100%;
+}
+
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+.col-md-9 img {
+ max-width: 100%;
+ max-height: 100%;
+}
+
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+
+.videoThumbs img {
+ float: left;
+ margin:15px 15px 15px 0px;
+ box-shadow: 2px 2px 1px #f0f0f0;
+ border: 1px solid #dedede;
+}
+
+
+@media only screen and (min-width: 900px), @media only screen and (min-device-width: 900px) {
+ .col-md-9 img {
+ max-width: 700px;
+ max-height: 700px;
+ }
+}
+
+*:hover > .anchorjs-link {
+ transition: color .25s linear;
+ text-decoration: none;
+}
+
+.kbCaption {
+ color: white;
+ background-color: #444;
+ padding:10px;
+}
+
+/* this part adds an icon after external links, using FontAwesome*/
+a[href^="http://"]:after, a[href^="https://"]:after {
+ content: "\f08e";
+ font-family: FontAwesome;
+ font-weight: normal;
+ font-style: normal;
+ display: inline-block;
+ text-decoration: none;
+ padding-left: 3px;
+}
+
+/* Strip the outbound icon when this class is present */
+a[href].noCrossRef::after,
+a.no_icon:after
+ {
+ content:"" !important;
+ padding-left: 0;
+}
+
+.btn-default {
+ margin-bottom: 10px;
+}
+
+/* algolia search */
+
+.search {
+ text-align: left;
+}
+.search input {
+ font-size: 20px;
+ width: 300px;
+}
+.results {
+ margin: auto;
+ text-align: left;
+}
+.results ul {
+ list-style-type: none;
+ padding: 0;
+}
+
+/* algolia */
+
+div.results {
+ position: absolute;
+ background-color: white;
+ width: 100%;
+}
+
+.post-meta {
+ font-size: 14px;
+ color: #828282;
+}
+
+.post-link {
+ font-size: 22px;
+}
+
+.post-list p {
+ margin: 10px 0px;
+}
+
+time {
+ margin-right: 10px;
+}
+
+p.post-meta time {
+ margin-right: 0px;
+}
+
+span.label.label-default {
+ background-color: gray;
+}
+
+span.label.label-primary {
+ background-color: #f0ad4e;
+}
+.col-lg-12 .nav li a {background-color: white}
+
+
+.nav li.active > a.subfoldersTitle {
+ background-color: whitesmoke;
+ font-weight: bold;
+ color: black;
+ }
+
+a code {
+ color: #248EC2;
+}
+
+code + a > code {
+ margin-left: -7px;
+}
+
+table th code {
+ color: white;
+}
+
+ol li ul li ol li {
+ list-style: decimal;
+}
+
+ol li ul li ol li ul li{
+ list-style: disc;
+}
+
+.post-content table th {
+ vertical-align: top;
+}
+
+table thead th code.highlighter-rouge {
+ background-color: transparent;
+}
+
+
+.box {
+ padding: 10px;
+ border: 1px solid #888;
+ box-shadow: 2px 2px 4px #dedede;
+ width: 100px;
+ height: 80px;
+ background-color: #f5f5f5;
+ font-family: Arial;
+ font-size: 12px;
+ hyphens: auto;
+ float: left;
+ font-size: 12px;
+}
+
+.box:hover {
+ background-color: #f0f0f0;
+}
+
+#userMap {
+ overflow-x: auto;
+ overflow-y: auto;
+ padding: 20px;
+ min-width: 770px;
+}
+
+#userMap .active {
+ background-color: #d6f5d6;
+ border:1px solid #555;
+ font-weight: bold;
+}
+
+h2.userMapTitle {
+ font-family: Arial;
+}
+
+#userMap a:hover {
+ text-decoration: none;
+ }
+
+div.arrow {
+ max-width: 50px;
+ margin-left: 15px;
+ margin-right: 15px;
+ font-size: 20px;
+}
+
+div.content {
+ max-width: 110px
+}
+
+#userMap div.arrow, #userMap div.content {
+ float: left;
+}
+
+.clearfix {
+ clear: both;
+}
+
+
+#userMap div.arrow {
+ position: relative;
+ top: 30px;
+}
+
+.box1 {
+ margin-left:0px;
+}
+
+button.btn.btn-default.btn-lg.modalButton1 {
+ margin-left: -20px;
+}
+
+div.box.box1 {
+ margin-left: -20px;
+}
+
+#userMap .btn-lg {
+ width: 100px;
+ height: 80px;
+
+}
+
+#userMap .complexArrow {
+ font-size: 22px;
+ margin: 0px 10px;
+}
+
+
+#userMap .btn-lg .active {
+ background-color: #d6f5d6;
+}
+
+#userMap .btn-lg {
+ white-space: pre-wrap; /* css-3 */
+ white-space: -moz-pre-wrap; /* Mozilla, since 1999 */
+ white-space: -pre-wrap; /* Opera 4-6 */
+ white-space: -o-pre-wrap; /* Opera 7 */
+ word-wrap: break-word; /* Internet Explorer 5.5+ */
+ font-size: 14px;
+ }
+
+/*
+ * Let's target IE to respect aspect ratios and sizes for img tags containing SVG files
+ *
+ * [1] IE9
+ * [2] IE10+
+ */
+/* 1 */
+.ie9 img[src$=".svg"] {
+ width: 100%;
+}
+/* 2 */
+@media screen and (-ms-high-contrast: active), (-ms-high-contrast: none) {
+ img[src$=".svg"] {
+ width: 100%;
+ }
+}
+
+h4.panel-title {
+ padding-top: 0px;
+ margin-top: 0px;
+}
\ No newline at end of file
diff --git a/content/css/font-awesome.min.css b/content/css/font-awesome.min.css
new file mode 100644
index 0000000..08e68ec
--- /dev/null
+++ b/content/css/font-awesome.min.css
@@ -0,0 +1,4 @@
+/*!
+ * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
+ * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
+ */@font-face{font-family:'FontAwesome';src:url('fonts/fontawesome-webfont.eot?v=4.2.0');src:url('fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'),url('fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'),url('fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'),url('fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');font-weight:normal;font-style:normal}.fa{display:inline-block;font:normal normal normal 14px/1 FontAwesome;font-size [...]
\ No newline at end of file
diff --git a/content/css/fonts/FontAwesome.otf b/content/css/fonts/FontAwesome.otf
new file mode 100644
index 0000000..f7936cc
Binary files /dev/null and b/content/css/fonts/FontAwesome.otf differ
diff --git a/content/css/fonts/fontawesome-webfont.eot b/content/css/fonts/fontawesome-webfont.eot
new file mode 100644
index 0000000..33b2bb8
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diff --git a/content/css/fonts/fontawesome-webfont.svg b/content/css/fonts/fontawesome-webfont.svg
new file mode 100644
index 0000000..1ee89d4
--- /dev/null
+++ b/content/css/fonts/fontawesome-webfont.svg
@@ -0,0 +1,565 @@
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+<metadata></metadata>
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+<glyph unicode="©" horiz-adv-x="1792" />
+<glyph unicode="®" horiz-adv-x="1792" />
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+<glyph unicode="Æ" horiz-adv-x="1792" />
+<glyph unicode="Ø" horiz-adv-x="1792" />
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+<glyph unicode=" " horiz-adv-x="256" />
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new file mode 100644
index 0000000..ff64532
--- /dev/null
+++ b/content/css/lavish-bootstrap.css
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+/* CSS generated by http://lavishbootstrap.com */
+/*! normalize.css v2.1.0 | MIT License | git.io/normalize */
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+hgroup,
+main,
+nav,
+section,
+summary {
+ display: block;
+}
+audio,
+canvas,
+video {
+ display: inline-block;
+}
+audio:not([controls]) {
+ display: none;
+ height: 0;
+}
+[hidden] {
+ display: none;
+}
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+ font-family: sans-serif;
+ -webkit-text-size-adjust: 100%;
+ -ms-text-size-adjust: 100%;
+}
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+ margin: 0;
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+ outline: thin dotted;
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+}
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+ font-size: 2em;
+ margin: 0.67em 0;
+}
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+ border-bottom: 1px dotted;
+}
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+ font-weight: bold;
+}
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+ font-style: italic;
+}
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+ -moz-box-sizing: content-box;
+ box-sizing: content-box;
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+ color: #000;
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+ font-family: monospace, serif;
+ font-size: 1em;
+}
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+ white-space: pre-wrap;
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+ position: relative;
+ vertical-align: baseline;
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+ top: -0.5em;
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+ bottom: -0.25em;
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+ border: 0;
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+ overflow: hidden;
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+ margin: 0;
+}
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+ border: 1px solid #c0c0c0;
+ margin: 0 2px;
+ padding: 0.35em 0.625em 0.75em;
+}
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+ border: 0;
+ padding: 0;
+}
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+select,
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+ font-family: inherit;
+ font-size: 100%;
+ margin: 0;
+}
+button,
+input {
+ line-height: normal;
+}
+button,
+select {
+ text-transform: none;
+}
+button,
+html input[type="button"],
+input[type="reset"],
+input[type="submit"] {
+ -webkit-appearance: button;
+ cursor: pointer;
+}
+button[disabled],
+html input[disabled] {
+ cursor: default;
+}
+input[type="checkbox"],
+input[type="radio"] {
+ box-sizing: border-box;
+ padding: 0;
+}
+input[type="search"] {
+ -webkit-appearance: textfield;
+ -moz-box-sizing: content-box;
+ -webkit-box-sizing: content-box;
+ box-sizing: content-box;
+}
+input[type="search"]::-webkit-search-cancel-button,
+input[type="search"]::-webkit-search-decoration {
+ -webkit-appearance: none;
+}
+button::-moz-focus-inner,
+input::-moz-focus-inner {
+ border: 0;
+ padding: 0;
+}
+textarea {
+ overflow: auto;
+ vertical-align: top;
+}
+table {
+ border-collapse: collapse;
+ border-spacing: 0;
+}
+@media print {
+ * {
+ text-shadow: none !important;
+ color: #000 !important;
+ background: transparent !important;
+ box-shadow: none !important;
+ }
+ a,
+ a:visited {
+ text-decoration: underline;
+ }
+ a[href]:after {
+ content: " (" attr(href) ")";
+ }
+ abbr[title]:after {
+ content: " (" attr(title) ")";
+ }
+ .ir a:after,
+ a[href^="javascript:"]:after,
+ a[href^="#"]:after {
+ content: "";
+ }
+ pre,
+ blockquote {
+ border: 1px solid #999;
+ page-break-inside: avoid;
+ }
+ thead {
+ display: table-header-group;
+ }
+ tr,
+ img {
+ page-break-inside: avoid;
+ }
+ img {
+ max-width: 100% !important;
+ }
+ @page {
+ margin: 2cm .5cm;
+ }
+ p,
+ h2,
+ h3 {
+ orphans: 3;
+ widows: 3;
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+ h3 {
+ page-break-after: avoid;
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+ display: none;
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+ }
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+ .dropup > .btn > .caret {
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+ .table-bordered td {
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+*:before,
+*:after {
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
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+ font-size: 62.5%;
+ -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
+}
+body {
+ font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+ font-size: 14px;
+ line-height: 1.428571429;
+ /*color: #77777a; */
+ background-color: #ffffff;
+}
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+ font-family: inherit;
+ font-size: inherit;
+ line-height: inherit;
+}
+button,
+input,
+select[multiple],
+textarea {
+ background-image: none;
+}
+a {
+ color: #248EC2;
+ text-decoration: none;
+}
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+a:focus {
+ text-decoration: underline;
+}
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+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
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+ vertical-align: middle;
+}
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+ display: block;
+ max-width: 100%;
+ height: auto;
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+}
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+ padding: 4px;
+ line-height: 1.428571429;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-radius: 4px;
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+ transition: all 0.2s ease-in-out;
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+ max-width: 100%;
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+ border-radius: 50%;
+}
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+ margin-top: 20px;
+ margin-bottom: 20px;
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+ border-top: 1px solid #bac9c2;
+}
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+ width: 1px;
+ height: 1px;
+ margin: -1px;
+ padding: 0;
+ overflow: hidden;
+ clip: rect(0 0 0 0);
+ border: 0;
+}
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+ margin: 0 0 10px;
+}
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+ margin-bottom: 20px;
+ font-size: 16.099999999999998px;
+ font-weight: 200;
+ line-height: 1.4;
+}
+@media (min-width: 768px) {
+ .lead {
+ font-size: 21px;
+ }
+}
+small {
+ font-size: 85%;
+}
+cite {
+ font-style: normal;
+}
+.text-muted {
+ color: #f9faf9;
+}
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+ color: #74ab50;
+}
+.text-warning {
+ color: #c09853;
+}
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+ color: #b94a48;
+}
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+ color: #468847;
+}
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+ color: #3a87ad;
+}
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+ text-align: left;
+}
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+ text-align: right;
+}
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+ text-align: center;
+}
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+ font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
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+}
+h1 small,
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+ font-weight: normal;
+ line-height: 1;
+ color: #f9faf9;
+}
+h1,
+h2,
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+ margin-top: 20px;
+ margin-bottom: 10px;
+}
+h4,
+h5,
+h6 {
+ margin-top: 10px;
+ margin-bottom: 10px;
+}
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+}
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+ padding-bottom: 9px;
+ margin: 40px 0 20px;
+ border-bottom: 1px solid #bac9c2;
+}
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+ margin-top: 0;
+ margin-bottom: 10px;
+}
+ul ul,
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+ margin-bottom: 0;
+}
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+ padding-left: 0;
+ list-style: none;
+}
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+ padding-left: 0;
+ list-style: none;
+}
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+ display: inline-block;
+ padding-left: 5px;
+ padding-right: 5px;
+}
+dl {
+ margin-bottom: 20px;
+}
+dt,
+dd {
+ line-height: 1.428571429;
+}
+dt {
+ font-weight: bold;
+}
+dd {
+ margin-left: 0;
+}
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+ .dl-horizontal dt {
+ float: left;
+ width: 160px;
+ clear: left;
+ text-align: right;
+ overflow: hidden;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+ }
+ .dl-horizontal dd {
+ margin-left: 180px;
+ }
+ .dl-horizontal dd:before,
+ .dl-horizontal dd:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+ }
+ .dl-horizontal dd:after {
+ clear: both;
+ }
+ .dl-horizontal dd:before,
+ .dl-horizontal dd:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+ }
+ .dl-horizontal dd:after {
+ clear: both;
+ }
+}
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+ cursor: help;
+ border-bottom: 1px dotted #f9faf9;
+}
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+}
+blockquote {
+ padding: 10px 20px;
+ margin: 0 0 20px;
+ border-left: 5px solid #bac9c2;
+}
+blockquote p {
+ font-size: 17.5px;
+ font-weight: 300;
+ line-height: 1.25;
+}
+blockquote p:last-child {
+ margin-bottom: 0;
+}
+blockquote small {
+ display: block;
+ line-height: 1.428571429;
+ color: #f9faf9;
+}
+blockquote small:before {
+ content: '\2014 \00A0';
+}
+blockquote.pull-right {
+ padding-right: 15px;
+ padding-left: 0;
+ border-right: 5px solid #bac9c2;
+ border-left: 0;
+}
+blockquote.pull-right p,
+blockquote.pull-right small {
+ text-align: right;
+}
+blockquote.pull-right small:before {
+ content: '';
+}
+blockquote.pull-right small:after {
+ content: '\00A0 \2014';
+}
+q:before,
+q:after,
+blockquote:before,
+blockquote:after {
+ content: "";
+}
+address {
+ display: block;
+ margin-bottom: 20px;
+ font-style: normal;
+ line-height: 1.428571429;
+}
+code,
+pre {
+ font-family: Monaco, Menlo, Consolas, "Courier New", monospace;
+}
+code {
+ padding: 2px 4px;
+ font-size: 90%;
+ color: #444;
+ background-color: #f0f0f0;
+ white-space: nowrap;
+ border-radius: 4px;
+}
+
+pre {
+ display: block;
+ padding: 9.5px;
+ margin: 0 0 10px;
+ font-size: 13px;
+ line-height: 1.428571429;
+ word-break: break-all;
+ word-wrap: break-word;
+ color: #77777a;
+ background-color: #f5f5f5;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+}
+pre.prettyprint {
+ margin-bottom: 20px;
+}
+pre code {
+ padding: 0;
+ font-size: inherit;
+ color: inherit;
+ white-space: pre-wrap;
+ background-color: transparent;
+ border: 0;
+}
+.pre-scrollable {
+ max-height: 340px;
+ overflow-y: scroll;
+}
+.container {
+ margin-right: auto;
+ margin-left: auto;
+ padding-left: 15px;
+ padding-right: 15px;
+}
+.container:before,
+.container:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.container:after {
+ clear: both;
+}
+.container:before,
+.container:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.container:after {
+ clear: both;
+}
+.row {
+ margin-left: -15px;
+ margin-right: -15px;
+}
+.row:before,
+.row:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.row:after {
+ clear: both;
+}
+.row:before,
+.row:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.row:after {
+ clear: both;
+}
+.col-xs-1,
+.col-xs-2,
+.col-xs-3,
+.col-xs-4,
+.col-xs-5,
+.col-xs-6,
+.col-xs-7,
+.col-xs-8,
+.col-xs-9,
+.col-xs-10,
+.col-xs-11,
+.col-xs-12,
+.col-sm-1,
+.col-sm-2,
+.col-sm-3,
+.col-sm-4,
+.col-sm-5,
+.col-sm-6,
+.col-sm-7,
+.col-sm-8,
+.col-sm-9,
+.col-sm-10,
+.col-sm-11,
+.col-sm-12,
+.col-md-1,
+.col-md-2,
+.col-md-3,
+.col-md-4,
+.col-md-5,
+.col-md-6,
+.col-md-7,
+.col-md-8,
+.col-md-9,
+.col-md-10,
+.col-md-11,
+.col-md-12,
+.col-lg-1,
+.col-lg-2,
+.col-lg-3,
+.col-lg-4,
+.col-lg-5,
+.col-lg-6,
+.col-lg-7,
+.col-lg-8,
+.col-lg-9,
+.col-lg-10,
+.col-lg-11,
+.col-lg-12 {
+ position: relative;
+ min-height: 1px;
+ padding-left: 15px;
+ padding-right: 15px;
+}
+.col-xs-1,
+.col-xs-2,
+.col-xs-3,
+.col-xs-4,
+.col-xs-5,
+.col-xs-6,
+.col-xs-7,
+.col-xs-8,
+.col-xs-9,
+.col-xs-10,
+.col-xs-11 {
+ float: left;
+}
+.col-xs-1 {
+ width: 8.333333333333332%;
+}
+.col-xs-2 {
+ width: 16.666666666666664%;
+}
+.col-xs-3 {
+ width: 25%;
+}
+.col-xs-4 {
+ width: 33.33333333333333%;
+}
+.col-xs-5 {
+ width: 41.66666666666667%;
+}
+.col-xs-6 {
+ width: 50%;
+}
+.col-xs-7 {
+ width: 58.333333333333336%;
+}
+.col-xs-8 {
+ width: 66.66666666666666%;
+}
+.col-xs-9 {
+ width: 75%;
+}
+.col-xs-10 {
+ width: 83.33333333333334%;
+}
+.col-xs-11 {
+ width: 91.66666666666666%;
+}
+.col-xs-12 {
+ width: 100%;
+}
+@media (min-width: 768px) {
+ .container {
+ max-width: 750px;
+ }
+ .col-sm-1,
+ .col-sm-2,
+ .col-sm-3,
+ .col-sm-4,
+ .col-sm-5,
+ .col-sm-6,
+ .col-sm-7,
+ .col-sm-8,
+ .col-sm-9,
+ .col-sm-10,
+ .col-sm-11 {
+ float: left;
+ }
+ .col-sm-1 {
+ width: 8.333333333333332%;
+ }
+ .col-sm-2 {
+ width: 16.666666666666664%;
+ }
+ .col-sm-3 {
+ width: 25%;
+ }
+ .col-sm-4 {
+ width: 33.33333333333333%;
+ }
+ .col-sm-5 {
+ width: 41.66666666666667%;
+ }
+ .col-sm-6 {
+ width: 50%;
+ }
+ .col-sm-7 {
+ width: 58.333333333333336%;
+ }
+ .col-sm-8 {
+ width: 66.66666666666666%;
+ }
+ .col-sm-9 {
+ width: 75%;
+ }
+ .col-sm-10 {
+ width: 83.33333333333334%;
+ }
+ .col-sm-11 {
+ width: 91.66666666666666%;
+ }
+ .col-sm-12 {
+ width: 100%;
+ }
+ .col-sm-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-sm-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-sm-push-3 {
+ left: 25%;
+ }
+ .col-sm-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-sm-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-sm-push-6 {
+ left: 50%;
+ }
+ .col-sm-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-sm-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-sm-push-9 {
+ left: 75%;
+ }
+ .col-sm-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-sm-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-sm-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-sm-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-sm-pull-3 {
+ right: 25%;
+ }
+ .col-sm-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-sm-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-sm-pull-6 {
+ right: 50%;
+ }
+ .col-sm-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-sm-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-sm-pull-9 {
+ right: 75%;
+ }
+ .col-sm-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-sm-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-sm-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-sm-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-sm-offset-3 {
+ margin-left: 25%;
+ }
+ .col-sm-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-sm-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-sm-offset-6 {
+ margin-left: 50%;
+ }
+ .col-sm-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-sm-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-sm-offset-9 {
+ margin-left: 75%;
+ }
+ .col-sm-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-sm-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+@media (min-width: 992px) {
+ .container {
+ max-width: 970px;
+ }
+ .col-md-1,
+ .col-md-2,
+ .col-md-3,
+ .col-md-4,
+ .col-md-5,
+ .col-md-6,
+ .col-md-7,
+ .col-md-8,
+ .col-md-9,
+ .col-md-10,
+ .col-md-11 {
+ float: left;
+ }
+ .col-md-1 {
+ width: 8.333333333333332%;
+ }
+ .col-md-2 {
+ width: 16.666666666666664%;
+ }
+ .col-md-3 {
+ width: 25%;
+ }
+ .col-md-4 {
+ width: 33.33333333333333%;
+ }
+ .col-md-5 {
+ width: 41.66666666666667%;
+ }
+ .col-md-6 {
+ width: 50%;
+ }
+ .col-md-7 {
+ width: 58.333333333333336%;
+ }
+ .col-md-8 {
+ width: 66.66666666666666%;
+ }
+ .col-md-9 {
+ width: 75%;
+ }
+ .col-md-10 {
+ width: 83.33333333333334%;
+ }
+ .col-md-11 {
+ width: 91.66666666666666%;
+ }
+ .col-md-12 {
+ width: 100%;
+ }
+ .col-md-push-0 {
+ left: auto;
+ }
+ .col-md-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-md-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-md-push-3 {
+ left: 25%;
+ }
+ .col-md-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-md-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-md-push-6 {
+ left: 50%;
+ }
+ .col-md-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-md-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-md-push-9 {
+ left: 75%;
+ }
+ .col-md-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-md-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-md-pull-0 {
+ right: auto;
+ }
+ .col-md-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-md-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-md-pull-3 {
+ right: 25%;
+ }
+ .col-md-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-md-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-md-pull-6 {
+ right: 50%;
+ }
+ .col-md-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-md-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-md-pull-9 {
+ right: 75%;
+ }
+ .col-md-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-md-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-md-offset-0 {
+ margin-left: 0;
+ }
+ .col-md-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-md-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-md-offset-3 {
+ margin-left: 25%;
+ }
+ .col-md-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-md-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-md-offset-6 {
+ margin-left: 50%;
+ }
+ .col-md-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-md-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-md-offset-9 {
+ margin-left: 75%;
+ }
+ .col-md-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-md-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+@media (min-width: 1200px) {
+ .container {
+ max-width: 1170px;
+ }
+ .col-lg-1,
+ .col-lg-2,
+ .col-lg-3,
+ .col-lg-4,
+ .col-lg-5,
+ .col-lg-6,
+ .col-lg-7,
+ .col-lg-8,
+ .col-lg-9,
+ .col-lg-10,
+ .col-lg-11 {
+ float: left;
+ }
+ .col-lg-1 {
+ width: 8.333333333333332%;
+ }
+ .col-lg-2 {
+ width: 16.666666666666664%;
+ }
+ .col-lg-3 {
+ width: 25%;
+ }
+ .col-lg-4 {
+ width: 33.33333333333333%;
+ }
+ .col-lg-5 {
+ width: 41.66666666666667%;
+ }
+ .col-lg-6 {
+ width: 50%;
+ }
+ .col-lg-7 {
+ width: 58.333333333333336%;
+ }
+ .col-lg-8 {
+ width: 66.66666666666666%;
+ }
+ .col-lg-9 {
+ width: 75%;
+ }
+ .col-lg-10 {
+ width: 83.33333333333334%;
+ }
+ .col-lg-11 {
+ width: 91.66666666666666%;
+ }
+ .col-lg-12 {
+ width: 100%;
+ }
+ .col-lg-push-0 {
+ left: auto;
+ }
+ .col-lg-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-lg-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-lg-push-3 {
+ left: 25%;
+ }
+ .col-lg-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-lg-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-lg-push-6 {
+ left: 50%;
+ }
+ .col-lg-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-lg-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-lg-push-9 {
+ left: 75%;
+ }
+ .col-lg-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-lg-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-lg-pull-0 {
+ right: auto;
+ }
+ .col-lg-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-lg-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-lg-pull-3 {
+ right: 25%;
+ }
+ .col-lg-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-lg-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-lg-pull-6 {
+ right: 50%;
+ }
+ .col-lg-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-lg-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-lg-pull-9 {
+ right: 75%;
+ }
+ .col-lg-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-lg-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-lg-offset-0 {
+ margin-left: 0;
+ }
+ .col-lg-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-lg-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-lg-offset-3 {
+ margin-left: 25%;
+ }
+ .col-lg-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-lg-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-lg-offset-6 {
+ margin-left: 50%;
+ }
+ .col-lg-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-lg-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-lg-offset-9 {
+ margin-left: 75%;
+ }
+ .col-lg-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-lg-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+table {
+ max-width: 100%;
+ background-color: transparent;
+}
+th {
+ text-align: left;
+}
+.table {
+ width: 100%;
+ margin-bottom: 20px;
+}
+.table thead > tr > th,
+.table tbody > tr > th,
+.table tfoot > tr > th,
+.table thead > tr > td,
+.table tbody > tr > td,
+.table tfoot > tr > td {
+ padding: 8px;
+ line-height: 1.428571429;
+ vertical-align: top;
+ border-top: 1px solid #77777a;
+}
+.table thead > tr > th {
+ vertical-align: bottom;
+ border-bottom: 2px solid #77777a;
+}
+.table caption + thead tr:first-child th,
+.table colgroup + thead tr:first-child th,
+.table thead:first-child tr:first-child th,
+.table caption + thead tr:first-child td,
+.table colgroup + thead tr:first-child td,
+.table thead:first-child tr:first-child td {
+ border-top: 0;
+}
+.table tbody + tbody {
+ border-top: 2px solid #77777a;
+}
+.table .table {
+ background-color: #ffffff;
+}
+.table-condensed thead > tr > th,
+.table-condensed tbody > tr > th,
+.table-condensed tfoot > tr > th,
+.table-condensed thead > tr > td,
+.table-condensed tbody > tr > td,
+.table-condensed tfoot > tr > td {
+ padding: 5px;
+}
+.table-bordered {
+ border: 1px solid #77777a;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > tbody > tr > th,
+.table-bordered > tfoot > tr > th,
+.table-bordered > thead > tr > td,
+.table-bordered > tbody > tr > td,
+.table-bordered > tfoot > tr > td {
+ border: 1px solid #77777a;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > thead > tr > td {
+ border-bottom-width: 2px;
+}
+.table-striped > tbody > tr:nth-child(odd) > td,
+.table-striped > tbody > tr:nth-child(odd) > th {
+ background-color: #f9f9f9;
+}
+.table-hover > tbody > tr:hover > td,
+.table-hover > tbody > tr:hover > th {
+ background-color: #f5f5f5;
+}
+table col[class*="col-"] {
+ float: none;
+ display: table-column;
+}
+table td[class*="col-"],
+table th[class*="col-"] {
+ float: none;
+ display: table-cell;
+}
+.table > thead > tr > td.active,
+.table > tbody > tr > td.active,
+.table > tfoot > tr > td.active,
+.table > thead > tr > th.active,
+.table > tbody > tr > th.active,
+.table > tfoot > tr > th.active,
+.table > thead > tr.active > td,
+.table > tbody > tr.active > td,
+.table > tfoot > tr.active > td,
+.table > thead > tr.active > th,
+.table > tbody > tr.active > th,
+.table > tfoot > tr.active > th {
+ background-color: #f5f5f5;
+}
+.table > thead > tr > td.success,
+.table > tbody > tr > td.success,
+.table > tfoot > tr > td.success,
+.table > thead > tr > th.success,
+.table > tbody > tr > th.success,
+.table > tfoot > tr > th.success,
+.table > thead > tr.success > td,
+.table > tbody > tr.success > td,
+.table > tfoot > tr.success > td,
+.table > thead > tr.success > th,
+.table > tbody > tr.success > th,
+.table > tfoot > tr.success > th {
+ background-color: #dff0d8;
+ border-color: #d6e9c6;
+}
+.table-hover > tbody > tr > td.success:hover,
+.table-hover > tbody > tr > th.success:hover,
+.table-hover > tbody > tr.success:hover > td {
+ background-color: #d0e9c6;
+ border-color: #c9e2b3;
+}
+.table > thead > tr > td.danger,
+.table > tbody > tr > td.danger,
+.table > tfoot > tr > td.danger,
+.table > thead > tr > th.danger,
+.table > tbody > tr > th.danger,
+.table > tfoot > tr > th.danger,
+.table > thead > tr.danger > td,
+.table > tbody > tr.danger > td,
+.table > tfoot > tr.danger > td,
+.table > thead > tr.danger > th,
+.table > tbody > tr.danger > th,
+.table > tfoot > tr.danger > th {
+ background-color: #f2dede;
+ border-color: #eed3d7;
+}
+.table-hover > tbody > tr > td.danger:hover,
+.table-hover > tbody > tr > th.danger:hover,
+.table-hover > tbody > tr.danger:hover > td {
+ background-color: #ebcccc;
+ border-color: #e6c1c7;
+}
+.table > thead > tr > td.warning,
+.table > tbody > tr > td.warning,
+.table > tfoot > tr > td.warning,
+.table > thead > tr > th.warning,
+.table > tbody > tr > th.warning,
+.table > tfoot > tr > th.warning,
+.table > thead > tr.warning > td,
+.table > tbody > tr.warning > td,
+.table > tfoot > tr.warning > td,
+.table > thead > tr.warning > th,
+.table > tbody > tr.warning > th,
+.table > tfoot > tr.warning > th {
+ background-color: #fcf8e3;
+ border-color: #fbeed5;
+}
+.table-hover > tbody > tr > td.warning:hover,
+.table-hover > tbody > tr > th.warning:hover,
+.table-hover > tbody > tr.warning:hover > td {
+ background-color: #faf2cc;
+ border-color: #f8e5be;
+}
+@media (max-width: 768px) {
+ .table-responsive {
+ width: 100%;
+ margin-bottom: 15px;
+ overflow-y: hidden;
+ overflow-x: scroll;
+ border: 1px solid #77777a;
+ }
+ .table-responsive > .table {
+ margin-bottom: 0;
+ background-color: #fff;
+ }
+ .table-responsive > .table > thead > tr > th,
+ .table-responsive > .table > tbody > tr > th,
+ .table-responsive > .table > tfoot > tr > th,
+ .table-responsive > .table > thead > tr > td,
+ .table-responsive > .table > tbody > tr > td,
+ .table-responsive > .table > tfoot > tr > td {
+ white-space: nowrap;
+ }
+ .table-responsive > .table-bordered {
+ border: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr > th:first-child,
+ .table-responsive > .table-bordered > tbody > tr > th:first-child,
+ .table-responsive > .table-bordered > tfoot > tr > th:first-child,
+ .table-responsive > .table-bordered > thead > tr > td:first-child,
+ .table-responsive > .table-bordered > tbody > tr > td:first-child,
+ .table-responsive > .table-bordered > tfoot > tr > td:first-child {
+ border-left: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr > th:last-child,
+ .table-responsive > .table-bordered > tbody > tr > th:last-child,
+ .table-responsive > .table-bordered > tfoot > tr > th:last-child,
+ .table-responsive > .table-bordered > thead > tr > td:last-child,
+ .table-responsive > .table-bordered > tbody > tr > td:last-child,
+ .table-responsive > .table-bordered > tfoot > tr > td:last-child {
+ border-right: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr:last-child > th,
+ .table-responsive > .table-bordered > tbody > tr:last-child > th,
+ .table-responsive > .table-bordered > tfoot > tr:last-child > th,
+ .table-responsive > .table-bordered > thead > tr:last-child > td,
+ .table-responsive > .table-bordered > tbody > tr:last-child > td,
+ .table-responsive > .table-bordered > tfoot > tr:last-child > td {
+ border-bottom: 0;
+ }
+}
+fieldset {
+ padding: 0;
+ margin: 0;
+ border: 0;
+}
+legend {
+ display: block;
+ width: 100%;
+ padding: 0;
+ margin-bottom: 20px;
+ font-size: 21px;
+ line-height: inherit;
+ color: #77777a;
+ border: 0;
+ border-bottom: 1px solid #e5e5e5;
+}
+label {
+ display: inline-block;
+ margin-bottom: 5px;
+ font-weight: bold;
+}
+input[type="search"] {
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
+}
+input[type="radio"],
+input[type="checkbox"] {
+ margin: 4px 0 0;
+ margin-top: 1px \9;
+ /* IE8-9 */
+
+ line-height: normal;
+}
+input[type="file"] {
+ display: block;
+}
+select[multiple],
+select[size] {
+ height: auto;
+}
+select optgroup {
+ font-size: inherit;
+ font-style: inherit;
+ font-family: inherit;
+}
+input[type="file"]:focus,
+input[type="radio"]:focus,
+input[type="checkbox"]:focus {
+ outline: thin dotted #333;
+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
+input[type="number"]::-webkit-outer-spin-button,
+input[type="number"]::-webkit-inner-spin-button {
+ height: auto;
+}
+.form-control:-moz-placeholder {
+ color: #f9faf9;
+}
+.form-control::-moz-placeholder {
+ color: #f9faf9;
+}
+.form-control:-ms-input-placeholder {
+ color: #f9faf9;
+}
+.form-control::-webkit-input-placeholder {
+ color: #f9faf9;
+}
+.form-control {
+ display: block;
+ width: 100%;
+ height: 34px;
+ padding: 6px 12px;
+ font-size: 14px;
+ line-height: 1.428571429;
+ color: #4aadd6;
+ vertical-align: middle;
+ background-color: #ffffff;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+ transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+}
+.form-control:focus {
+ border-color: #66afe9;
+ outline: 0;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+ box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.form-control[disabled],
+.form-control[readonly],
+fieldset[disabled] .form-control {
+ cursor: not-allowed;
+ background-color: #bac9c2;
+}
+textarea.form-control {
+ height: auto;
+}
+.form-group {
+ margin-bottom: 15px;
+}
+.radio,
+.checkbox {
+ display: block;
+ min-height: 20px;
+ margin-top: 10px;
+ margin-bottom: 10px;
+ padding-left: 20px;
+ vertical-align: middle;
+}
+.radio label,
+.checkbox label {
+ display: inline;
+ margin-bottom: 0;
+ font-weight: normal;
+ cursor: pointer;
+}
+.radio input[type="radio"],
+.radio-inline input[type="radio"],
+.checkbox input[type="checkbox"],
+.checkbox-inline input[type="checkbox"] {
+ float: left;
+ margin-left: -20px;
+}
+.radio + .radio,
+.checkbox + .checkbox {
+ margin-top: -5px;
+}
+.radio-inline,
+.checkbox-inline {
+ display: inline-block;
+ padding-left: 20px;
+ margin-bottom: 0;
+ vertical-align: middle;
+ font-weight: normal;
+ cursor: pointer;
+}
+.radio-inline + .radio-inline,
+.checkbox-inline + .checkbox-inline {
+ margin-top: 0;
+ margin-left: 10px;
+}
+input[type="radio"][disabled],
+input[type="checkbox"][disabled],
+.radio[disabled],
+.radio-inline[disabled],
+.checkbox[disabled],
+.checkbox-inline[disabled],
+fieldset[disabled] input[type="radio"],
+fieldset[disabled] input[type="checkbox"],
+fieldset[disabled] .radio,
+fieldset[disabled] .radio-inline,
+fieldset[disabled] .checkbox,
+fieldset[disabled] .checkbox-inline {
+ cursor: not-allowed;
+}
+.input-sm {
+ height: 30px;
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+select.input-sm {
+ height: 30px;
+ line-height: 30px;
+}
+textarea.input-sm {
+ height: auto;
+}
+.input-lg {
+ height: 45px;
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+select.input-lg {
+ height: 45px;
+ line-height: 45px;
+}
+textarea.input-lg {
+ height: auto;
+}
+.has-warning .help-block,
+.has-warning .control-label {
+ color: #c09853;
+}
+.has-warning .form-control {
+ border-color: #c09853;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-warning .form-control:focus {
+ border-color: #a47e3c;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #dbc59e;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #dbc59e;
+}
+.has-warning .input-group-addon {
+ color: #c09853;
+ border-color: #c09853;
+ background-color: #fcf8e3;
+}
+.has-error .help-block,
+.has-error .control-label {
+ color: #b94a48;
+}
+.has-error .form-control {
+ border-color: #b94a48;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-error .form-control:focus {
+ border-color: #953b39;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #d59392;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #d59392;
+}
+.has-error .input-group-addon {
+ color: #b94a48;
+ border-color: #b94a48;
+ background-color: #f2dede;
+}
+.has-success .help-block,
+.has-success .control-label {
+ color: #468847;
+}
+.has-success .form-control {
+ border-color: #468847;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-success .form-control:focus {
+ border-color: #356635;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #7aba7b;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #7aba7b;
+}
+.has-success .input-group-addon {
+ color: #468847;
+ border-color: #468847;
+ background-color: #dff0d8;
+}
+.form-control-static {
+ margin-bottom: 0;
+ padding-top: 7px;
+}
+.help-block {
+ display: block;
+ margin-top: 5px;
+ margin-bottom: 10px;
+ color: #b7b7b9;
+}
+@media (min-width: 768px) {
+ .form-inline .form-group {
+ display: inline-block;
+ margin-bottom: 0;
+ vertical-align: middle;
+ }
+ .form-inline .form-control {
+ display: inline-block;
+ }
+ .form-inline .radio,
+ .form-inline .checkbox {
+ display: inline-block;
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-left: 0;
+ }
+ .form-inline .radio input[type="radio"],
+ .form-inline .checkbox input[type="checkbox"] {
+ float: none;
+ margin-left: 0;
+ }
+}
+.form-horizontal .control-label,
+.form-horizontal .radio,
+.form-horizontal .checkbox,
+.form-horizontal .radio-inline,
+.form-horizontal .checkbox-inline {
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-top: 7px;
+}
+.form-horizontal .form-group {
+ margin-left: -15px;
+ margin-right: -15px;
+}
+.form-horizontal .form-group:before,
+.form-horizontal .form-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.form-horizontal .form-group:after {
+ clear: both;
+}
+.form-horizontal .form-group:before,
+.form-horizontal .form-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.form-horizontal .form-group:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .form-horizontal .control-label {
+ text-align: right;
+ }
+}
+.btn {
+ display: inline-block;
+ padding: 6px 12px;
+ margin-bottom: 0;
+ font-size: 14px;
+ font-weight: normal;
+ line-height: 1.428571429;
+ text-align: center;
+ vertical-align: middle;
+ cursor: pointer;
+ border: 1px solid transparent;
+ border-radius: 4px;
+ white-space: nowrap;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ -o-user-select: none;
+ user-select: none;
+}
+.btn:focus {
+ outline: thin dotted #333;
+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
+.btn:hover,
+.btn:focus {
+ color: #333333;
+ text-decoration: none;
+}
+.btn:active,
+.btn.active {
+ outline: 0;
+ background-image: none;
+ -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+ box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn.disabled,
+.btn[disabled],
+fieldset[disabled] .btn {
+ cursor: not-allowed;
+ pointer-events: none;
+ opacity: 0.65;
+ filter: alpha(opacity=65);
+ -webkit-box-shadow: none;
+ box-shadow: none;
+}
+.btn-default {
+ color: #333333;
+ background-color: #ffffff;
+ border-color: #cccccc;
+}
+.btn-default:hover,
+.btn-default:focus,
+.btn-default:active,
+.btn-default.active,
+.open .dropdown-toggle.btn-default {
+ color: #333333;
+ background-color: #ebebeb;
+ border-color: #adadad;
+}
+.btn-default:active,
+.btn-default.active,
+.open .dropdown-toggle.btn-default {
+ background-image: none;
+}
+.btn-default.disabled,
+.btn-default[disabled],
+fieldset[disabled] .btn-default,
+.btn-default.disabled:hover,
+.btn-default[disabled]:hover,
+fieldset[disabled] .btn-default:hover,
+.btn-default.disabled:focus,
+.btn-default[disabled]:focus,
+fieldset[disabled] .btn-default:focus,
+.btn-default.disabled:active,
+.btn-default[disabled]:active,
+fieldset[disabled] .btn-default:active,
+.btn-default.disabled.active,
+.btn-default[disabled].active,
+fieldset[disabled] .btn-default.active {
+ background-color: #ffffff;
+ border-color: #cccccc;
+}
+.btn-primary {
+ color: #ffffff;
+ background-color: #74ab50;
+ border-color: #689a48;
+}
+.btn-primary:hover,
+.btn-primary:focus,
+.btn-primary:active,
+.btn-primary.active,
+.open .dropdown-toggle.btn-primary {
+ color: #ffffff;
+ background-color: #618f43;
+ border-color: #4c7034;
+}
+.btn-primary:active,
+.btn-primary.active,
+.open .dropdown-toggle.btn-primary {
+ background-image: none;
+}
+.btn-primary.disabled,
+.btn-primary[disabled],
+fieldset[disabled] .btn-primary,
+.btn-primary.disabled:hover,
+.btn-primary[disabled]:hover,
+fieldset[disabled] .btn-primary:hover,
+.btn-primary.disabled:focus,
+.btn-primary[disabled]:focus,
+fieldset[disabled] .btn-primary:focus,
+.btn-primary.disabled:active,
+.btn-primary[disabled]:active,
+fieldset[disabled] .btn-primary:active,
+.btn-primary.disabled.active,
+.btn-primary[disabled].active,
+fieldset[disabled] .btn-primary.active {
+ background-color: #74ab50;
+ border-color: #689a48;
+}
+.btn-warning {
+ color: #ffffff;
+ background-color: #f0ad4e;
+ border-color: #eea236;
+}
+.btn-warning:hover,
+.btn-warning:focus,
+.btn-warning:active,
+.btn-warning.active,
+.open .dropdown-toggle.btn-warning {
+ color: #ffffff;
+ background-color: #ed9c28;
+ border-color: #d58512;
+}
+.btn-warning:active,
+.btn-warning.active,
+.open .dropdown-toggle.btn-warning {
+ background-image: none;
+}
+.btn-warning.disabled,
+.btn-warning[disabled],
+fieldset[disabled] .btn-warning,
+.btn-warning.disabled:hover,
+.btn-warning[disabled]:hover,
+fieldset[disabled] .btn-warning:hover,
+.btn-warning.disabled:focus,
+.btn-warning[disabled]:focus,
+fieldset[disabled] .btn-warning:focus,
+.btn-warning.disabled:active,
+.btn-warning[disabled]:active,
+fieldset[disabled] .btn-warning:active,
+.btn-warning.disabled.active,
+.btn-warning[disabled].active,
+fieldset[disabled] .btn-warning.active {
+ background-color: #f0ad4e;
+ border-color: #eea236;
+}
+.btn-danger {
+ color: #ffffff;
+ background-color: #d9534f;
+ border-color: #d43f3a;
+}
+.btn-danger:hover,
+.btn-danger:focus,
+.btn-danger:active,
+.btn-danger.active,
+.open .dropdown-toggle.btn-danger {
+ color: #ffffff;
+ background-color: #d2322d;
+ border-color: #ac2925;
+}
+.btn-danger:active,
+.btn-danger.active,
+.open .dropdown-toggle.btn-danger {
+ background-image: none;
+}
+.btn-danger.disabled,
+.btn-danger[disabled],
+fieldset[disabled] .btn-danger,
+.btn-danger.disabled:hover,
+.btn-danger[disabled]:hover,
+fieldset[disabled] .btn-danger:hover,
+.btn-danger.disabled:focus,
+.btn-danger[disabled]:focus,
+fieldset[disabled] .btn-danger:focus,
+.btn-danger.disabled:active,
+.btn-danger[disabled]:active,
+fieldset[disabled] .btn-danger:active,
+.btn-danger.disabled.active,
+.btn-danger[disabled].active,
+fieldset[disabled] .btn-danger.active {
+ background-color: #d9534f;
+ border-color: #d43f3a;
+}
+.btn-success {
+ color: #ffffff;
+ background-color: #5cb85c;
+ border-color: #4cae4c;
+}
+.btn-success:hover,
+.btn-success:focus,
+.btn-success:active,
+.btn-success.active,
+.open .dropdown-toggle.btn-success {
+ color: #ffffff;
+ background-color: #47a447;
+ border-color: #398439;
+}
+.btn-success:active,
+.btn-success.active,
+.open .dropdown-toggle.btn-success {
+ background-image: none;
+}
+.btn-success.disabled,
+.btn-success[disabled],
+fieldset[disabled] .btn-success,
+.btn-success.disabled:hover,
+.btn-success[disabled]:hover,
+fieldset[disabled] .btn-success:hover,
+.btn-success.disabled:focus,
+.btn-success[disabled]:focus,
+fieldset[disabled] .btn-success:focus,
+.btn-success.disabled:active,
+.btn-success[disabled]:active,
+fieldset[disabled] .btn-success:active,
+.btn-success.disabled.active,
+.btn-success[disabled].active,
+fieldset[disabled] .btn-success.active {
+ background-color: #5cb85c;
+ border-color: #4cae4c;
+}
+.btn-info {
+ color: #ffffff;
+ background-color: #347DBE;
+ border-color: #347DBE;
+}
+.btn-info:hover,
+.btn-info:focus,
+.btn-info:active,
+.btn-info.active,
+.open .dropdown-toggle.btn-info {
+ color: #ffffff;
+ background-color: #015CAE;
+ border-color: #015CAE;
+}
+.btn-info:active,
+.btn-info.active,
+.open .dropdown-toggle.btn-info {
+ background-image: none;
+}
+.btn-info.disabled,
+.btn-info[disabled],
+fieldset[disabled] .btn-info,
+.btn-info.disabled:hover,
+.btn-info[disabled]:hover,
+fieldset[disabled] .btn-info:hover,
+.btn-info.disabled:focus,
+.btn-info[disabled]:focus,
+fieldset[disabled] .btn-info:focus,
+.btn-info.disabled:active,
+.btn-info[disabled]:active,
+fieldset[disabled] .btn-info:active,
+.btn-info.disabled.active,
+.btn-info[disabled].active,
+fieldset[disabled] .btn-info.active {
+ background-color: #5bc0de;
+ border-color: #46b8da;
+}
+.btn-link {
+ color: #74ab50;
+ font-weight: normal;
+ cursor: pointer;
+ border-radius: 0;
+}
+.btn-link,
+.btn-link:active,
+.btn-link[disabled],
+fieldset[disabled] .btn-link {
+ background-color: transparent;
+ -webkit-box-shadow: none;
+ box-shadow: none;
+}
+.btn-link,
+.btn-link:hover,
+.btn-link:focus,
+.btn-link:active {
+ border-color: transparent;
+}
+.btn-link:hover,
+.btn-link:focus {
+ color: #517738;
+ text-decoration: underline;
+ background-color: transparent;
+}
+.btn-link[disabled]:hover,
+fieldset[disabled] .btn-link:hover,
+.btn-link[disabled]:focus,
+fieldset[disabled] .btn-link:focus {
+ color: #f9faf9;
+ text-decoration: none;
+}
+.btn-lg {
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+.btn-sm,
+.btn-xs {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+.btn-xs {
+ padding: 1px 5px;
+}
+.btn-block {
+ display: block;
+ width: 100%;
+ padding-left: 0;
+ padding-right: 0;
+}
+.btn-block + .btn-block {
+ margin-top: 5px;
+}
+input[type="submit"].btn-block,
+input[type="reset"].btn-block,
+input[type="button"].btn-block {
+ width: 100%;
+}
+.fade {
+ opacity: 0;
+ -webkit-transition: opacity 0.15s linear;
+ transition: opacity 0.15s linear;
+}
+.fade.in {
+ opacity: 1;
+}
+.collapse {
+ display: none;
+}
+.collapse.in {
+ display: block;
+}
+.collapsing {
+ position: relative;
+ height: 0;
+ overflow: hidden;
+ -webkit-transition: height 0.35s ease;
+ transition: height 0.35s ease;
+}
+@font-face {
+ font-family: 'Glyphicons Halflings';
+ src: url('../fonts/glyphicons-halflings-regular.eot');
+ src: url('../fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../fonts/glyphicons-halflings-regular.woff') format('woff'), url('../fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../fonts/glyphicons-halflings-regular.svg#glyphicons-halflingsregular') format('svg');
+}
+.glyphicon {
+ position: relative;
+ top: 1px;
+ display: inline-block;
+ font-family: 'Glyphicons Halflings';
+ font-style: normal;
+ font-weight: normal;
+ line-height: 1;
+ -webkit-font-smoothing: antialiased;
+}
+.glyphicon-asterisk:before {
+ content: "\2a";
+}
+.glyphicon-plus:before {
+ content: "\2b";
+}
+.glyphicon-euro:before {
+ content: "\20ac";
+}
+.glyphicon-minus:before {
+ content: "\2212";
+}
+.glyphicon-cloud:before {
+ content: "\2601";
+}
+.glyphicon-envelope:before {
+ content: "\2709";
+}
+.glyphicon-pencil:before {
+ content: "\270f";
+}
+.glyphicon-glass:before {
+ content: "\e001";
+}
+.glyphicon-music:before {
+ content: "\e002";
+}
+.glyphicon-search:before {
+ content: "\e003";
+}
+.glyphicon-heart:before {
+ content: "\e005";
+}
+.glyphicon-star:before {
+ content: "\e006";
+}
+.glyphicon-star-empty:before {
+ content: "\e007";
+}
+.glyphicon-user:before {
+ content: "\e008";
+}
+.glyphicon-film:before {
+ content: "\e009";
+}
+.glyphicon-th-large:before {
+ content: "\e010";
+}
+.glyphicon-th:before {
+ content: "\e011";
+}
+.glyphicon-th-list:before {
+ content: "\e012";
+}
+.glyphicon-ok:before {
+ content: "\e013";
+}
+.glyphicon-remove:before {
+ content: "\e014";
+}
+.glyphicon-zoom-in:before {
+ content: "\e015";
+}
+.glyphicon-zoom-out:before {
+ content: "\e016";
+}
+.glyphicon-off:before {
+ content: "\e017";
+}
+.glyphicon-signal:before {
+ content: "\e018";
+}
+.glyphicon-cog:before {
+ content: "\e019";
+}
+.glyphicon-trash:before {
+ content: "\e020";
+}
+.glyphicon-home:before {
+ content: "\e021";
+}
+.glyphicon-file:before {
+ content: "\e022";
+}
+.glyphicon-time:before {
+ content: "\e023";
+}
+.glyphicon-road:before {
+ content: "\e024";
+}
+.glyphicon-download-alt:before {
+ content: "\e025";
+}
+.glyphicon-download:before {
+ content: "\e026";
+}
+.glyphicon-upload:before {
+ content: "\e027";
+}
+.glyphicon-inbox:before {
+ content: "\e028";
+}
+.glyphicon-play-circle:before {
+ content: "\e029";
+}
+.glyphicon-repeat:before {
+ content: "\e030";
+}
+.glyphicon-refresh:before {
+ content: "\e031";
+}
+.glyphicon-list-alt:before {
+ content: "\e032";
+}
+.glyphicon-flag:before {
+ content: "\e034";
+}
+.glyphicon-headphones:before {
+ content: "\e035";
+}
+.glyphicon-volume-off:before {
+ content: "\e036";
+}
+.glyphicon-volume-down:before {
+ content: "\e037";
+}
+.glyphicon-volume-up:before {
+ content: "\e038";
+}
+.glyphicon-qrcode:before {
+ content: "\e039";
+}
+.glyphicon-barcode:before {
+ content: "\e040";
+}
+.glyphicon-tag:before {
+ content: "\e041";
+}
+.glyphicon-tags:before {
+ content: "\e042";
+}
+.glyphicon-book:before {
+ content: "\e043";
+}
+.glyphicon-print:before {
+ content: "\e045";
+}
+.glyphicon-font:before {
+ content: "\e047";
+}
+.glyphicon-bold:before {
+ content: "\e048";
+}
+.glyphicon-italic:before {
+ content: "\e049";
+}
+.glyphicon-text-height:before {
+ content: "\e050";
+}
+.glyphicon-text-width:before {
+ content: "\e051";
+}
+.glyphicon-align-left:before {
+ content: "\e052";
+}
+.glyphicon-align-center:before {
+ content: "\e053";
+}
+.glyphicon-align-right:before {
+ content: "\e054";
+}
+.glyphicon-align-justify:before {
+ content: "\e055";
+}
+.glyphicon-list:before {
+ content: "\e056";
+}
+.glyphicon-indent-left:before {
+ content: "\e057";
+}
+.glyphicon-indent-right:before {
+ content: "\e058";
+}
+.glyphicon-facetime-video:before {
+ content: "\e059";
+}
+.glyphicon-picture:before {
+ content: "\e060";
+}
+.glyphicon-map-marker:before {
+ content: "\e062";
+}
+.glyphicon-adjust:before {
+ content: "\e063";
+}
+.glyphicon-tint:before {
+ content: "\e064";
+}
+.glyphicon-edit:before {
+ content: "\e065";
+}
+.glyphicon-share:before {
+ content: "\e066";
+}
+.glyphicon-check:before {
+ content: "\e067";
+}
+.glyphicon-move:before {
+ content: "\e068";
+}
+.glyphicon-step-backward:before {
+ content: "\e069";
+}
+.glyphicon-fast-backward:before {
+ content: "\e070";
+}
+.glyphicon-backward:before {
+ content: "\e071";
+}
+.glyphicon-play:before {
+ content: "\e072";
+}
+.glyphicon-pause:before {
+ content: "\e073";
+}
+.glyphicon-stop:before {
+ content: "\e074";
+}
+.glyphicon-forward:before {
+ content: "\e075";
+}
+.glyphicon-fast-forward:before {
+ content: "\e076";
+}
+.glyphicon-step-forward:before {
+ content: "\e077";
+}
+.glyphicon-eject:before {
+ content: "\e078";
+}
+.glyphicon-chevron-left:before {
+ content: "\e079";
+}
+.glyphicon-chevron-right:before {
+ content: "\e080";
+}
+.glyphicon-plus-sign:before {
+ content: "\e081";
+}
+.glyphicon-minus-sign:before {
+ content: "\e082";
+}
+.glyphicon-remove-sign:before {
+ content: "\e083";
+}
+.glyphicon-ok-sign:before {
+ content: "\e084";
+}
+.glyphicon-question-sign:before {
+ content: "\e085";
+}
+.glyphicon-info-sign:before {
+ content: "\e086";
+}
+.glyphicon-screenshot:before {
+ content: "\e087";
+}
+.glyphicon-remove-circle:before {
+ content: "\e088";
+}
+.glyphicon-ok-circle:before {
+ content: "\e089";
+}
+.glyphicon-ban-circle:before {
+ content: "\e090";
+}
+.glyphicon-arrow-left:before {
+ content: "\e091";
+}
+.glyphicon-arrow-right:before {
+ content: "\e092";
+}
+.glyphicon-arrow-up:before {
+ content: "\e093";
+}
+.glyphicon-arrow-down:before {
+ content: "\e094";
+}
+.glyphicon-share-alt:before {
+ content: "\e095";
+}
+.glyphicon-resize-full:before {
+ content: "\e096";
+}
+.glyphicon-resize-small:before {
+ content: "\e097";
+}
+.glyphicon-exclamation-sign:before {
+ content: "\e101";
+}
+.glyphicon-gift:before {
+ content: "\e102";
+}
+.glyphicon-leaf:before {
+ content: "\e103";
+}
+.glyphicon-eye-open:before {
+ content: "\e105";
+}
+.glyphicon-eye-close:before {
+ content: "\e106";
+}
+.glyphicon-warning-sign:before {
+ content: "\e107";
+}
+.glyphicon-plane:before {
+ content: "\e108";
+}
+.glyphicon-random:before {
+ content: "\e110";
+}
+.glyphicon-comment:before {
+ content: "\e111";
+}
+.glyphicon-magnet:before {
+ content: "\e112";
+}
+.glyphicon-chevron-up:before {
+ content: "\e113";
+}
+.glyphicon-chevron-down:before {
+ content: "\e114";
+}
+.glyphicon-retweet:before {
+ content: "\e115";
+}
+.glyphicon-shopping-cart:before {
+ content: "\e116";
+}
+.glyphicon-folder-close:before {
+ content: "\e117";
+}
+.glyphicon-folder-open:before {
+ content: "\e118";
+}
+.glyphicon-resize-vertical:before {
+ content: "\e119";
+}
+.glyphicon-resize-horizontal:before {
+ content: "\e120";
+}
+.glyphicon-hdd:before {
+ content: "\e121";
+}
+.glyphicon-bullhorn:before {
+ content: "\e122";
+}
+.glyphicon-certificate:before {
+ content: "\e124";
+}
+.glyphicon-thumbs-up:before {
+ content: "\e125";
+}
+.glyphicon-thumbs-down:before {
+ content: "\e126";
+}
+.glyphicon-hand-right:before {
+ content: "\e127";
+}
+.glyphicon-hand-left:before {
+ content: "\e128";
+}
+.glyphicon-hand-up:before {
+ content: "\e129";
+}
+.glyphicon-hand-down:before {
+ content: "\e130";
+}
+.glyphicon-circle-arrow-right:before {
+ content: "\e131";
+}
+.glyphicon-circle-arrow-left:before {
+ content: "\e132";
+}
+.glyphicon-circle-arrow-up:before {
+ content: "\e133";
+}
+.glyphicon-circle-arrow-down:before {
+ content: "\e134";
+}
+.glyphicon-globe:before {
+ content: "\e135";
+}
+.glyphicon-tasks:before {
+ content: "\e137";
+}
+.glyphicon-filter:before {
+ content: "\e138";
+}
+.glyphicon-fullscreen:before {
+ content: "\e140";
+}
+.glyphicon-dashboard:before {
+ content: "\e141";
+}
+.glyphicon-heart-empty:before {
+ content: "\e143";
+}
+.glyphicon-link:before {
+ content: "\e144";
+}
+.glyphicon-phone:before {
+ content: "\e145";
+}
+.glyphicon-usd:before {
+ content: "\e148";
+}
+.glyphicon-gbp:before {
+ content: "\e149";
+}
+.glyphicon-sort:before {
+ content: "\e150";
+}
+.glyphicon-sort-by-alphabet:before {
+ content: "\e151";
+}
+.glyphicon-sort-by-alphabet-alt:before {
+ content: "\e152";
+}
+.glyphicon-sort-by-order:before {
+ content: "\e153";
+}
+.glyphicon-sort-by-order-alt:before {
+ content: "\e154";
+}
+.glyphicon-sort-by-attributes:before {
+ content: "\e155";
+}
+.glyphicon-sort-by-attributes-alt:before {
+ content: "\e156";
+}
+.glyphicon-unchecked:before {
+ content: "\e157";
+}
+.glyphicon-expand:before {
+ content: "\e158";
+}
+.glyphicon-collapse-down:before {
+ content: "\e159";
+}
+.glyphicon-collapse-up:before {
+ content: "\e160";
+}
+.glyphicon-log-in:before {
+ content: "\e161";
+}
+.glyphicon-flash:before {
+ content: "\e162";
+}
+.glyphicon-log-out:before {
+ content: "\e163";
+}
+.glyphicon-new-window:before {
+ content: "\e164";
+}
+.glyphicon-record:before {
+ content: "\e165";
+}
+.glyphicon-save:before {
+ content: "\e166";
+}
+.glyphicon-open:before {
+ content: "\e167";
+}
+.glyphicon-saved:before {
+ content: "\e168";
+}
+.glyphicon-import:before {
+ content: "\e169";
+}
+.glyphicon-export:before {
+ content: "\e170";
+}
+.glyphicon-send:before {
+ content: "\e171";
+}
+.glyphicon-floppy-disk:before {
+ content: "\e172";
+}
+.glyphicon-floppy-saved:before {
+ content: "\e173";
+}
+.glyphicon-floppy-remove:before {
+ content: "\e174";
+}
+.glyphicon-floppy-save:before {
+ content: "\e175";
+}
+.glyphicon-floppy-open:before {
+ content: "\e176";
+}
+.glyphicon-credit-card:before {
+ content: "\e177";
+}
+.glyphicon-transfer:before {
+ content: "\e178";
+}
+.glyphicon-cutlery:before {
+ content: "\e179";
+}
+.glyphicon-header:before {
+ content: "\e180";
+}
+.glyphicon-compressed:before {
+ content: "\e181";
+}
+.glyphicon-earphone:before {
+ content: "\e182";
+}
+.glyphicon-phone-alt:before {
+ content: "\e183";
+}
+.glyphicon-tower:before {
+ content: "\e184";
+}
+.glyphicon-stats:before {
+ content: "\e185";
+}
+.glyphicon-sd-video:before {
+ content: "\e186";
+}
+.glyphicon-hd-video:before {
+ content: "\e187";
+}
+.glyphicon-subtitles:before {
+ content: "\e188";
+}
+.glyphicon-sound-stereo:before {
+ content: "\e189";
+}
+.glyphicon-sound-dolby:before {
+ content: "\e190";
+}
+.glyphicon-sound-5-1:before {
+ content: "\e191";
+}
+.glyphicon-sound-6-1:before {
+ content: "\e192";
+}
+.glyphicon-sound-7-1:before {
+ content: "\e193";
+}
+.glyphicon-copyright-mark:before {
+ content: "\e194";
+}
+.glyphicon-registration-mark:before {
+ content: "\e195";
+}
+.glyphicon-cloud-download:before {
+ content: "\e197";
+}
+.glyphicon-cloud-upload:before {
+ content: "\e198";
+}
+.glyphicon-tree-conifer:before {
+ content: "\e199";
+}
+.glyphicon-tree-deciduous:before {
+ content: "\e200";
+}
+.glyphicon-briefcase:before {
+ content: "\1f4bc";
+}
+.glyphicon-calendar:before {
+ content: "\1f4c5";
+}
+.glyphicon-pushpin:before {
+ content: "\1f4cc";
+}
+.glyphicon-paperclip:before {
+ content: "\1f4ce";
+}
+.glyphicon-camera:before {
+ content: "\1f4f7";
+}
+.glyphicon-lock:before {
+ content: "\1f512";
+}
+.glyphicon-bell:before {
+ content: "\1f514";
+}
+.glyphicon-bookmark:before {
+ content: "\1f516";
+}
+.glyphicon-fire:before {
+ content: "\1f525";
+}
+.glyphicon-wrench:before {
+ content: "\1f527";
+}
+.caret {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 2px;
+ vertical-align: middle;
+ border-top: 4px solid #000000;
+ border-right: 4px solid transparent;
+ border-left: 4px solid transparent;
+ border-bottom: 0 dotted;
+ content: "";
+}
+.dropdown {
+ position: relative;
+}
+.dropdown-toggle:focus {
+ outline: 0;
+}
+.dropdown-menu {
+ position: absolute;
+ top: 100%;
+ left: 0;
+ z-index: 1000;
+ display: none;
+ float: left;
+ min-width: 160px;
+ padding: 5px 0;
+ margin: 2px 0 0;
+ list-style: none;
+ font-size: 14px;
+ background-color: #ffffff;
+ border: 1px solid #cccccc;
+ border: 1px solid rgba(0, 0, 0, 0.15);
+ border-radius: 4px;
+ -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+ box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+ background-clip: padding-box;
+}
+.dropdown-menu.pull-right {
+ right: 0;
+ left: auto;
+}
+.dropdown-menu .divider {
+ height: 1px;
+ margin: 9px 0;
+ overflow: hidden;
+ background-color: #e5e5e5;
+}
+.dropdown-menu > li > a {
+ display: block;
+ padding: 3px 20px;
+ clear: both;
+ font-weight: normal;
+ line-height: 1.428571429;
+ color: #77777a;
+ white-space: nowrap;
+}
+.dropdown-menu > li > a:hover,
+.dropdown-menu > li > a:focus {
+ text-decoration: none;
+ color: #ffffff;
+ background-color: #679DCE;
+}
+.dropdown-menu > .active > a,
+.dropdown-menu > .active > a:hover,
+.dropdown-menu > .active > a:focus {
+ color: #ffffff;
+ text-decoration: none;
+ outline: 0;
+ background-color: #679DCE;
+}
+.dropdown-menu > .disabled > a,
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+ color: #f9faf9;
+}
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+ text-decoration: none;
+ background-color: transparent;
+ background-image: none;
+ filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+ cursor: not-allowed;
+}
+.open > .dropdown-menu {
+ display: block;
+}
+.open > a {
+ outline: 0;
+}
+.dropdown-header {
+ display: block;
+ padding: 3px 20px;
+ font-size: 12px;
+ line-height: 1.428571429;
+ color: #f9faf9;
+}
+.dropdown-backdrop {
+ position: fixed;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ top: 0;
+ z-index: 990;
+}
+.pull-right > .dropdown-menu {
+ right: 0;
+ left: auto;
+}
+.dropup .caret,
+.navbar-fixed-bottom .dropdown .caret {
+ border-top: 0 dotted;
+ border-bottom: 4px solid #000000;
+ content: "";
+}
+.dropup .dropdown-menu,
+.navbar-fixed-bottom .dropdown .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ margin-bottom: 1px;
+}
+@media (min-width: 768px) {
+ .navbar-right .dropdown-menu {
+ right: 0;
+ left: auto;
+ }
+}
+.btn-default .caret {
+ border-top-color: #333333;
+}
+.btn-primary .caret,
+.btn-success .caret,
+.btn-warning .caret,
+.btn-danger .caret,
+.btn-info .caret {
+ border-top-color: #fff;
+}
+.dropup .btn-default .caret {
+ border-bottom-color: #333333;
+}
+.dropup .btn-primary .caret,
+.dropup .btn-success .caret,
+.dropup .btn-warning .caret,
+.dropup .btn-danger .caret,
+.dropup .btn-info .caret {
+ border-bottom-color: #fff;
+}
+.btn-group,
+.btn-group-vertical {
+ position: relative;
+ display: inline-block;
+ vertical-align: middle;
+}
+.btn-group > .btn,
+.btn-group-vertical > .btn {
+ position: relative;
+ float: left;
+}
+.btn-group > .btn:hover,
+.btn-group-vertical > .btn:hover,
+.btn-group > .btn:focus,
+.btn-group-vertical > .btn:focus,
+.btn-group > .btn:active,
+.btn-group-vertical > .btn:active,
+.btn-group > .btn.active,
+.btn-group-vertical > .btn.active {
+ z-index: 2;
+}
+.btn-group > .btn:focus,
+.btn-group-vertical > .btn:focus {
+ outline: none;
+}
+.btn-group .btn + .btn,
+.btn-group .btn + .btn-group,
+.btn-group .btn-group + .btn,
+.btn-group .btn-group + .btn-group {
+ margin-left: -1px;
+}
+.btn-toolbar:before,
+.btn-toolbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-toolbar:after {
+ clear: both;
+}
+.btn-toolbar:before,
+.btn-toolbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-toolbar:after {
+ clear: both;
+}
+.btn-toolbar .btn-group {
+ float: left;
+}
+.btn-toolbar > .btn + .btn,
+.btn-toolbar > .btn-group + .btn,
+.btn-toolbar > .btn + .btn-group,
+.btn-toolbar > .btn-group + .btn-group {
+ margin-left: 5px;
+}
+.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
+ border-radius: 0;
+}
+.btn-group > .btn:first-child {
+ margin-left: 0;
+}
+.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.btn-group > .btn:last-child:not(:first-child),
+.btn-group > .dropdown-toggle:not(:first-child) {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group > .btn-group {
+ float: left;
+}
+.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
+ border-radius: 0;
+}
+.btn-group > .btn-group:first-child > .btn:last-child,
+.btn-group > .btn-group:first-child > .dropdown-toggle {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.btn-group > .btn-group:last-child > .btn:first-child {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group .dropdown-toggle:active,
+.btn-group.open .dropdown-toggle {
+ outline: 0;
+}
+.btn-group-xs > .btn {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+ padding: 1px 5px;
+}
+.btn-group-sm > .btn {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+.btn-group-lg > .btn {
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+.btn-group > .btn + .dropdown-toggle {
+ padding-left: 8px;
+ padding-right: 8px;
+}
+.btn-group > .btn-lg + .dropdown-toggle {
+ padding-left: 12px;
+ padding-right: 12px;
+}
+.btn-group.open .dropdown-toggle {
+ -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+ box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn .caret {
+ margin-left: 0;
+}
+.btn-lg .caret {
+ border-width: 5px 5px 0;
+ border-bottom-width: 0;
+}
+.dropup .btn-lg .caret {
+ border-width: 0 5px 5px;
+}
+.btn-group-vertical > .btn,
+.btn-group-vertical > .btn-group {
+ display: block;
+ float: none;
+ width: 100%;
+ max-width: 100%;
+}
+.btn-group-vertical > .btn-group:before,
+.btn-group-vertical > .btn-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-group-vertical > .btn-group:after {
+ clear: both;
+}
+.btn-group-vertical > .btn-group:before,
+.btn-group-vertical > .btn-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-group-vertical > .btn-group:after {
+ clear: both;
+}
+.btn-group-vertical > .btn-group > .btn {
+ float: none;
+}
+.btn-group-vertical > .btn + .btn,
+.btn-group-vertical > .btn + .btn-group,
+.btn-group-vertical > .btn-group + .btn,
+.btn-group-vertical > .btn-group + .btn-group {
+ margin-top: -1px;
+ margin-left: 0;
+}
+.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
+ border-radius: 0;
+}
+.btn-group-vertical > .btn:first-child:not(:last-child) {
+ border-top-right-radius: 4px;
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn:last-child:not(:first-child) {
+ border-bottom-left-radius: 4px;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
+ border-radius: 0;
+}
+.btn-group-vertical > .btn-group:first-child > .btn:last-child,
+.btn-group-vertical > .btn-group:first-child > .dropdown-toggle {
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn-group:last-child > .btn:first-child {
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group-justified {
+ display: table;
+ width: 100%;
+ table-layout: fixed;
+ border-collapse: separate;
+}
+.btn-group-justified .btn {
+ float: none;
+ display: table-cell;
+ width: 1%;
+}
+[data-toggle="buttons"] > .btn > input[type="radio"],
+[data-toggle="buttons"] > .btn > input[type="checkbox"] {
+ display: none;
+}
+.input-group {
+ position: relative;
+ display: table;
+ border-collapse: separate;
+}
+.input-group.col {
+ float: none;
+ padding-left: 0;
+ padding-right: 0;
+}
+.input-group .form-control {
+ width: 100%;
+ margin-bottom: 0;
+}
+.input-group-lg > .form-control,
+.input-group-lg > .input-group-addon,
+.input-group-lg > .input-group-btn > .btn {
+ height: 45px;
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+select.input-group-lg > .form-control,
+select.input-group-lg > .input-group-addon,
+select.input-group-lg > .input-group-btn > .btn {
+ height: 45px;
+ line-height: 45px;
+}
+textarea.input-group-lg > .form-control,
+textarea.input-group-lg > .input-group-addon,
+textarea.input-group-lg > .input-group-btn > .btn {
+ height: auto;
+}
+.input-group-sm > .form-control,
+.input-group-sm > .input-group-addon,
+.input-group-sm > .input-group-btn > .btn {
+ height: 30px;
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+select.input-group-sm > .form-control,
+select.input-group-sm > .input-group-addon,
+select.input-group-sm > .input-group-btn > .btn {
+ height: 30px;
+ line-height: 30px;
+}
+textarea.input-group-sm > .form-control,
+textarea.input-group-sm > .input-group-addon,
+textarea.input-group-sm > .input-group-btn > .btn {
+ height: auto;
+}
+.input-group-addon,
+.input-group-btn,
+.input-group .form-control {
+ display: table-cell;
+}
+.input-group-addon:not(:first-child):not(:last-child),
+.input-group-btn:not(:first-child):not(:last-child),
+.input-group .form-control:not(:first-child):not(:last-child) {
+ border-radius: 0;
+}
+.input-group-addon,
+.input-group-btn {
+ width: 1%;
+ white-space: nowrap;
+ vertical-align: middle;
+}
+.input-group-addon {
+ padding: 6px 12px;
+ font-size: 14px;
+ font-weight: normal;
+ line-height: 1;
+ text-align: center;
+ background-color: #bac9c2;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+}
+.input-group-addon.input-sm {
+ padding: 5px 10px;
+ font-size: 12px;
+ border-radius: 3px;
+}
+.input-group-addon.input-lg {
+ padding: 10px 16px;
+ font-size: 18px;
+ border-radius: 6px;
+}
+.input-group-addon input[type="radio"],
+.input-group-addon input[type="checkbox"] {
+ margin-top: 0;
+}
+.input-group .form-control:first-child,
+.input-group-addon:first-child,
+.input-group-btn:first-child > .btn,
+.input-group-btn:first-child > .dropdown-toggle,
+.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle) {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.input-group-addon:first-child {
+ border-right: 0;
+}
+.input-group .form-control:last-child,
+.input-group-addon:last-child,
+.input-group-btn:last-child > .btn,
+.input-group-btn:last-child > .dropdown-toggle,
+.input-group-btn:first-child > .btn:not(:first-child) {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.input-group-addon:last-child {
+ border-left: 0;
+}
+.input-group-btn {
+ position: relative;
+ white-space: nowrap;
+}
+.input-group-btn > .btn {
+ position: relative;
+}
+.input-group-btn > .btn + .btn {
+ margin-left: -4px;
+}
+.input-group-btn > .btn:hover,
+.input-group-btn > .btn:active {
+ z-index: 2;
+}
+.nav {
+ margin-bottom: 0;
+ padding-left: 0;
+ list-style: none;
+}
+.nav:before,
+.nav:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.nav:after {
+ clear: both;
+}
+.nav:before,
+.nav:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.nav:after {
+ clear: both;
+}
+.nav > li {
+ position: relative;
+ display: block;
+}
+.nav > li > a {
+ position: relative;
+ display: block;
+ padding: 10px 15px;
+}
+.nav > li > a:hover,
+.nav > li > a:focus {
+ text-decoration: none;
+ background-color: #bac9c2;
+}
+.nav > li.disabled > a {
+ color: #f9faf9;
+}
+.nav > li.disabled > a:hover,
+.nav > li.disabled > a:focus {
+ color: #f9faf9;
+ text-decoration: none;
+ background-color: transparent;
+ cursor: not-allowed;
+}
+.nav .open > a,
+.nav .open > a:hover,
+.nav .open > a:focus {
+ background-color: #bac9c2;
+ border-color: #74ab50;
+}
+.nav .nav-divider {
+ height: 1px;
+ margin: 9px 0;
+ overflow: hidden;
+ background-color: #e5e5e5;
+}
+.nav > li > a > img {
+ max-width: none;
+}
+.nav-tabs {
+ border-bottom: 1px solid #dddddd;
+}
+.nav-tabs > li {
+ float: left;
+ margin-bottom: -1px;
+}
+.nav-tabs > li > a {
+ margin-right: 2px;
+ line-height: 1.428571429;
+ border: 1px solid transparent;
+ border-radius: 4px 4px 0 0;
+}
+.nav-tabs > li > a:hover {
+ border-color: #bac9c2 #bac9c2 #dddddd;
+}
+.nav-tabs > li.active > a,
+.nav-tabs > li.active > a:hover,
+.nav-tabs > li.active > a:focus {
+ color: #4aadd6;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-bottom-color: transparent;
+ cursor: default;
+}
+.nav-tabs.nav-justified {
+ width: 100%;
+ border-bottom: 0;
+}
+.nav-tabs.nav-justified > li {
+ float: none;
+}
+.nav-tabs.nav-justified > li > a {
+ text-align: center;
+}
+@media (min-width: 768px) {
+ .nav-tabs.nav-justified > li {
+ display: table-cell;
+ width: 1%;
+ }
+}
+.nav-tabs.nav-justified > li > a {
+ border-bottom: 1px solid #dddddd;
+ margin-right: 0;
+}
+.nav-tabs.nav-justified > .active > a {
+ border-bottom-color: #ffffff;
+}
+.nav-pills > li {
+ float: left;
+}
+.nav-pills > li > a {
+ border-radius: 5px;
+}
+.nav-pills > li + li {
+ margin-left: 2px;
+}
+.nav-pills > li.active > a,
+.nav-pills > li.active > a:hover,
+.nav-pills > li.active > a:focus {
+ color: #ffffff;
+ background-color: #74ab50;
+}
+.nav-stacked > li {
+ float: none;
+}
+.nav-stacked > li + li {
+ margin-top: 2px;
+ margin-left: 0;
+}
+.nav-justified {
+ width: 100%;
+}
+.nav-justified > li {
+ float: none;
+}
+.nav-justified > li > a {
+ text-align: center;
+}
+@media (min-width: 768px) {
+ .nav-justified > li {
+ display: table-cell;
+ width: 1%;
+ }
+}
+.nav-tabs-justified {
+ border-bottom: 0;
+}
+.nav-tabs-justified > li > a {
+ border-bottom: 1px solid #dddddd;
+ margin-right: 0;
+}
+.nav-tabs-justified > .active > a {
+ border-bottom-color: #ffffff;
+}
+.tabbable:before,
+.tabbable:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.tabbable:after {
+ clear: both;
+}
+.tabbable:before,
+.tabbable:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.tabbable:after {
+ clear: both;
+}
+.tab-content > .tab-pane,
+.pill-content > .pill-pane {
+ display: none;
+}
+.tab-content > .active,
+.pill-content > .active {
+ display: block;
+}
+.nav .caret {
+ border-top-color: #74ab50;
+ border-bottom-color: #74ab50;
+}
+.nav a:hover .caret {
+ border-top-color: #517738;
+ border-bottom-color: #517738;
+}
+.nav-tabs .dropdown-menu {
+ margin-top: -1px;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.navbar {
+ position: relative;
+ z-index: 1000;
+ min-height: 50px;
+ margin-bottom: 20px;
+ border: 1px solid transparent;
+ background-color: white
+}
+.navbar:before,
+.navbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar:after {
+ clear: both;
+}
+.navbar:before,
+.navbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .navbar {
+ border-radius: 4px;
+ }
+}
+.navbar-header:before,
+.navbar-header:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-header:after {
+ clear: both;
+}
+.navbar-header:before,
+.navbar-header:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-header:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .navbar-header {
+ float: left;
+ }
+}
+.navbar-collapse {
+ max-height: 340px;
+ overflow-x: visible;
+ padding-right: 15px;
+ padding-left: 15px;
+ border-top: 1px solid transparent;
+ box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
+ -webkit-overflow-scrolling: touch;
+}
+.navbar-collapse:before,
+.navbar-collapse:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-collapse:after {
+ clear: both;
+}
+.navbar-collapse:before,
+.navbar-collapse:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-collapse:after {
+ clear: both;
+}
+.navbar-collapse.in {
+ overflow-y: auto;
+}
+@media (min-width: 768px) {
+ .navbar-collapse {
+ width: auto;
+ border-top: 0;
+ box-shadow: none;
+ }
+ .navbar-collapse.collapse {
+ display: block !important;
+ height: auto !important;
+ padding-bottom: 0;
+ overflow: visible !important;
+ }
+ .navbar-collapse.in {
+ overflow-y: visible;
+ }
+ .navbar-collapse .navbar-nav.navbar-left:first-child {
+ margin-left: -15px;
+ }
+ .navbar-collapse .navbar-nav.navbar-right:last-child {
+ margin-right: -15px;
+ }
+ .navbar-collapse .navbar-text:last-child {
+ margin-right: 0;
+ }
+}
+.container > .navbar-header,
+.container > .navbar-collapse {
+ margin-right: -15px;
+ margin-left: -15px;
+}
+@media (min-width: 768px) {
+ .container > .navbar-header,
+ .container > .navbar-collapse {
+ margin-right: 0;
+ margin-left: 0;
+ }
+}
+.navbar-static-top {
+ border-width: 0 0 1px;
+}
+@media (min-width: 768px) {
+ .navbar-static-top {
+ border-radius: 0;
+ }
+}
+.navbar-fixed-top,
+.navbar-fixed-bottom {
+ position: fixed;
+ right: 0;
+ left: 0;
+ border-width: 0 0 1px;
+}
+@media (min-width: 768px) {
+ .navbar-fixed-top,
+ .navbar-fixed-bottom {
+ border-radius: 0;
+ }
+}
+.navbar-fixed-top {
+ z-index: 1030;
+ top: 0;
+}
+.navbar-fixed-bottom {
+ bottom: 0;
+ margin-bottom: 0;
+}
+.navbar-brand {
+ float: left;
+ padding: 15px 15px;
+ font-size: 18px;
+ line-height: 20px;
+}
+.navbar-brand:hover,
+.navbar-brand:focus {
+ text-decoration: none;
+}
+@media (min-width: 768px) {
+ .navbar > .container .navbar-brand {
+ margin-left: -15px;
+ }
+}
+.navbar-toggle {
+ position: relative;
+ float: right;
+ margin-right: 15px;
+ padding: 9px 10px;
+ margin-top: 8px;
+ margin-bottom: 8px;
+ background-color: transparent;
+ border: 1px solid transparent;
+ border-radius: 4px;
+}
+.navbar-toggle .icon-bar {
+ display: block;
+ width: 22px;
+ height: 2px;
+ border-radius: 1px;
+}
+.navbar-toggle .icon-bar + .icon-bar {
+ margin-top: 4px;
+}
+@media (min-width: 768px) {
+ .navbar-toggle {
+ display: none;
+ }
+}
+.navbar-nav {
+ margin: 7.5px -15px;
+}
+.navbar-nav > li > a {
+ padding-top: 10px;
+ padding-bottom: 10px;
+ line-height: 20px;
+}
+@media (max-width: 767px) {
+ .navbar-nav .open .dropdown-menu {
+ position: static;
+ float: none;
+ width: auto;
+ margin-top: 0;
+ background-color: transparent;
+ border: 0;
+ box-shadow: none;
+ }
+ .navbar-nav .open .dropdown-menu > li > a,
+ .navbar-nav .open .dropdown-menu .dropdown-header {
+ padding: 5px 15px 5px 25px;
+ }
+ .navbar-nav .open .dropdown-menu > li > a {
+ line-height: 20px;
+ }
+ .navbar-nav .open .dropdown-menu > li > a:hover,
+ .navbar-nav .open .dropdown-menu > li > a:focus {
+ background-image: none;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-nav {
+ float: left;
+ margin: 0;
+ }
+ .navbar-nav > li {
+ float: left;
+ }
+ .navbar-nav > li > a {
+ padding-top: 15px;
+ padding-bottom: 15px;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-left {
+ float: left !important;
+ }
+ .navbar-right {
+ float: right !important;
+ }
+}
+.navbar-form {
+ margin-left: -15px;
+ margin-right: -15px;
+ padding: 10px 15px;
+ border-top: 1px solid transparent;
+ border-bottom: 1px solid transparent;
+ -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+ box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+ margin-top: 8px;
+ margin-bottom: 8px;
+}
+@media (min-width: 768px) {
+ .navbar-form .form-group {
+ display: inline-block;
+ margin-bottom: 0;
+ vertical-align: middle;
+ }
+ .navbar-form .form-control {
+ display: inline-block;
+ }
+ .navbar-form .radio,
+ .navbar-form .checkbox {
+ display: inline-block;
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-left: 0;
+ }
+ .navbar-form .radio input[type="radio"],
+ .navbar-form .checkbox input[type="checkbox"] {
+ float: none;
+ margin-left: 0;
+ }
+}
+@media (max-width: 767px) {
+ .navbar-form .form-group {
+ margin-bottom: 5px;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-form {
+ width: auto;
+ border: 0;
+ margin-left: 0;
+ margin-right: 0;
+ padding-top: 0;
+ padding-bottom: 0;
+ -webkit-box-shadow: none;
+ box-shadow: none;
+ }
+}
+.navbar-nav > li > .dropdown-menu {
+ margin-top: 0;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.navbar-nav.pull-right > li > .dropdown-menu,
+.navbar-nav > li > .dropdown-menu.pull-right {
+ left: auto;
+ right: 0;
+}
+.navbar-btn {
+ margin-top: 8px;
+ margin-bottom: 8px;
+}
+.navbar-text {
+ float: left;
... 14575 lines suppressed ...
[incubator-hudi-site] 11/19: Copyright footer + privacy policy to
site
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 9ca095cf39b760ab05f2d13724c9008b4769e2c0
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Mon Feb 18 17:47:08 2019 -0800
Copyright footer + privacy policy to site
- css formatting changes
- Added asf logo
- Refreshed hudi landing page
---
docs/_includes/footer.html | 10 +-
docs/_includes/topnav.html | 3 +-
docs/css/customstyles.css | 4 +-
docs/css/lavish-bootstrap.css | 8 ++
docs/css/theme-blue.css | 3 +-
docs/images/asf_logo.svg | 210 +++++++++++++++++++++++++++++++++++++++++
docs/images/hoodie_intro_1.png | Bin 23478 -> 27890 bytes
docs/index.md | 11 +--
docs/privacy.md | 23 +++++
9 files changed, 258 insertions(+), 14 deletions(-)
diff --git a/docs/_includes/footer.html b/docs/_includes/footer.html
index 9847670..00605db 100755
--- a/docs/_includes/footer.html
+++ b/docs/_includes/footer.html
@@ -1,9 +1,13 @@
<footer>
<div class="row">
<div class="col-lg-12 footer">
- ©{{ site.time | date: "%Y" }} {{site.company_name}}. All rights reserved. <br />
-{% if page.last_updated %}<span>Page last updated:</span> {{page.last_updated}}<br/>{% endif %} Site last generated: {{ site.time | date: "%b %-d, %Y" }} <br />
- <!--<p><img src="{{ "images/company_logo.png" }}" alt="Company logo"/></p>-->
+ <p>
+ Copyright © <span id="copyright-year">2019</span> <a href="https://apache.org">The Apache Software Foundation</a>,
+ Licensed under the Apache License, Version 2.0<br>
+ Apache and the Apache feather logo are trademarks of The Apache Software Foundation.| <a href="/privacy">Privacy Policy</a><br>
+ <a class="footer-link-img" href="https://apache.org">
+ <img src="images/asf_logo.svg" alt="The Apache Software Foundation" height="100px" widh="50px"></a>
+ </p>
</div>
</div>
</footer>
diff --git a/docs/_includes/topnav.html b/docs/_includes/topnav.html
index 7019fe8..f2d0189 100644
--- a/docs/_includes/topnav.html
+++ b/docs/_includes/topnav.html
@@ -13,7 +13,8 @@
<a class="fa fa-lg navbar-brand" href="index.html"> <span class="projectTitle">
<img src="{{ "images/hudi_site_logo.png" }}" alt="Hudi logo"/>
<!--{{site.topnav_title}}-->
- </span></a>
+ </span><br/>
+ <p class="navbar-incubate">(Incubating)</p></a>
</div>
<div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
<ul class="nav navbar-nav navbar-right">
diff --git a/docs/css/customstyles.css b/docs/css/customstyles.css
index 676c804..d6667a5 100644
--- a/docs/css/customstyles.css
+++ b/docs/css/customstyles.css
@@ -83,7 +83,7 @@ padding-top: 60px;
margin-top: -40px
}
-body h1 {margin-top:40px;}
+body h1 {margin-top:80px;}
.post-content img {
margin: 12px 0px 3px 0px;
@@ -1178,4 +1178,4 @@ div.box.box1 {
h4.panel-title {
padding-top: 0px;
margin-top: 0px;
-}
\ No newline at end of file
+}
diff --git a/docs/css/lavish-bootstrap.css b/docs/css/lavish-bootstrap.css
index ff64532..a050c9a 100644
--- a/docs/css/lavish-bootstrap.css
+++ b/docs/css/lavish-bootstrap.css
@@ -3643,6 +3643,14 @@ textarea.input-group-sm > .input-group-btn > .btn {
.navbar-brand:focus {
text-decoration: none;
}
+.navbar-incubate {
+ text-align: center;
+ font-size: 24px;
+ color: grey;
+}
+
+
+
@media (min-width: 768px) {
.navbar > .container .navbar-brand {
margin-left: -15px;
diff --git a/docs/css/theme-blue.css b/docs/css/theme-blue.css
index f9aa248..9a923ef 100644
--- a/docs/css/theme-blue.css
+++ b/docs/css/theme-blue.css
@@ -95,11 +95,10 @@ div.sidebarTitle {
}
li.sidebarTitle {
- margin-top:40px;
+ margin-top:80px;
font-weight:normal;
font-size:130%;
color: #333;
margin-bottom:10px;
margin-left: 5px;
-
}
diff --git a/docs/images/asf_logo.svg b/docs/images/asf_logo.svg
new file mode 100644
index 0000000..620694c
--- /dev/null
+++ b/docs/images/asf_logo.svg
@@ -0,0 +1,210 @@
+<?xml version="1.0" encoding="utf-8"?>
+<!-- Generator: Adobe Illustrator 19.0.0, SVG Export Plug-In . SVG Version: 6.00 Build 0) -->
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+<svg version="1.1" id="Layer_2" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" y="0px"
+ viewBox="0 0 7127.6 2890" enable-background="new 0 0 7127.6 2890" xml:space="preserve">
+<path fill="#6D6E71" d="M7104.7,847.8c15.3,15.3,22.9,33.7,22.9,55.2c0,21.5-7.6,39.9-22.9,55.4c-15.3,15.4-33.8,23.1-55.6,23.1
+ c-21.8,0-40.2-7.6-55.4-22.9c-15.1-15.3-22.7-33.7-22.7-55.2c0-21.5,7.6-39.9,22.9-55.4c15.3-15.4,33.7-23.1,55.4-23.1
+ C7070.9,824.9,7089.4,832.5,7104.7,847.8z M7098.1,951.9c13.3-13.6,20-29.8,20-48.7s-6.6-35-19.8-48.5
+ c-13.2-13.4-29.4-20.1-48.6-20.1c-19.2,0-35.4,6.7-48.7,20.2c-13.3,13.5-19.9,29.7-19.9,48.7c0,19,6.6,35.2,19.7,48.6
+ c13.1,13.4,29.3,20.1,48.5,20.1S7084.7,965.4,7098.1,951.9z M7087.1,888.1c0,14-6.1,22.8-18.4,26.4l22.5,30.5h-18.2l-20.3-28.3
+ h-18.6v28.3h-14.7v-84.6h31.8c12.8,0,22,2.2,27.6,6.6C7084.4,871.4,7087.1,878.4,7087.1,888.1z M7068.2,900c3-2.4,4.4-6.5,4.4-12
+ c0-5.5-1.5-9.4-4.5-11.6c-3-2.2-8.4-3.2-16-3.2h-18v30.5h17.5C7059.7,903.6,7065.3,902.4,7068.2,900z"/>
+<path fill="#6D6E71" d="M1803.6,499.8v155.4h-20V499.8h-56.8v-19.2h133.9v19.2H1803.6z"/>
+<path fill="#6D6E71" d="M2082.2,655.2v-76.9h-105.2v76.9h-20V480.5h20v78.9h105.2v-78.9h20v174.7H2082.2z"/>
+<path fill="#6D6E71" d="M2241.4,499.8v57.4h88.1v19.2h-88.1v59.8h101.8v19h-121.8V480.5H2340v19.2H2241.4z"/>
+<path fill="#D22128" d="M1574.5,1852.4l417.3-997.6h80.1l417.3,997.6h-105.4l-129.3-311.9h-448.2l-127.9,311.9H1574.5z M2032.6,970
+ l-205.1,493.2h404.7L2032.6,970z"/>
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diff --git a/docs/images/hoodie_intro_1.png b/docs/images/hoodie_intro_1.png
index dd8977a..6220b46 100644
Binary files a/docs/images/hoodie_intro_1.png and b/docs/images/hoodie_intro_1.png differ
diff --git a/docs/index.md b/docs/index.md
index c198431..b5b9da7 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -1,5 +1,5 @@
---
-title: Apache Hudi Overview
+title: What is Hudi?
keywords: homepage
tags: [getting_started]
sidebar: mydoc_sidebar
@@ -10,16 +10,15 @@ summary: "Hudi lowers data latency across the board, while simultaneously achiev
-Hudi (pronounced “Hoodie”) manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud and serves them out via two types of tables
+Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud stores and provides three logical views for query access.
- * **Read Optimized Table** - Provides excellent query performance via purely columnar storage (e.g. [Parquet](https://parquet.apache.org/))
+ * **Read Optimized View** - Provides excellent query performance on pure columnar storage, much like plain [Parquet](https://parquet.apache.org/) tables.
+ * **Incremental View** - Provides a change stream out of the dataset to feed downstream jobs/ETLs.
* **Near-Real time Table** - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + [Avro](http://avro.apache.org/docs/current/mr.html))
{% include image.html file="hoodie_intro_1.png" alt="hoodie_intro_1.png" %}
-By carefully managing how data is laid out in storage & how it’s exposed to queries, Hoodie is able to power a rich data ecosystem where external sources can be ingested into Hadoop in near real-time. The ingested data is then available for interactive SQL Engines like [Presto](https://prestodb.io) & [Spark](https://spark.apache.org/sql/), while at the same time capable of being consumed incrementally from processing/ETL frameworks like [Hive](https://hive.apache.org/) & [Spark](https:// [...]
+By carefully managing how data is laid out in storage & how it’s exposed to queries, Hudi is able to power a rich data ecosystem where external sources can be ingested in near real-time and made available for interactive SQL Engines like [Presto](https://prestodb.io) & [Spark](https://spark.apache.org/sql/), while at the same time capable of being consumed incrementally from processing/ETL frameworks like [Hive](https://hive.apache.org/) & [Spark](https://spark.apache.org/docs/latest/) t [...]
Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access.
-
-{% include callout.html content="Hudi is a new project. Near Real-Time Table implementation is currently underway. Get involved [here](https://github.com/uber/hoodie/projects/1)" type="info" %}
diff --git a/docs/privacy.md b/docs/privacy.md
new file mode 100644
index 0000000..32fcb91
--- /dev/null
+++ b/docs/privacy.md
@@ -0,0 +1,23 @@
+---
+title: Privacy Policy
+keywords: privacy
+sidebar: mydoc_sidebar
+permalink: privacy.html
+---
+
+Information about your use of this website is collected using server access logs and a tracking cookie.
+The collected information consists of the following:
+
+* The IP address from which you access the website;
+* The type of browser and operating system you use to access our site;
+* The date and time you access our site;
+* The pages you visit;
+* The addresses of pages from where you followed a link to our site.
+
+Part of this information is gathered using a tracking cookie set by the [Google Analytics](http://www.google.com/analytics) service and handled by Google as described in their [privacy policy](http://www.google.com/privacy.html). See your browser documentation for instructions on how to disable the cookie if you prefer not to share this data with Google.
+
+We use the gathered information to help us make our site more useful to visitors and to better understand how and when our site is used. We do not track or collect personally identifiable information or associate gathered data with any personally identifying information from other sources.
+
+By using this website, you consent to the collection of this data in the manner and for the purpose described above.
+
+The Hudi development community welcomes your questions or comments regarding this Privacy Policy. Send them to dev@hudi.apache.org
[incubator-hudi-site] 09/19: Merge pull request #3 from
vinothchandar/patch-2
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 14c34e955ab9cc1057d9622e4f60be101b170645
Merge: 6b2b809 d445077
Author: vinoth chandar <vi...@users.noreply.github.com>
AuthorDate: Fri Feb 15 20:58:56 2019 -0800
Merge pull request #3 from vinothchandar/patch-2
Add delta streamer transformer option to docs
docs/incremental_processing.md | 7 ++++++-
1 file changed, 6 insertions(+), 1 deletion(-)
[incubator-hudi-site] 17/19: Refreshing site content
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 97b3106520c489612dd2187eb9ce4796d5f5c49f
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Sat Mar 9 13:18:07 2019 -0800
Refreshing site content
---
content/.gitignore | 1 -
content/404.html | 6 +-
content/admin_guide.html | 50 ++-
content/community.html | 11 +-
content/comparison.html | 15 +-
content/concepts.html | 8 +-
content/configurations.html | 489 ++++++++++++++-------
content/contributing.html | 8 +-
content/css/customstyles.css | 4 +-
content/css/theme-blue.css | 2 +-
content/feed.xml | 6 +-
content/gcs_hoodie.html | 16 +-
...ommit_duration.png => hudi_commit_duration.png} | Bin
.../{hoodie_intro_1.png => hudi_intro_1.png} | Bin
...ie_log_format_v2.png => hudi_log_format_v2.png} | Bin
...uery_perf_hive.png => hudi_query_perf_hive.png} | Bin
..._perf_presto.png => hudi_query_perf_presto.png} | Bin
...ry_perf_spark.png => hudi_query_perf_spark.png} | Bin
.../{hoodie_upsert_dag.png => hudi_upsert_dag.png} | Bin
...odie_upsert_perf1.png => hudi_upsert_perf1.png} | Bin
...odie_upsert_perf2.png => hudi_upsert_perf2.png} | Bin
content/implementation.html | 22 +-
content/incremental_processing.html | 36 +-
content/index.html | 10 +-
content/js/mydoc_scroll.html | 6 +-
content/migration_guide.html | 15 +-
content/news.html | 8 +-
content/news_archive.html | 6 +-
content/powered_by.html | 7 +-
content/privacy.html | 6 +-
content/quickstart.html | 26 +-
content/s3_hoodie.html | 19 +-
content/search.json | 40 +-
content/sql_queries.html | 8 +-
content/strata-talk.html | 6 +-
content/use_cases.html | 19 +-
36 files changed, 558 insertions(+), 292 deletions(-)
diff --git a/content/.gitignore b/content/.gitignore
deleted file mode 100644
index e43b0f9..0000000
--- a/content/.gitignore
+++ /dev/null
@@ -1 +0,0 @@
-.DS_Store
diff --git a/content/404.html b/content/404.html
index 9491810..fedef9b 100644
--- a/content/404.html
+++ b/content/404.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" ">
+<meta name="keywords" content="">
<title>Page Not Found | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
diff --git a/content/admin_guide.html b/content/admin_guide.html
index 470a219..3625cee 100644
--- a/content/admin_guide.html
+++ b/content/admin_guide.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="This section offers an overview of tools available to operate an ecosystem of Hudi datasets">
-<meta name="keywords" content=" admin">
+<meta name="keywords" content="hudi, administration, operation, devops">
<title>Admin Guide | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -355,11 +359,11 @@
<h2 id="admin-cli">Admin CLI</h2>
-<p>Once hoodie has been built via <code class="highlighter-rouge">mvn clean install -DskipTests</code>, the shell can be fired by via <code class="highlighter-rouge">cd hoodie-cli && ./hoodie-cli.sh</code>.
-A hoodie dataset resides on HDFS, in a location referred to as the <strong>basePath</strong> and we would need this location in order to connect to a Hoodie dataset.
-Hoodie library effectively manages this HDFS dataset internally, using .hoodie subfolder to track all metadata</p>
+<p>Once hudi has been built, the shell can be fired by via <code class="highlighter-rouge">cd hoodie-cli && ./hoodie-cli.sh</code>.
+A hudi dataset resides on DFS, in a location referred to as the <strong>basePath</strong> and we would need this location in order to connect to a Hudi dataset.
+Hudi library effectively manages this dataset internally, using .hoodie subfolder to track all metadata</p>
-<p>To initialize a hoodie table, use the following command.</p>
+<p>To initialize a hudi table, use the following command.</p>
<div class="highlighter-rouge"><pre class="highlight"><code>18/09/06 15:56:52 INFO annotation.AutowiredAnnotationBeanPostProcessor: JSR-330 'javax.inject.Inject' annotation found and supported for autowiring
============================================
@@ -380,7 +384,7 @@ hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1
</code></pre>
</div>
-<p>To see the description of hoodie table, use the command:</p>
+<p>To see the description of hudi table, use the command:</p>
<div class="highlighter-rouge"><pre class="highlight"><code>
hoodie:hoodie_table_1->desc
@@ -398,7 +402,7 @@ hoodie:hoodie_table_1->desc
</code></pre>
</div>
-<p>Following is a sample command to connect to a Hoodie dataset contains uber trips.</p>
+<p>Following is a sample command to connect to a Hudi dataset contains uber trips.</p>
<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->connect --path /app/uber/trips
@@ -447,7 +451,7 @@ hoodie:trips->
<h4 id="inspecting-commits">Inspecting Commits</h4>
-<p>The task of upserting or inserting a batch of incoming records is known as a <strong>commit</strong> in Hoodie. A commit provides basic atomicity guarantees such that only commited data is available for querying.
+<p>The task of upserting or inserting a batch of incoming records is known as a <strong>commit</strong> in Hudi. A commit provides basic atomicity guarantees such that only commited data is available for querying.
Each commit has a monotonically increasing string/number called the <strong>commit number</strong>. Typically, this is the time at which we started the commit.</p>
<p>To view some basic information about the last 10 commits,</p>
@@ -464,7 +468,7 @@ hoodie:trips->
</code></pre>
</div>
-<p>At the start of each write, Hoodie also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight</p>
+<p>At the start of each write, Hudi also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight</p>
<div class="highlighter-rouge"><pre class="highlight"><code>$ hdfs dfs -ls /app/uber/trips/.hoodie/*.inflight
-rw-r--r-- 3 vinoth supergroup 321984 2016-10-05 23:18 /app/uber/trips/.hoodie/20161005225920.inflight
@@ -522,7 +526,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
<h4 id="statistics">Statistics</h4>
-<p>Since Hoodie directly manages file sizes for HDFS dataset, it might be good to get an overall picture</p>
+<p>Since Hudi directly manages file sizes for DFS dataset, it might be good to get an overall picture</p>
<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->stats filesizes --partitionPath 2016/09/01 --sortBy "95th" --desc true --limit 10
________________________________________________________________________________________________
@@ -534,7 +538,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
</code></pre>
</div>
-<p>In case of Hoodie write taking much longer, it might be good to see the write amplification for any sudden increases</p>
+<p>In case of Hudi write taking much longer, it might be good to see the write amplification for any sudden increases</p>
<div class="highlighter-rouge"><pre class="highlight"><code>hoodie:trips->stats wa
__________________________________________________________________________
@@ -547,7 +551,7 @@ order (See Concepts). The below commands allow users to view the file-slices for
<h4 id="archived-commits">Archived Commits</h4>
-<p>In order to limit the amount of growth of .commit files on HDFS, Hoodie archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
+<p>In order to limit the amount of growth of .commit files on DFS, Hudi archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
This is a sequence file that contains a mapping from commitNumber => json with raw information about the commit (same that is nicely rolled up above).</p>
<h4 id="compactions">Compactions</h4>
@@ -692,7 +696,7 @@ No File renames needed to unschedule pending compaction. Operation successful.</
<div class="highlighter-rouge"><pre class="highlight"><code>
##### Repair Compaction
-The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
+The above compaction unscheduling operations could sometimes fail partially (e:g -> DFS temporarily unavailable). With
partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
`compaction validate`, you can notice invalid compaction operations if there is one. In these cases, the repair
command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
@@ -710,7 +714,7 @@ Compaction successfully repaired
<h2 id="metrics">Metrics</h2>
-<p>Once the Hoodie Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hoodie datasets</p>
+<p>Once the Hudi Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hudi datasets</p>
<ul>
<li><strong>Commit Duration</strong> - This is amount of time it took to successfully commit a batch of records</li>
@@ -722,29 +726,29 @@ Compaction successfully repaired
<p>These metrics can then be plotted on a standard tool like grafana. Below is a sample commit duration chart.</p>
-<figure><img class="docimage" src="images/hoodie_commit_duration.png" alt="hoodie_commit_duration.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_commit_duration.png" alt="hudi_commit_duration.png" style="max-width: 1000px" /></figure>
<h2 id="troubleshooting-failures">Troubleshooting Failures</h2>
-<p>Section below generally aids in debugging Hoodie failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)</p>
+<p>Section below generally aids in debugging Hudi failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)</p>
<ul>
- <li><strong>_hoodie_record_key</strong> - Treated as a primary key within each HDFS partition, basis of all updates/inserts</li>
+ <li><strong>_hoodie_record_key</strong> - Treated as a primary key within each DFS partition, basis of all updates/inserts</li>
<li><strong>_hoodie_commit_time</strong> - Last commit that touched this record</li>
<li><strong>_hoodie_file_name</strong> - Actual file name containing the record (super useful to triage duplicates)</li>
<li><strong>_hoodie_partition_path</strong> - Path from basePath that identifies the partition containing this record</li>
</ul>
-<div class="bs-callout bs-callout-warning">Note that as of now, Hoodie assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition</div>
+<div class="bs-callout bs-callout-warning">Note that as of now, Hudi assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition</div>
<h4 id="missing-records">Missing records</h4>
<p>Please check if there were any write errors using the admin commands above, during the window at which the record could have been written.
-If you do find errors, then the record was not actually written by Hoodie, but handed back to the application to decide what to do with it.</p>
+If you do find errors, then the record was not actually written by Hudi, but handed back to the application to decide what to do with it.</p>
<h4 id="duplicates">Duplicates</h4>
-<p>First of all, please confirm if you do indeed have duplicates <strong>AFTER</strong> ensuring the query is accessing the Hoodie datasets <a href="sql_queries.html">properly</a> .</p>
+<p>First of all, please confirm if you do indeed have duplicates <strong>AFTER</strong> ensuring the query is accessing the Hudi datasets <a href="sql_queries.html">properly</a> .</p>
<ul>
<li>If confirmed, please use the metadata fields above, to identify the physical files & partition files containing the records .</li>
@@ -754,10 +758,10 @@ If you do find errors, then the record was not actually written by Hoodie, but h
<h4 id="spark-failures">Spark failures</h4>
-<p>Typical upsert() DAG looks like below. Note that Hoodie client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
+<p>Typical upsert() DAG looks like below. Note that Hudi client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
Also Spark UI shows sortByKey twice due to the probe job also being shown, nonetheless its just a single sort.</p>
-<figure><img class="docimage" src="images/hoodie_upsert_dag.png" alt="hoodie_upsert_dag.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_upsert_dag.png" alt="hudi_upsert_dag.png" style="max-width: 1000px" /></figure>
<p>At a high level, there are two steps</p>
@@ -777,7 +781,7 @@ Also Spark UI shows sortByKey twice due to the probe job also being shown, nonet
<li>Job 7 : Actual writing of data (update + insert + insert turned to updates to maintain file size)</li>
</ul>
-<p>Depending on the exception source (Hoodie/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/HDFS temporary failures.
+<p>Depending on the exception source (Hudi/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/DFS temporary failures.
In the future, a more sophisticated debug/management UI would be added to the project, that can help automate some of this debugging.</p>
diff --git a/content/community.html b/content/community.html
index 39488eb..34196f3 100644
--- a/content/community.html
+++ b/content/community.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" usecases">
+<meta name="keywords" content="hudi, use cases, big data, apache">
<title>Community | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -355,7 +359,7 @@
<tbody>
<tr>
<td>For any general questions, user support, development discussions</td>
- <td>Dev Mailing list (<a href="mailto:dev-subscribe@hudi.apache.org">Subscribe</a>, <a href="mailto:dev-unsubscribe@hudi.apache.or& [...]
+ <td>Dev Mailing list (<a href="mailto:dev-subscribe@hudi.apache.org">Subscribe</a>, <a href="mailto:dev-unsubscribe@hudi.apache.or& [...]
</tr>
<tr>
<td>For reporting bugs or issues or discover known issues</td>
@@ -389,9 +393,10 @@ Apache Hudi follows the typical Apache vulnerability handling <a href="https://a
<li>Ask (and/or) answer questions on our support channels listed above.</li>
<li>Review code or HIPs</li>
<li>Help improve documentation</li>
+ <li>Author blogs on our wiki</li>
<li>Testing; Improving out-of-box experience by reporting bugs</li>
<li>Share new ideas/directions to pursue or propose a new HIP</li>
- <li>Contributing code to the project</li>
+ <li>Contributing code to the project (<a href="https://issues.apache.org/jira/issues/?jql=project+%3D+HUDI+AND+component+%3D+newbie">newbie JIRAs</a>)</li>
</ul>
<h4 id="code-contributions">Code Contributions</h4>
diff --git a/content/comparison.html b/content/comparison.html
index 34082e0..59bcf75 100644
--- a/content/comparison.html
+++ b/content/comparison.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" usecases">
+<meta name="keywords" content="apache, hudi, kafka, kudu, hive, hbase, stream processing">
<title>Comparison | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -341,7 +345,7 @@
- <p>Apache Hudi fills a big void for processing data on top of HDFS, and thus mostly co-exists nicely with these technologies. However,
+ <p>Apache Hudi fills a big void for processing data on top of DFS, and thus mostly co-exists nicely with these technologies. However,
it would be useful to understand how Hudi fits into the current big data ecosystem, contrasting it with a few related systems
and bring out the different tradeoffs these systems have accepted in their design.</p>
@@ -380,16 +384,15 @@ just for analytics. Finally, HBase does not support incremental processing primi
<p>A popular question, we get is : “How does Hudi relate to stream processing systems?”, which we will try to answer here. Simply put, Hudi can integrate with
batch (<code class="highlighter-rouge">copy-on-write storage</code>) and streaming (<code class="highlighter-rouge">merge-on-read storage</code>) jobs of today, to store the computed results in Hadoop. For Spark apps, this can happen via direct
integration of Hudi library with Spark/Spark streaming DAGs. In case of Non-Spark processing systems (eg: Flink, Hive), the processing can be done in the respective systems
-and later sent into a Hudi table via a Kafka topic/HDFS intermediate file. In more conceptual level, data processing
+and later sent into a Hudi table via a Kafka topic/DFS intermediate file. In more conceptual level, data processing
pipelines just consist of three components : <code class="highlighter-rouge">source</code>, <code class="highlighter-rouge">processing</code>, <code class="highlighter-rouge">sink</code>, with users ultimately running queries against the sink to use the results of the pipeline.
-Hudi can act as either a source or sink, that stores data on HDFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
+Hudi can act as either a source or sink, that stores data on DFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
of Presto/SparkSQL/Hive for your queries.</p>
<p>More advanced use cases revolve around the concepts of <a href="https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop">incremental processing</a>, which effectively
uses Hudi even inside the <code class="highlighter-rouge">processing</code> engine to speed up typical batch pipelines. For e.g: Hudi can be used as a state store inside a processing DAG (similar
to how <a href="https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend">rocksDB</a> is used by Flink). This is an item on the roadmap
-and will eventually happen as a <a href="https://github.com/uber/hoodie/issues/8">Beam Runner</a></p>
-
+and will eventually happen as a <a href="https://issues.apache.org/jira/browse/HUDI-60">Beam Runner</a></p>
<div class="tags">
diff --git a/content/concepts.html b/content/concepts.html
index 7e85d32..22754c4 100644
--- a/content/concepts.html
+++ b/content/concepts.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="Here we introduce some basic concepts & give a broad technical overview of Hudi">
-<meta name="keywords" content=" concepts">
+<meta name="keywords" content="hudi, design, storage, views, timeline">
<title>Concepts | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -343,7 +347,7 @@
- <p>Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on HDFS</p>
+ <p>Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on DFS</p>
<ul>
<li>Upsert (how do I change the dataset?)</li>
diff --git a/content/configurations.html b/content/configurations.html
index 5f1adb8..73f66c9 100644
--- a/content/configurations.html
+++ b/content/configurations.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="Here we list all possible configurations and what they mean">
-<meta name="keywords" content=" configurations">
+<meta name="keywords" content="garbage collection, hudi, jvm, configs, tuning">
<title>Configurations | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -343,174 +347,360 @@
- <h3 id="configuration">Configuration</h3>
+ <p>This page covers the different ways of configuring your job to write/read Hudi datasets.
+At a high level, you can control behaviour at few levels.</p>
+
+<ul>
+ <li><strong><a href="#spark-datasource">Spark Datasource Configs</a></strong> : These configs control the Hudi Spark Datasource, providing ability to define keys/partitioning, pick out the write operation, specify how to merge records or choosing view type to read.</li>
+ <li><strong><a href="#writeclient-configs">WriteClient Configs</a></strong> : Internally, the Hudi datasource uses a RDD based <code class="highlighter-rouge">HoodieWriteClient</code> api to actually perform writes to storage. These configs provide deep control over lower level aspects like
+ file sizing, compression, parallelism, compaction, write schema, cleaning etc. Although Hudi provides sane defaults, from time-time these configs may need to be tweaked to optimize for specific workloads.</li>
+ <li><strong><a href="#PAYLOAD_CLASS_OPT_KEY">RecordPayload Config</a></strong> : This is the lowest level of customization offered by Hudi. Record payloads define how to produce new values to upsert based on incoming new record and
+ stored old record. Hudi provides default implementations such as <code class="highlighter-rouge">OverwriteWithLatestAvroPayload</code> which simply update storage with the latest/last-written record.
+ This can be overridden to a custom class extending <code class="highlighter-rouge">HoodieRecordPayload</code> class, on both datasource and WriteClient levels.</li>
+</ul>
+
+<h3 id="talking-to-cloud-storage">Talking to Cloud Storage</h3>
+
+<p>Immaterial of whether RDD/WriteClient APIs or Datasource is used, the following information helps configure access
+to cloud stores.</p>
+
+<ul>
+ <li><a href="s3_hoodie.html">AWS S3</a> <br />
+Configurations required for S3 and Hudi co-operability.</li>
+ <li><a href="gcs_hoodie.html">Google Cloud Storage</a> <br />
+Configurations required for GCS and Hudi co-operability.</li>
+</ul>
+
+<h3 id="spark-datasource">Spark Datasource Configs</h3>
+
+<p>Spark jobs using the datasource can be configured by passing the below options into the <code class="highlighter-rouge">option(k,v)</code> method as usual.
+The actual datasource level configs are listed below.</p>
+
+<h4 id="write-options">Write Options</h4>
+
+<p>Additionally, you can pass down any of the WriteClient level configs directly using <code class="highlighter-rouge">options()</code> or <code class="highlighter-rouge">option(k,v)</code> methods.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>inputDF.write()
+.format("com.uber.hoodie")
+.options(clientOpts) // any of the Hudi client opts can be passed in as well
+.option(DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY(), "_row_key")
+.option(DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY(), "partition")
+.option(DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY(), "timestamp")
+.option(HoodieWriteConfig.TABLE_NAME, tableName)
+.mode(SaveMode.Append)
+.save(basePath);
+</code></pre>
+</div>
+
+<p>Options useful for writing datasets via <code class="highlighter-rouge">write.format.option(...)</code></p>
+
+<ul>
+ <li><a href="#TABLE_NAME_OPT_KEY">TABLE_NAME_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.table.name</code> [Required]<br />
+<span style="color:grey">Hive table name, to register the dataset into.</span></li>
+ <li><a href="#OPERATION_OPT_KEY">OPERATION_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.operation</code>, Default: <code class="highlighter-rouge">upsert</code><br />
+<span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation. Use <code class="highlighter-rouge">bulkinsert</code> to load new data into a table, and there on use <code class="highlighter-rouge">upsert</code>/<code class="highlighter-rouge">insert</code>.
+bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</span></li>
+ <li><a href="#STORAGE_TYPE_OPT_KEY">STORAGE_TYPE_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.storage.type</code>, Default: <code class="highlighter-rouge">COPY_ON_WRITE</code> <br />
+<span style="color:grey">The storage type for the underlying data, for this write. This can’t change between writes.</span></li>
+ <li><a href="#PRECOMBINE_FIELD_OPT_KEY">PRECOMBINE_FIELD_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.precombine.field</code>, Default: <code class="highlighter-rouge">ts</code> <br />
+<span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
+we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span></li>
+ <li><a href="#PAYLOAD_CLASS_OPT_KEY">PAYLOAD_CLASS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.payload.class</code>, Default: <code class="highlighter-rouge">com.uber.hoodie.OverwriteWithLatestAvroPayload</code> <br />
+<span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
+This will render any value set for <code class="highlighter-rouge">PRECOMBINE_FIELD_OPT_VAL</code> in-effective</span></li>
+ <li><a href="#RECORDKEY_FIELD_OPT_KEY">RECORDKEY_FIELD_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.recordkey.field</code>, Default: <code class="highlighter-rouge">uuid</code> <br />
+<span style="color:grey">Record key field. Value to be used as the <code class="highlighter-rouge">recordKey</code> component of <code class="highlighter-rouge">HoodieKey</code>. Actual value
+will be obtained by invoking .toString() on the field value. Nested fields can be specified using
+the dot notation eg: <code class="highlighter-rouge">a.b.c</code></span></li>
+ <li><a href="#PARTITIONPATH_FIELD_OPT_KEY">PARTITIONPATH_FIELD_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.partitionpath.field</code>, Default: <code class="highlighter-rouge">partitionpath</code> <br />
+<span style="color:grey">Partition path field. Value to be used at the <code class="highlighter-rouge">partitionPath</code> component of <code class="highlighter-rouge">HoodieKey</code>.
+Actual value ontained by invoking .toString()</span></li>
+ <li><a href="#KEYGENERATOR_CLASS_OPT_KEY">KEYGENERATOR_CLASS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.keygenerator.class</code>, Default: <code class="highlighter-rouge">com.uber.hoodie.SimpleKeyGenerator</code> <br />
+<span style="color:grey">Key generator class, that implements will extract the key out of incoming <code class="highlighter-rouge">Row</code> object</span></li>
+ <li><a href="#COMMIT_METADATA_KEYPREFIX_OPT_KEY">COMMIT_METADATA_KEYPREFIX_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.commitmeta.key.prefix</code>, Default: <code class="highlighter-rouge">_</code> <br />
+<span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
+This is useful to store checkpointing information, in a consistent way with the hudi timeline</span></li>
+ <li><a href="#INSERT_DROP_DUPS_OPT_KEY">INSERT_DROP_DUPS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.write.insert.drop.duplicates</code>, Default: <code class="highlighter-rouge">false</code> <br />
+<span style="color:grey">If set to true, filters out all duplicate records from incoming dataframe, during insert operations. </span></li>
+ <li><a href="#HIVE_SYNC_ENABLED_OPT_KEY">HIVE_SYNC_ENABLED_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.enable</code>, Default: <code class="highlighter-rouge">false</code> <br />
+<span style="color:grey">When set to true, register/sync the dataset to Apache Hive metastore</span></li>
+ <li><a href="#HIVE_DATABASE_OPT_KEY">HIVE_DATABASE_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.database</code>, Default: <code class="highlighter-rouge">default</code> <br />
+<span style="color:grey">database to sync to</span></li>
+ <li><a href="#HIVE_TABLE_OPT_KEY">HIVE_TABLE_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.table</code>, [Required] <br />
+<span style="color:grey">table to sync to</span></li>
+ <li><a href="#HIVE_USER_OPT_KEY">HIVE_USER_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.username</code>, Default: <code class="highlighter-rouge">hive</code> <br />
+<span style="color:grey">hive user name to use</span></li>
+ <li><a href="#HIVE_PASS_OPT_KEY">HIVE_PASS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.password</code>, Default: <code class="highlighter-rouge">hive</code> <br />
+<span style="color:grey">hive password to use</span></li>
+ <li><a href="#HIVE_URL_OPT_KEY">HIVE_URL_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.jdbcurl</code>, Default: <code class="highlighter-rouge">jdbc:hive2://localhost:10000</code> <br />
+<span style="color:grey">Hive metastore url</span></li>
+ <li><a href="#HIVE_PARTITION_FIELDS_OPT_KEY">HIVE_PARTITION_FIELDS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.partition_fields</code>, Default: ` ` <br />
+<span style="color:grey">field in the dataset to use for determining hive partition columns.</span></li>
+ <li><a href="#HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY">HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.partition_extractor_class</code>, Default: <code class="highlighter-rouge">com.uber.hoodie.hive.SlashEncodedDayPartitionValueExtractor</code> <br />
+<span style="color:grey">Class used to extract partition field values into hive partition columns.</span></li>
+ <li><a href="#HIVE_ASSUME_DATE_PARTITION_OPT_KEY">HIVE_ASSUME_DATE_PARTITION_OPT_KEY</a><br />
+Property: <code class="highlighter-rouge">hoodie.datasource.hive_sync.assume_date_partitioning</code>, Default: <code class="highlighter-rouge">false</code> <br />
+<span style="color:grey">Assume partitioning is yyyy/mm/dd</span></li>
+</ul>
+
+<h4 id="read-options">Read Options</h4>
+
+<p>Options useful for reading datasets via <code class="highlighter-rouge">read.format.option(...)</code></p>
<ul>
- <li><a href="#HoodieWriteConfig">HoodieWriteConfig</a> <br />
-<span style="color:grey">Top Level Config which is passed in when HoodieWriteClent is created.</span>
+ <li><a href="#VIEW_TYPE_OPT_KEY">VIEW_TYPE_OPT_KEY</a> <br />
+Property: <code class="highlighter-rouge">hoodie.datasource.view.type</code>, Default: <code class="highlighter-rouge">read_optimized</code> <br />
+<span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
+(or) Read Optimized mode (obtain latest view, based on columnar data)
+(or) Real time mode (obtain latest view, based on row & columnar data)</span></li>
+ <li><a href="#BEGIN_INSTANTTIME_OPT_KEY">BEGIN_INSTANTTIME_OPT_KEY</a> <br />
+Property: <code class="highlighter-rouge">hoodie.datasource.read.begin.instanttime</code>, [Required in incremental mode] <br />
+<span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
+necessarily correspond to an instant on the timeline. New data written with an
+ <code class="highlighter-rouge">instant_time > BEGIN_INSTANTTIME</code> are fetched out. For e.g: ‘20170901080000’ will get
+ all new data written after Sep 1, 2017 08:00AM.</span></li>
+ <li><a href="#END_INSTANTTIME_OPT_KEY">END_INSTANTTIME_OPT_KEY</a> <br />
+Property: <code class="highlighter-rouge">hoodie.datasource.read.end.instanttime</code>, Default: latest instant (i.e fetches all new data since begin instant time) <br />
+<span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
+<code class="highlighter-rouge">instant_time <= END_INSTANTTIME</code> are fetched out.</span></li>
+</ul>
+
+<h3 id="writeclient-configs">WriteClient Configs</h3>
+
+<p>Jobs programming directly against the RDD level apis can build a <code class="highlighter-rouge">HoodieWriteConfig</code> object and pass it in to the <code class="highlighter-rouge">HoodieWriteClient</code> constructor.
+HoodieWriteConfig can be built using a builder pattern as below.</p>
+
+<div class="highlighter-rouge"><pre class="highlight"><code>HoodieWriteConfig cfg = HoodieWriteConfig.newBuilder()
+ .withPath(basePath)
+ .forTable(tableName)
+ .withSchema(schemaStr)
+ .withProps(props) // pass raw k,v pairs from a property file.
+ .withCompactionConfig(HoodieCompactionConfig.newBuilder().withXXX(...).build())
+ .withIndexConfig(HoodieIndexConfig.newBuilder().withXXX(...).build())
+ ...
+ .build();
+</code></pre>
+</div>
+
+<p>Following subsections go over different aspects of write configs, explaining most important configs with their property names, default values.</p>
+
+<ul>
+ <li><a href="#withPath">withPath</a> (hoodie_base_path)
+Property: <code class="highlighter-rouge">hoodie.base.path</code> [Required] <br />
+<span style="color:grey">Base DFS path under which all the data partitions are created. Always prefix it explicitly with the storage scheme (e.g hdfs://, s3:// etc). Hudi stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span></li>
+ <li><a href="#withSchema">withSchema</a> (schema_str) <br />
+Property: <code class="highlighter-rouge">hoodie.avro.schema</code> [Required]<br />
+<span style="color:grey">This is the current reader avro schema for the dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span></li>
+ <li><a href="#forTable">forTable</a> (table_name)<br />
+Property: <code class="highlighter-rouge">hoodie.table.name</code> [Required] <br />
+ <span style="color:grey">Table name for the dataset, will be used for registering with Hive. Needs to be same across runs.</span></li>
+ <li><a href="#withBulkInsertParallelism">withBulkInsertParallelism</a> (bulk_insert_parallelism = 1500) <br />
+Property: <code class="highlighter-rouge">hoodie.bulkinsert.shuffle.parallelism</code><br />
+<span style="color:grey">Bulk insert is meant to be used for large initial imports and this parallelism determines the initial number of files in your dataset. Tune this to achieve a desired optimal size during initial import.</span></li>
+ <li><a href="#withParallelism">withParallelism</a> (insert_shuffle_parallelism = 1500, upsert_shuffle_parallelism = 1500)<br />
+Property: <code class="highlighter-rouge">hoodie.insert.shuffle.parallelism</code>, <code class="highlighter-rouge">hoodie.upsert.shuffle.parallelism</code><br />
+<span style="color:grey">Once data has been initially imported, this parallelism controls initial parallelism for reading input records. Ensure this value is high enough say: 1 partition for 1 GB of input data</span></li>
+ <li><a href="#combineInput">combineInput</a> (on_insert = false, on_update=true)<br />
+Property: <code class="highlighter-rouge">hoodie.combine.before.insert</code>, <code class="highlighter-rouge">hoodie.combine.before.upsert</code><br />
+<span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in DFS</span></li>
+ <li><a href="#withWriteStatusStorageLevel">withWriteStatusStorageLevel</a> (level = MEMORY_AND_DISK_SER)<br />
+Property: <code class="highlighter-rouge">hoodie.write.status.storage.level</code><br />
+<span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span></li>
+ <li><a href="#withAutoCommit">withAutoCommit</a> (autoCommit = true)<br />
+Property: <code class="highlighter-rouge">hoodie.auto.commit</code><br />
+<span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a “defined success condition”</span></li>
+ <li><a href="#withAssumeDatePartitioning">withAssumeDatePartitioning</a> (assumeDatePartitioning = false)<br />
+Property: ` hoodie.assume.date.partitioning`<br />
+<span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span></li>
+ <li><a href="#withConsistencyCheckEnabled">withConsistencyCheckEnabled</a> (enabled = false)<br />
+Property: <code class="highlighter-rouge">hoodie.consistency.check.enabled</code><br />
+<span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files’ are listable on the underlying filesystem/storage. Set this to true, to workaround S3’s eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span></li>
+</ul>
+
+<h4 id="index-configs">Index configs</h4>
+<p>Following configs control indexing behavior, which tags incoming records as either inserts or updates to older records.</p>
+
+<ul>
+ <li><a href="#withIndexConfig">withIndexConfig</a> (HoodieIndexConfig) <br />
+ <span style="color:grey">This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
<ul>
- <li><a href="#withPath">withPath</a> (hoodie_base_path) <br />
- <span style="color:grey">Base HDFS path under which all the data partitions are created. Hoodie stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span></li>
- <li><a href="#withSchema">withSchema</a> (schema_str) <br />
- <span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span></li>
- <li><a href="#withParallelism">withParallelism</a> (insert_shuffle_parallelism = 200, upsert_shuffle_parallelism = 200) <br />
- <span style="color:grey">Insert DAG uses the insert_parallelism in every shuffle. Upsert DAG uses the upsert_parallelism in every shuffle. Typical workload is profiled and once a min parallelism is established, trade off between latency and cluster usage optimizations this is tuned and have a conservatively high number to optimize for latency and </span></li>
- <li><a href="#combineInput">combineInput</a> (on_insert = false, on_update=true) <br />
- <span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span></li>
- <li><a href="#withWriteStatusStorageLevel">withWriteStatusStorageLevel</a> (level = MEMORY_AND_DISK_SER) <br />
- <span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span></li>
- <li><a href="#withAutoCommit">withAutoCommit</a> (autoCommit = true) <br />
- <span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a “defined success condition”</span></li>
- <li><a href="#withAssumeDatePartitioning">withAssumeDatePartitioning</a> (assumeDatePartitioning = false) <br />
- <span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span></li>
- <li>
- <p><a href="#withConsistencyCheckEnabled">withConsistencyCheckEnabled</a> (enabled = false) <br />
- <span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files’ are listable on the underlying filesystem/storage. Set this to true, to workaround S3’s eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span></p>
- </li>
- <li><a href="#withIndexConfig">withIndexConfig</a> (HoodieIndexConfig) <br />
- <span style="color:grey">Hoodie uses a index to help find the FileID which contains an incoming record key. This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
- <ul>
- <li><a href="#withIndexType">withIndexType</a> (indexType = BLOOM) <br />
+ <li><a href="#withIndexType">withIndexType</a> (indexType = BLOOM) <br />
+ Property: <code class="highlighter-rouge">hoodie.index.type</code> <br />
<span style="color:grey">Type of index to use. Default is Bloom filter. Possible options are [BLOOM | HBASE | INMEMORY]. Bloom filters removes the dependency on a external system and is stored in the footer of the Parquet Data Files</span></li>
- <li><a href="#bloomFilterNumEntries">bloomFilterNumEntries</a> (60000) <br />
- <span style="color:grey">Only applies if index type is BLOOM. <br />This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. <a href="https://github.com/uber/hoodie/issues/70">#70</a> tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positives and in [...]
- <li><a href="#bloomFilterFPP">bloomFilterFPP</a> (0.000000001) <br />
+ <li><a href="#bloomFilterNumEntries">bloomFilterNumEntries</a> (numEntries = 60000) <br />
+ Property: <code class="highlighter-rouge">hoodie.index.bloom.num_entries</code> <br />
+ <span style="color:grey">Only applies if index type is BLOOM. <br />This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. <a href="https://issues.apache.org/jira/browse/HUDI-56">HUDI-56</a> tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positiv [...]
+ <li><a href="#bloomFilterFPP">bloomFilterFPP</a> (fpp = 0.000000001) <br />
+ Property: <code class="highlighter-rouge">hoodie.index.bloom.fpp</code> <br />
<span style="color:grey">Only applies if index type is BLOOM. <br /> Error rate allowed given the number of entries. This is used to calculate how many bits should be assigned for the bloom filter and the number of hash functions. This is usually set very low (default: 0.000000001), we like to tradeoff disk space for lower false positives</span></li>
- <li><a href="#bloomIndexPruneByRanges">bloomIndexPruneByRanges</a> (true) <br />
+ <li><a href="#bloomIndexPruneByRanges">bloomIndexPruneByRanges</a> (pruneRanges = true) <br />
+ Property: <code class="highlighter-rouge">hoodie.bloom.index.prune.by.ranges</code> <br />
<span style="color:grey">Only applies if index type is BLOOM. <br /> When true, range information from files to leveraged speed up index lookups. Particularly helpful, if the key has a monotonously increasing prefix, such as timestamp.</span></li>
- <li><a href="#bloomIndexUseCaching">bloomIndexUseCaching</a> (true) <br />
+ <li><a href="#bloomIndexUseCaching">bloomIndexUseCaching</a> (useCaching = true) <br />
+ Property: <code class="highlighter-rouge">hoodie.bloom.index.use.caching</code> <br />
<span style="color:grey">Only applies if index type is BLOOM. <br /> When true, the input RDD will cached to speed up index lookup by reducing IO for computing parallelism or affected partitions</span></li>
- <li><a href="#bloomIndexParallelism">bloomIndexParallelism</a> (0) <br />
+ <li><a href="#bloomIndexParallelism">bloomIndexParallelism</a> (0) <br />
+ Property: <code class="highlighter-rouge">hoodie.bloom.index.parallelism</code> <br />
<span style="color:grey">Only applies if index type is BLOOM. <br /> This is the amount of parallelism for index lookup, which involves a Spark Shuffle. By default, this is auto computed based on input workload characteristics</span></li>
- <li><a href="#hbaseZkQuorum">hbaseZkQuorum</a> (zkString) <br />
+ <li><a href="#hbaseZkQuorum">hbaseZkQuorum</a> (zkString) [Required]<br />
+ Property: <code class="highlighter-rouge">hoodie.index.hbase.zkquorum</code> <br />
<span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum url to connect to.</span></li>
- <li><a href="#hbaseZkPort">hbaseZkPort</a> (port) <br />
+ <li><a href="#hbaseZkPort">hbaseZkPort</a> (port) [Required]<br />
+ Property: <code class="highlighter-rouge">hoodie.index.hbase.zkport</code> <br />
<span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span></li>
- <li><a href="#hbaseTableName">hbaseTableName</a> (tableName) <br />
- <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span></li>
- </ul>
- </li>
- <li><a href="#withStorageConfig">withStorageConfig</a> (HoodieStorageConfig) <br />
- <span style="color:grey">Storage related configs</span>
- <ul>
- <li><a href="#limitFileSize">limitFileSize</a> (size = 120MB) <br />
- <span style="color:grey">Hoodie re-writes a single file during update (copy_on_write) or a compaction (merge_on_read). This is fundamental unit of parallelism. It is important that this is aligned with the underlying filesystem block size. </span></li>
- <li><a href="#parquetBlockSize">parquetBlockSize</a> (rowgroupsize = 120MB) <br />
- <span style="color:grey">Parquet RowGroup size. Its better than this is aligned with the file size, so that a single column within a file is stored continuously on disk</span></li>
- <li><a href="#parquetPageSize">parquetPageSize</a> (pagesize = 1MB) <br />
+ <li><a href="#hbaseTableName">hbaseTableName</a> (tableName) [Required]<br />
+ Property: <code class="highlighter-rouge">hoodie.index.hbase.table</code> <br />
+ <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hudi stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span></li>
+ </ul>
+ </li>
+</ul>
+
+<h4 id="storage-configs">Storage configs</h4>
+<p>Controls aspects around sizing parquet and log files.</p>
+
+<ul>
+ <li><a href="#withStorageConfig">withStorageConfig</a> (HoodieStorageConfig) <br />
+ <ul>
+ <li><a href="#limitFileSize">limitFileSize</a> (size = 120MB) <br />
+ Property: <code class="highlighter-rouge">hoodie.parquet.max.file.size</code> <br />
+ <span style="color:grey">Target size for parquet files produced by Hudi write phases. For DFS, this needs to be aligned with the underlying filesystem block size for optimal performance. </span></li>
+ <li><a href="#parquetBlockSize">parquetBlockSize</a> (rowgroupsize = 120MB) <br />
+ Property: <code class="highlighter-rouge">hoodie.parquet.block.size</code> <br />
+ <span style="color:grey">Parquet RowGroup size. Its better this is same as the file size, so that a single column within a file is stored continuously on disk</span></li>
+ <li><a href="#parquetPageSize">parquetPageSize</a> (pagesize = 1MB) <br />
+ Property: <code class="highlighter-rouge">hoodie.parquet.page.size</code> <br />
<span style="color:grey">Parquet page size. Page is the unit of read within a parquet file. Within a block, pages are compressed seperately. </span></li>
- <li><a href="#logFileMaxSize">logFileMaxSize</a> (logFileSize = 1GB) <br />
+ <li><a href="#parquetCompressionRatio">parquetCompressionRatio</a> (parquetCompressionRatio = 0.1) <br />
+ Property: <code class="highlighter-rouge">hoodie.parquet.compression.ratio</code> <br />
+ <span style="color:grey">Expected compression of parquet data used by Hudi, when it tries to size new parquet files. Increase this value, if bulk_insert is producing smaller than expected sized files</span></li>
+ <li><a href="#logFileMaxSize">logFileMaxSize</a> (logFileSize = 1GB) <br />
+ Property: <code class="highlighter-rouge">hoodie.logfile.max.size</code> <br />
<span style="color:grey">LogFile max size. This is the maximum size allowed for a log file before it is rolled over to the next version. </span></li>
- <li><a href="#logFileDataBlockMaxSize">logFileDataBlockMaxSize</a> (dataBlockSize = 256MB) <br />
+ <li><a href="#logFileDataBlockMaxSize">logFileDataBlockMaxSize</a> (dataBlockSize = 256MB) <br />
+ Property: <code class="highlighter-rouge">hoodie.logfile.data.block.max.size</code> <br />
<span style="color:grey">LogFile Data block max size. This is the maximum size allowed for a single data block to be appended to a log file. This helps to make sure the data appended to the log file is broken up into sizable blocks to prevent from OOM errors. This size should be greater than the JVM memory. </span></li>
- </ul>
- </li>
- <li><a href="#withCompactionConfig">withCompactionConfig</a> (HoodieCompactionConfig) <br />
- <span style="color:grey">Cleaning and configurations related to compaction techniques</span>
- <ul>
- <li><a href="#withCleanerPolicy">withCleanerPolicy</a> (policy = KEEP_LATEST_COMMITS) <br />
- <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span></li>
- <li><a href="#retainCommits">retainCommits</a> (no_of_commits_to_retain = 24) <br />
+ <li><a href="#logFileToParquetCompressionRatio">logFileToParquetCompressionRatio</a> (logFileToParquetCompressionRatio = 0.35) <br />
+ Property: <code class="highlighter-rouge">hoodie.logfile.to.parquet.compression.ratio</code> <br />
+ <span style="color:grey">Expected additional compression as records move from log files to parquet. Used for merge_on_read storage to send inserts into log files & control the size of compacted parquet file.</span></li>
+ </ul>
+ </li>
+</ul>
+
+<h4 id="compaction-configs">Compaction configs</h4>
+<p>Configs that control compaction (merging of log files onto a new parquet base file), cleaning (reclamation of older/unused file groups).</p>
+
+<ul>
+ <li><a href="#withCompactionConfig">withCompactionConfig</a> (HoodieCompactionConfig) <br />
+ <ul>
+ <li><a href="#withCleanerPolicy">withCleanerPolicy</a> (policy = KEEP_LATEST_COMMITS) <br />
+ Property: <code class="highlighter-rouge">hoodie.cleaner.policy</code> <br />
+ <span style="color:grey"> Cleaning policy to be used. Hudi will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span></li>
+ <li><a href="#retainCommits">retainCommits</a> (no_of_commits_to_retain = 24) <br />
+ Property: <code class="highlighter-rouge">hoodie.cleaner.commits.retained</code> <br />
<span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span></li>
- <li><a href="#archiveCommitsWith">archiveCommitsWith</a> (minCommits = 96, maxCommits = 128) <br />
- <span style="color:grey">Each commit is a small file in the .hoodie directory. Since HDFS is not designed to handle multiple small files, hoodie archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span></li>
- <li><a href="#compactionSmallFileSize">compactionSmallFileSize</a> (size = 0) <br />
- <span style="color:grey">Small files can always happen because of the number of insert records in a paritition in a batch. Hoodie has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a “small file size”. This should be less < maxFileSize and setting it to 0, turns off this feature. </span></li>
- <li><a href="#insertSplitSize">insertSplitSize</a> (size = 500000) <br />
+ <li><a href="#archiveCommitsWith">archiveCommitsWith</a> (minCommits = 96, maxCommits = 128) <br />
+ Property: <code class="highlighter-rouge">hoodie.keep.min.commits</code>, <code class="highlighter-rouge">hoodie.keep.max.commits</code> <br />
+ <span style="color:grey">Each commit is a small file in the <code class="highlighter-rouge">.hoodie</code> directory. Since DFS typically does not favor lots of small files, Hudi archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span></li>
+ <li><a href="#compactionSmallFileSize">compactionSmallFileSize</a> (size = 0) <br />
+ Property: <code class="highlighter-rouge">hoodie.parquet.small.file.limit</code> <br />
+ <span style="color:grey">This should be less < maxFileSize and setting it to 0, turns off this feature. Small files can always happen because of the number of insert records in a partition in a batch. Hudi has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a “small file size”.</span></li>
+ <li><a href="#insertSplitSize">insertSplitSize</a> (size = 500000) <br />
+ Property: <code class="highlighter-rouge">hoodie.copyonwrite.insert.split.size</code> <br />
<span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span></li>
- <li><a href="#autoTuneInsertSplits">autoTuneInsertSplits</a> (true) <br />
- <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit’s metadata. Turned off by default. </span></li>
- <li><a href="#approxRecordSize">approxRecordSize</a> () <br />
- <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit’s metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span></li>
- <li><a href="#withCompactionLazyBlockReadEnabled">withCompactionLazyBlockReadEnabled</a> (true) <br />
- <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span></li>
- <li><a href="#withMaxNumDeltaCommitsBeforeCompaction">withMaxNumDeltaCommitsBeforeCompaction</a> (maxNumDeltaCommitsBeforeCompaction = 10) <br />
+ <li><a href="#autoTuneInsertSplits">autoTuneInsertSplits</a> (true) <br />
+ Property: <code class="highlighter-rouge">hoodie.copyonwrite.insert.auto.split</code> <br />
+ <span style="color:grey">Should hudi dynamically compute the insertSplitSize based on the last 24 commit’s metadata. Turned off by default. </span></li>
+ <li><a href="#approxRecordSize">approxRecordSize</a> () <br />
+ Property: <code class="highlighter-rouge">hoodie.copyonwrite.record.size.estimate</code> <br />
+ <span style="color:grey">The average record size. If specified, hudi will use this and not compute dynamically based on the last 24 commit’s metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span></li>
+ <li><a href="#withInlineCompaction">withInlineCompaction</a> (inlineCompaction = false) <br />
+ Property: <code class="highlighter-rouge">hoodie.compact.inline</code> <br />
+ <span style="color:grey">When set to true, compaction is triggered by the ingestion itself, right after a commit/deltacommit action as part of insert/upsert/bulk_insert</span></li>
+ <li><a href="#withMaxNumDeltaCommitsBeforeCompaction">withMaxNumDeltaCommitsBeforeCompaction</a> (maxNumDeltaCommitsBeforeCompaction = 10) <br />
+ Property: <code class="highlighter-rouge">hoodie.compact.inline.max.delta.commits</code> <br />
<span style="color:grey">Number of max delta commits to keep before triggering an inline compaction</span></li>
- <li><a href="#withCompactionReverseLogReadEnabled">withCompactionReverseLogReadEnabled</a> (false) <br />
+ <li><a href="#withCompactionLazyBlockReadEnabled">withCompactionLazyBlockReadEnabled</a> (true) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.lazy.block.read</code> <br />
+ <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span></li>
+ <li><a href="#withCompactionReverseLogReadEnabled">withCompactionReverseLogReadEnabled</a> (false) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.reverse.log.read</code> <br />
<span style="color:grey">HoodieLogFormatReader reads a logfile in the forward direction starting from pos=0 to pos=file_length. If this config is set to true, the Reader reads the logfile in reverse direction, from pos=file_length to pos=0</span></li>
- </ul>
- </li>
- <li><a href="#withMetricsConfig">withMetricsConfig</a> (HoodieMetricsConfig) <br />
- <span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
- <ul>
- <li><a href="#on">on</a> (true) <br />
+ <li><a href="#withCleanerParallelism">withCleanerParallelism</a> (cleanerParallelism = 200) <br />
+ Property: <code class="highlighter-rouge">hoodie.cleaner.parallelism</code> <br />
+ <span style="color:grey">Increase this if cleaning becomes slow.</span></li>
+ <li><a href="#withCompactionStrategy">withCompactionStrategy</a> (compactionStrategy = com.uber.hoodie.io.compact.strategy.LogFileSizeBasedCompactionStrategy) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.strategy</code> <br />
+ <span style="color:grey">Compaction strategy decides which file groups are picked up for compaction during each compaction run. By default. Hudi picks the log file with most accumulated unmerged data</span></li>
+ <li><a href="#withTargetIOPerCompactionInMB">withTargetIOPerCompactionInMB</a> (targetIOPerCompactionInMB = 500000) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.target.io</code> <br />
+ <span style="color:grey">Amount of MBs to spend during compaction run for the LogFileSizeBasedCompactionStrategy. This value helps bound ingestion latency while compaction is run inline mode.</span></li>
+ <li><a href="#withTargetPartitionsPerDayBasedCompaction">withTargetPartitionsPerDayBasedCompaction</a> (targetPartitionsPerCompaction = 10) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.daybased.target</code> <br />
+ <span style="color:grey">Used by com.uber.hoodie.io.compact.strategy.DayBasedCompactionStrategy to denote the number of latest partitions to compact during a compaction run.</span></li>
+ <li><a href="#payloadClassName">withPayloadClass</a> (payloadClassName = com.uber.hoodie.common.model.HoodieAvroPayload) <br />
+ Property: <code class="highlighter-rouge">hoodie.compaction.payload.class</code> <br />
+ <span style="color:grey">This needs to be same as class used during insert/upserts. Just like writing, compaction also uses the record payload class to merge records in the log against each other, merge again with the base file and produce the final record to be written after compaction.</span></li>
+ </ul>
+ </li>
+</ul>
+
+<h4 id="metrics-configs">Metrics configs</h4>
+<p>Enables reporting of Hudi metrics to graphite.</p>
+
+<ul>
+ <li><a href="#withMetricsConfig">withMetricsConfig</a> (HoodieMetricsConfig) <br />
+<span style="color:grey">Hudi publishes metrics on every commit, clean, rollback etc.</span>
+ <ul>
+ <li><a href="#on">on</a> (metricsOn = true) <br />
+ Property: <code class="highlighter-rouge">hoodie.metrics.on</code> <br />
<span style="color:grey">Turn sending metrics on/off. on by default.</span></li>
- <li><a href="#withReporterType">withReporterType</a> (GRAPHITE) <br />
+ <li><a href="#withReporterType">withReporterType</a> (reporterType = GRAPHITE) <br />
+ Property: <code class="highlighter-rouge">hoodie.metrics.reporter.type</code> <br />
<span style="color:grey">Type of metrics reporter. Graphite is the default and the only value suppported.</span></li>
- <li><a href="#toGraphiteHost">toGraphiteHost</a> () <br />
+ <li><a href="#toGraphiteHost">toGraphiteHost</a> (host = localhost) <br />
+ Property: <code class="highlighter-rouge">hoodie.metrics.graphite.host</code> <br />
<span style="color:grey">Graphite host to connect to</span></li>
- <li><a href="#onGraphitePort">onGraphitePort</a> () <br />
+ <li><a href="#onGraphitePort">onGraphitePort</a> (port = 4756) <br />
+ Property: <code class="highlighter-rouge">hoodie.metrics.graphite.port</code> <br />
<span style="color:grey">Graphite port to connect to</span></li>
- <li><a href="#usePrefix">usePrefix</a> () <br />
- <span style="color:grey">Standard prefix for all metrics</span></li>
- </ul>
- </li>
- <li><a href="#withMemoryConfig">withMemoryConfig</a> (HoodieMemoryConfig) <br />
- <span style="color:grey">Memory related configs</span>
- <ul>
- <li><a href="#withMaxMemoryFractionPerPartitionMerge">withMaxMemoryFractionPerPartitionMerge</a> (maxMemoryFractionPerPartitionMerge = 0.6) <br />
- <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span></li>
- <li><a href="#withMaxMemorySizePerCompactionInBytes">withMaxMemorySizePerCompactionInBytes</a> (maxMemorySizePerCompactionInBytes = 1GB) <br />
- <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span></li>
- </ul>
- </li>
- <li>
- <p><a href="s3_hoodie.html">S3Configs</a> (Hoodie S3 Configs) <br />
- <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span></p>
- </li>
- <li><a href="gcs_hoodie.html">GCSConfigs</a> (Hoodie GCS Configs) <br />
- <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span></li>
+ <li><a href="#usePrefix">usePrefix</a> (prefix = “”) <br />
+ Property: <code class="highlighter-rouge">hoodie.metrics.graphite.metric.prefix</code> <br />
+ <span style="color:grey">Standard prefix applied to all metrics. This helps to add datacenter, environment information for e.g</span></li>
</ul>
</li>
- <li><a href="#datasource">Hoodie Datasource</a> <br />
-<span style="color:grey">Configs for datasource</span>
+</ul>
+
+<h4 id="memory-configs">Memory configs</h4>
+<p>Controls memory usage for compaction and merges, performed internally by Hudi</p>
+
+<ul>
+ <li><a href="#withMemoryConfig">withMemoryConfig</a> (HoodieMemoryConfig) <br />
+<span style="color:grey">Memory related configs</span>
<ul>
- <li><a href="#writeoptions">write options</a> (write.format.option(…)) <br />
- <span style="color:grey"> Options useful for writing datasets </span>
- <ul>
- <li><a href="#OPERATION_OPT_KEY">OPERATION_OPT_KEY</a> (Default: upsert) <br />
- <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span></li>
- <li><a href="#STORAGE_TYPE_OPT_KEY">STORAGE_TYPE_OPT_KEY</a> (Default: COPY_ON_WRITE) <br />
- <span style="color:grey">The storage type for the underlying data, for this write. This can’t change between writes.</span></li>
- <li><a href="#TABLE_NAME_OPT_KEY">TABLE_NAME_OPT_KEY</a> (Default: None (mandatory)) <br />
- <span style="color:grey">Hive table name, to register the dataset into.</span></li>
- <li><a href="#PRECOMBINE_FIELD_OPT_KEY">PRECOMBINE_FIELD_OPT_KEY</a> (Default: ts) <br />
- <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
- we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span></li>
- <li><a href="#PAYLOAD_CLASS_OPT_KEY">PAYLOAD_CLASS_OPT_KEY</a> (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br />
- <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
- This will render any value set for <code class="highlighter-rouge">PRECOMBINE_FIELD_OPT_VAL</code> in-effective</span></li>
- <li><a href="#RECORDKEY_FIELD_OPT_KEY">RECORDKEY_FIELD_OPT_KEY</a> (Default: uuid) <br />
- <span style="color:grey">Record key field. Value to be used as the <code class="highlighter-rouge">recordKey</code> component of <code class="highlighter-rouge">HoodieKey</code>. Actual value
- will be obtained by invoking .toString() on the field value. Nested fields can be specified using
- the dot notation eg: <code class="highlighter-rouge">a.b.c</code></span></li>
- <li><a href="#PARTITIONPATH_FIELD_OPT_KEY">PARTITIONPATH_FIELD_OPT_KEY</a> (Default: partitionpath) <br />
- <span style="color:grey">Partition path field. Value to be used at the <code class="highlighter-rouge">partitionPath</code> component of <code class="highlighter-rouge">HoodieKey</code>.
- Actual value ontained by invoking .toString()</span></li>
- <li><a href="#KEYGENERATOR_CLASS_OPT_KEY">KEYGENERATOR_CLASS_OPT_KEY</a> (Default: com.uber.hoodie.SimpleKeyGenerator) <br />
- <span style="color:grey">Key generator class, that implements will extract the key out of incoming <code class="highlighter-rouge">Row</code> object</span></li>
- <li><a href="#COMMIT_METADATA_KEYPREFIX_OPT_KEY">COMMIT_METADATA_KEYPREFIX_OPT_KEY</a> (Default: <code class="highlighter-rouge">_</code>) <br />
- <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
- This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span></li>
- </ul>
- </li>
- <li><a href="#readoptions">read options</a> (read.format.option(…)) <br />
- <span style="color:grey">Options useful for reading datasets</span>
- <ul>
- <li><a href="#VIEW_TYPE_OPT_KEY">VIEW_TYPE_OPT_KEY</a> (Default: = read_optimized) <br />
- <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
- (or) Read Optimized mode (obtain latest view, based on columnar data)
- (or) Real time mode (obtain latest view, based on row & columnar data)</span></li>
- <li><a href="#BEGIN_INSTANTTIME_OPT_KEY">BEGIN_INSTANTTIME_OPT_KEY</a> (Default: None (Mandatory in incremental mode)) <br />
- <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
- necessarily correspond to an instant on the timeline. New data written with an
- <code class="highlighter-rouge">instant_time > BEGIN_INSTANTTIME</code> are fetched out. For e.g: ‘20170901080000’ will get
- all new data written after Sep 1, 2017 08:00AM.</span></li>
- <li><a href="#END_INSTANTTIME_OPT_KEY">END_INSTANTTIME_OPT_KEY</a> (Default: latest instant (i.e fetches all new data since begin instant time)) <br />
- <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
- <code class="highlighter-rouge">instant_time <= END_INSTANTTIME</code> are fetched out.</span></li>
- </ul>
- </li>
+ <li><a href="#withMaxMemoryFractionPerPartitionMerge">withMaxMemoryFractionPerPartitionMerge</a> (maxMemoryFractionPerPartitionMerge = 0.6) <br />
+ Property: <code class="highlighter-rouge">hoodie.memory.merge.fraction</code> <br />
+ <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span></li>
+ <li><a href="#withMaxMemorySizePerCompactionInBytes">withMaxMemorySizePerCompactionInBytes</a> (maxMemorySizePerCompactionInBytes = 1GB) <br />
+ Property: <code class="highlighter-rouge">hoodie.memory.compaction.fraction</code> <br />
+ <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span></li>
</ul>
</li>
</ul>
@@ -519,14 +709,11 @@
<p>Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.</p>
-<p><strong>Write operations</strong> : Use <code class="highlighter-rouge">bulkinsert</code> to load new data into a table, and there on use <code class="highlighter-rouge">upsert</code>/<code class="highlighter-rouge">insert</code>.
- Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.</p>
-
-<p><strong>Input Parallelism</strong> : By default, Hoodie tends to over-partition input (i.e <code class="highlighter-rouge">withParallelism(1500)</code>), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism <code class="highlighter-rouge">hoodie.[insert|upsert|bulkinsert].shuffle.parallelism</code> such that its atleast input_data_size/500MB</p>
+<p><strong>Input Parallelism</strong> : By default, Hudi tends to over-partition input (i.e <code class="highlighter-rouge">withParallelism(1500)</code>), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism <code class="highlighter-rouge">hoodie.[insert|upsert|bulkinsert].shuffle.parallelism</code> such that its atleast input_data_size/500MB</p>
-<p><strong>Off-heap memory</strong> : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like <code class="highlighter-rouge">spark.yarn.executor.memoryOverhead</code> or <code class="highlighter-rouge">spark.yarn.driver.memoryOverhead</code>, if you are running into such failures.</p>
+<p><strong>Off-heap memory</strong> : Hudi writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like <code class="highlighter-rouge">spark.yarn.executor.memoryOverhead</code> or <code class="highlighter-rouge">spark.yarn.driver.memoryOverhead</code>, if you are running into such failures.</p>
-<p><strong>Spark Memory</strong> : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some <code class="highlighter-rouge">spark.storage.memoryFraction</code> will generally help boost performance.</p>
+<p><strong>Spark Memory</strong> : Typically, hudi needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some <code class="highlighter-rouge">spark.storage.memoryFraction</code> will generally help boost performance.</p>
<p><strong>Sizing files</strong> : Set <code class="highlighter-rouge">limitFileSize</code> above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.</p>
diff --git a/content/contributing.html b/content/contributing.html
index 1901952..9c9e61d 100644
--- a/content/contributing.html
+++ b/content/contributing.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" developer setup">
+<meta name="keywords" content="hudi, ide, developer, setup">
<title>Developer Setup | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -380,6 +384,8 @@ have an open source license <a href="https://www.apache.org/legal/resolved.html#
<li>Add adequate tests for your new functionality</li>
<li>[Optional] For involved changes, its best to also run the entire integration test suite using <code class="highlighter-rouge">mvn clean install</code></li>
<li>For website changes, please build the site locally & test navigation, formatting & links thoroughly</li>
+ <li>If your code change changes some aspect of documentation (e.g new config, default value change),
+please ensure there is a another PR to <a href="https://github.com/apache/incubator-hudi/blob/asf-site/docs/README.md">update the docs</a> as well.</li>
</ul>
</li>
<li>Format commit messages and the pull request title like <code class="highlighter-rouge">[HUDI-XXX] Fixes bug in Spark Datasource</code>,
diff --git a/content/css/customstyles.css b/content/css/customstyles.css
index d6667a5..56dcdba 100644
--- a/content/css/customstyles.css
+++ b/content/css/customstyles.css
@@ -1,5 +1,5 @@
body {
- font-size:15px;
+ font-size:14px;
}
.bs-callout {
@@ -607,7 +607,7 @@ a.fa.fa-envelope-o.mailto {
font-weight: 600;
}
-h3 {color: #ED1951; font-weight:normal; font-size:130%;}
+h3 {color: #545253; font-weight:normal; font-size:130%;}
h4 {color: #808080; font-weight:normal; font-size:120%; font-style:italic;}
.alert, .callout {
diff --git a/content/css/theme-blue.css b/content/css/theme-blue.css
index 9a923ef..46fbd0d 100644
--- a/content/css/theme-blue.css
+++ b/content/css/theme-blue.css
@@ -5,7 +5,7 @@
}
-h3 {color: #ED1951; }
+h3 {color: #545253; }
h4 {color: #808080; }
.nav-tabs > li.active > a, .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus {
diff --git a/content/feed.xml b/content/feed.xml
index b21704e..cd76d50 100644
--- a/content/feed.xml
+++ b/content/feed.xml
@@ -5,8 +5,8 @@
<description>Apache Hudi (pronounced “Hoodie”) provides upserts and incremental processing capaibilities on Big Data</description>
<link>http://0.0.0.0:4000/</link>
<atom:link href="http://0.0.0.0:4000/feed.xml" rel="self" type="application/rss+xml"/>
- <pubDate>Mon, 25 Feb 2019 20:49:33 +0000</pubDate>
- <lastBuildDate>Mon, 25 Feb 2019 20:49:33 +0000</lastBuildDate>
+ <pubDate>Sat, 09 Mar 2019 21:08:53 +0000</pubDate>
+ <lastBuildDate>Sat, 09 Mar 2019 21:08:53 +0000</lastBuildDate>
<generator>Jekyll v3.3.1</generator>
<item>
@@ -25,7 +25,7 @@
<item>
<title>Connect with us at Strata San Jose March 2017</title>
- <description><p>We will be presenting Hoodie &amp; general concepts around how incremental processing works at Uber.
+ <description><p>We will be presenting Hudi &amp; general concepts around how incremental processing works at Uber.
Catch our talk <strong>“Incremental Processing on Hadoop At Uber”</strong></p>
</description>
diff --git a/content/gcs_hoodie.html b/content/gcs_hoodie.html
index f90992d..cb96011 100644
--- a/content/gcs_hoodie.html
+++ b/content/gcs_hoodie.html
@@ -4,8 +4,8 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="In this page, we go over how to configure hudi with Google Cloud Storage.">
-<meta name="keywords" content=" sql hive gcs spark presto">
-<title>GCS Filesystem (experimental) | Hudi</title>
+<meta name="keywords" content="hudi, hive, google cloud, storage, spark, presto">
+<title>GCS Filesystem | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -158,7 +162,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the GCS Filesystem (experimental) page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the GCS Filesystem page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -176,7 +180,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="GCS Filesystem (experimental)">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="GCS Filesystem">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -327,7 +331,7 @@
<!-- Content Column -->
<div class="col-md-9">
<div class="post-header">
- <h1 class="post-title-main">GCS Filesystem (experimental)</h1>
+ <h1 class="post-title-main">GCS Filesystem</h1>
</div>
@@ -343,7 +347,7 @@
- <p>Hudi works with HDFS by default and GCS <strong>regional</strong> buckets provide an HDFS API with strong consistency.</p>
+ <p>For Hudi storage on GCS, <strong>regional</strong> buckets provide an DFS API with strong consistency.</p>
<h2 id="gcs-configs">GCS Configs</h2>
diff --git a/content/images/hoodie_commit_duration.png b/content/images/hudi_commit_duration.png
similarity index 100%
rename from content/images/hoodie_commit_duration.png
rename to content/images/hudi_commit_duration.png
diff --git a/content/images/hoodie_intro_1.png b/content/images/hudi_intro_1.png
similarity index 100%
rename from content/images/hoodie_intro_1.png
rename to content/images/hudi_intro_1.png
diff --git a/content/images/hoodie_log_format_v2.png b/content/images/hudi_log_format_v2.png
similarity index 100%
rename from content/images/hoodie_log_format_v2.png
rename to content/images/hudi_log_format_v2.png
diff --git a/content/images/hoodie_query_perf_hive.png b/content/images/hudi_query_perf_hive.png
similarity index 100%
rename from content/images/hoodie_query_perf_hive.png
rename to content/images/hudi_query_perf_hive.png
diff --git a/content/images/hoodie_query_perf_presto.png b/content/images/hudi_query_perf_presto.png
similarity index 100%
rename from content/images/hoodie_query_perf_presto.png
rename to content/images/hudi_query_perf_presto.png
diff --git a/content/images/hoodie_query_perf_spark.png b/content/images/hudi_query_perf_spark.png
similarity index 100%
rename from content/images/hoodie_query_perf_spark.png
rename to content/images/hudi_query_perf_spark.png
diff --git a/content/images/hoodie_upsert_dag.png b/content/images/hudi_upsert_dag.png
similarity index 100%
rename from content/images/hoodie_upsert_dag.png
rename to content/images/hudi_upsert_dag.png
diff --git a/content/images/hoodie_upsert_perf1.png b/content/images/hudi_upsert_perf1.png
similarity index 100%
rename from content/images/hoodie_upsert_perf1.png
rename to content/images/hudi_upsert_perf1.png
diff --git a/content/images/hoodie_upsert_perf2.png b/content/images/hudi_upsert_perf2.png
similarity index 100%
rename from content/images/hoodie_upsert_perf2.png
rename to content/images/hudi_upsert_perf2.png
diff --git a/content/implementation.html b/content/implementation.html
index d649a70..e524ec6 100644
--- a/content/implementation.html
+++ b/content/implementation.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" implementation">
+<meta name="keywords" content="hudi, index, storage, compaction, cleaning, implementation">
<title>Implementation | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -347,7 +351,7 @@ Hudi upsert/insert is merely a Spark DAG, that can be broken into two big pieces
<ul>
<li>
- <p><strong>Indexing</strong> : A big part of Hoodie’s efficiency comes from indexing the mapping from record keys to the file ids, to which they belong to.
+ <p><strong>Indexing</strong> : A big part of Hudi’s efficiency comes from indexing the mapping from record keys to the file ids, to which they belong to.
This index also helps the <code class="highlighter-rouge">HoodieWriteClient</code> separate upserted records into inserts and updates, so they can be treated differently.
<code class="highlighter-rouge">HoodieReadClient</code> supports operations such as <code class="highlighter-rouge">filterExists</code> (used for de-duplication of table) and an efficient batch <code class="highlighter-rouge">read(keys)</code> api, that
can read out the records corresponding to the keys using the index much quickly, than a typical scan via a query. The index is also atomically
@@ -406,7 +410,7 @@ Any remaining records after that, are again packed into new file id groups, agai
<p>In the case of Copy-On-Write, a single parquet file constitutes one <code class="highlighter-rouge">file slice</code> which contains one complete version of
the file</p>
-<figure><img class="docimage" src="images/hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_log_format_v2.png" alt="hudi_log_format_v2.png" style="max-width: 1000px" /></figure>
<h4 id="merge-on-read">Merge On Read</h4>
@@ -575,7 +579,7 @@ incremental ingestion (writer at DC6) happened before the compaction (some time
The below description is with regards to compaction from file-group perspective.
<ul>
<li><code class="highlighter-rouge">Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”</code>:
-Hoodie’s implementation will be changed to become aware of file-groups currently waiting for compaction and
+Hudi’s implementation will be changed to become aware of file-groups currently waiting for compaction and
merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
@@ -602,12 +606,12 @@ the conventional alternatives for achieving these tasks.</p>
<p>Following shows the speed up obtained for NoSQL ingestion, by switching from bulk loads off HBase to Parquet to incrementally upserting
on a Hudi dataset, on 5 tables ranging from small to huge.</p>
-<figure><img class="docimage" src="images/hoodie_upsert_perf1.png" alt="hoodie_upsert_perf1.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_upsert_perf1.png" alt="hudi_upsert_perf1.png" style="max-width: 1000px" /></figure>
<p>Given Hudi can build the dataset incrementally, it opens doors for also scheduling ingesting more frequently thus reducing latency, with
significant savings on the overall compute cost.</p>
-<figure><img class="docimage" src="images/hoodie_upsert_perf2.png" alt="hoodie_upsert_perf2.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_upsert_perf2.png" alt="hudi_upsert_perf2.png" style="max-width: 1000px" /></figure>
<p>Hudi upserts have been stress tested upto 4TB in a single commit across the t1 table.</p>
@@ -618,15 +622,15 @@ with no impact on queries. Following charts compare the Hudi vs non-Hudi dataset
<p><strong>Hive</strong></p>
-<figure><img class="docimage" src="images/hoodie_query_perf_hive.png" alt="hoodie_query_perf_hive.png" style="max-width: 800px" /></figure>
+<figure><img class="docimage" src="images/hudi_query_perf_hive.png" alt="hudi_query_perf_hive.png" style="max-width: 800px" /></figure>
<p><strong>Spark</strong></p>
-<figure><img class="docimage" src="images/hoodie_query_perf_spark.png" alt="hoodie_query_perf_spark.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_query_perf_spark.png" alt="hudi_query_perf_spark.png" style="max-width: 1000px" /></figure>
<p><strong>Presto</strong></p>
-<figure><img class="docimage" src="images/hoodie_query_perf_presto.png" alt="hoodie_query_perf_presto.png" style="max-width: 1000px" /></figure>
+<figure><img class="docimage" src="images/hudi_query_perf_presto.png" alt="hudi_query_perf_presto.png" style="max-width: 1000px" /></figure>
diff --git a/content/incremental_processing.html b/content/incremental_processing.html
index a694881..c487368 100644
--- a/content/incremental_processing.html
+++ b/content/incremental_processing.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="In this page, we will discuss some available tools for ingesting data incrementally & consuming the changes.">
-<meta name="keywords" content=" incremental processing">
+<meta name="keywords" content="hudi, incremental, batch, stream, processing, Hive, ETL, Spark SQL">
<title>Incremental Processing | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -349,7 +353,7 @@ discusses a few tools that can be used to achieve these on different contexts.</
<h2 id="incremental-ingestion">Incremental Ingestion</h2>
-<p>Following means can be used to apply a delta or an incremental change to a Hudi dataset. For e.g, the incremental changes could be from a Kafka topic or files uploaded to HDFS or
+<p>Following means can be used to apply a delta or an incremental change to a Hudi dataset. For e.g, the incremental changes could be from a Kafka topic or files uploaded to DFS or
even changes pulled from another Hudi dataset.</p>
<h4 id="deltastreamer-tool">DeltaStreamer Tool</h4>
@@ -360,9 +364,10 @@ from different sources such as DFS or Kafka.</p>
<p>The tool is a spark job (part of hoodie-utilities), that provides the following functionality</p>
<ul>
- <li>Ability to consume new events from Kafka, incremental imports from Sqoop or output of <code class="highlighter-rouge">HiveIncrementalPuller</code> or files under a folder on HDFS</li>
+ <li>Ability to consume new events from Kafka, incremental imports from Sqoop or output of <code class="highlighter-rouge">HiveIncrementalPuller</code> or files under a folder on DFS</li>
<li>Support json, avro or a custom payload types for the incoming data</li>
- <li>New data is written to a Hudi dataset, with support for checkpointing & schemas and registered onto Hive</li>
+ <li>Pick up avro schemas from DFS or Confluent <a href="https://github.com/confluentinc/schema-registry">schema registry</a>.</li>
+ <li>New data is written to a Hudi dataset, with support for checkpointing and registered onto Hive</li>
</ul>
<p>Command line options describe capabilities in more detail (first build hoodie-utilities using <code class="highlighter-rouge">mvn clean package</code>).</p>
@@ -423,10 +428,10 @@ Usage: <main class> [options]
* --target-table
name of the target table in Hive
--transformer-class
- subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
- transform raw source dataset to a target dataset (conforming to target
- schema) before writing. Default : Not set. E:g -
- com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
+ subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
+ transform raw source dataset to a target dataset (conforming to target
+ schema) before writing. Default : Not set. E:g -
+ com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
allows a SQL query template to be passed as a transformation function)
</code></pre>
@@ -453,7 +458,7 @@ provided under <code class="highlighter-rouge">hoodie-utilities/src/test/resourc
</code></pre>
</div>
-<p>In some cases, you may want to convert your existing dataset into Hoodie, before you can begin ingesting new data. This can be accomplished using the <code class="highlighter-rouge">hdfsparquetimport</code> command on the <code class="highlighter-rouge">hoodie-cli</code>.
+<p>In some cases, you may want to convert your existing dataset into Hudi, before you can begin ingesting new data. This can be accomplished using the <code class="highlighter-rouge">hdfsparquetimport</code> command on the <code class="highlighter-rouge">hoodie-cli</code>.
Currently, there is support for converting parquet datasets.</p>
<h4 id="via-custom-spark-job">Via Custom Spark Job</h4>
@@ -503,8 +508,6 @@ Usage: <main class> [options]
</code></pre>
</div>
-<div class="bs-callout bs-callout-info">Note that for now, due to jar mismatches between Spark & Hive, its recommended to run this as a separate Java task in your workflow manager/cron. This is getting fix <a href="https://github.com/uber/hoodie/issues/123">here</a></div>
-
<h2 id="incrementally-pulling">Incrementally Pulling</h2>
<p>Hudi datasets can be pulled incrementally, which means you can get ALL and ONLY the updated & new rows since a specified commit timestamp.
@@ -530,7 +533,7 @@ This class can be used within existing Spark jobs and offers the following funct
<p>Please refer to <a href="configurations.html">configurations</a> section, to view all datasource options.</p>
-<p>Additionally, <code class="highlighter-rouge">HoodieReadClient</code> offers the following functionality using Hoodie’s implicit indexing.</p>
+<p>Additionally, <code class="highlighter-rouge">HoodieReadClient</code> offers the following functionality using Hudi’s implicit indexing.</p>
<table>
<tbody>
@@ -540,7 +543,7 @@ This class can be used within existing Spark jobs and offers the following funct
</tr>
<tr>
<td>read(keys)</td>
- <td>Read out the data corresponding to the keys as a DataFrame, using Hoodie’s own index for faster lookup</td>
+ <td>Read out the data corresponding to the keys as a DataFrame, using Hudi’s own index for faster lookup</td>
</tr>
<tr>
<td>filterExists()</td>
@@ -590,7 +593,7 @@ e.g: <code class="highlighter-rouge">/app/incremental-hql/intermediate/{source_t
</tr>
<tr>
<td>tmp</td>
- <td>Directory where the temporary delta data is stored in HDFS. The directory structure will follow conventions. Please see the below section.</td>
+ <td>Directory where the temporary delta data is stored in DFS. The directory structure will follow conventions. Please see the below section.</td>
<td> </td>
</tr>
<tr>
@@ -610,12 +613,12 @@ e.g: <code class="highlighter-rouge">/app/incremental-hql/intermediate/{source_t
</tr>
<tr>
<td>sourceDataPath</td>
- <td>Source HDFS Base Path. This is where the Hudi metadata will be read.</td>
+ <td>Source DFS Base Path. This is where the Hudi metadata will be read.</td>
<td> </td>
</tr>
<tr>
<td>targetDataPath</td>
- <td>Target HDFS Base path. This is needed to compute the fromCommitTime. This is not needed if fromCommitTime is specified explicitly.</td>
+ <td>Target DFS Base path. This is needed to compute the fromCommitTime. This is not needed if fromCommitTime is specified explicitly.</td>
<td> </td>
</tr>
<tr>
@@ -647,7 +650,6 @@ it will automatically use the backfill configuration, since applying the last 24
is the lack of support for self-joining the same table in mixed mode (normal and incremental modes).</p>
-
<div class="tags">
</div>
diff --git a/content/index.html b/content/index.html
index bd31b4d..1a1c5ff 100644
--- a/content/index.html
+++ b/content/index.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing.">
-<meta name="keywords" content="getting_started, homepage">
+<meta name="keywords" content="big data, stream processing, cloud, hdfs, storage, upserts, change capture">
<title>What is Hudi? | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -366,7 +370,7 @@ $('#toc').on('click', 'a', function() {
- <p>Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets on <a href="http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html">HDFS</a> or cloud stores and provides three logical views for query access.</p>
+ <p>Hudi (pronounced “Hoodie”) ingests & manages storage of large analytical datasets over DFS (<a href="http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html">HDFS</a> or cloud stores) and provides three logical views for query access.</p>
<ul>
<li><strong>Read Optimized View</strong> - Provides excellent query performance on pure columnar storage, much like plain <a href="https://parquet.apache.org/">Parquet</a> tables.</li>
@@ -374,7 +378,7 @@ $('#toc').on('click', 'a', function() {
<li><strong>Near-Real time Table</strong> - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + <a href="http://avro.apache.org/docs/current/mr.html">Avro</a>)</li>
</ul>
-<figure><img class="docimage" src="images/hoodie_intro_1.png" alt="hoodie_intro_1.png" /></figure>
+<figure><img class="docimage" src="images/hudi_intro_1.png" alt="hudi_intro_1.png" /></figure>
<p>By carefully managing how data is laid out in storage & how it’s exposed to queries, Hudi is able to power a rich data ecosystem where external sources can be ingested in near real-time and made available for interactive SQL Engines like <a href="https://prestodb.io">Presto</a> & <a href="https://spark.apache.org/sql/">Spark</a>, while at the same time capable of being consumed incrementally from processing/ETL frameworks like <a href="https://hive.apache.org/">Hive</a> & [...]
diff --git a/content/js/mydoc_scroll.html b/content/js/mydoc_scroll.html
index b23a6ad..ee70719 100644
--- a/content/js/mydoc_scroll.html
+++ b/content/js/mydoc_scroll.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="This page demonstrates how you the integration of a script called ScrollTo, which is used here to link definitions of a JSON code sample to a list of definit...">
-<meta name="keywords" content="special_layouts, json, scrolling, scrollto, jquery plugin">
+<meta name="keywords" content="json, scrolling, scrollto, jquery plugin">
<title>Scroll layout | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
diff --git a/content/migration_guide.html b/content/migration_guide.html
index 7bcfa1d..03ea8a1 100644
--- a/content/migration_guide.html
+++ b/content/migration_guide.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset">
-<meta name="keywords" content=" migration guide">
+<meta name="keywords" content="hudi, migration, use case">
<title>Migration Guide | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -362,7 +366,7 @@ Take this approach if your dataset is an append only type of dataset and you do
<p>Import your existing dataset into a Hudi managed dataset. Since all the data is Hudi managed, none of the limitations
of Approach 1 apply here. Updates spanning any partitions can be applied to this dataset and Hudi will efficiently
- make the update available to queries. Note that not only do you get to use all Hoodie primitives on this dataset,
+ make the update available to queries. Note that not only do you get to use all Hudi primitives on this dataset,
there are other additional advantages of doing this. Hudi automatically manages file sizes of a Hudi managed dataset
. You can define the desired file size when converting this dataset and Hudi will ensure it writes out files
adhering to the config. It will also ensure that smaller files later get corrected by routing some new inserts into
@@ -371,9 +375,8 @@ Take this approach if your dataset is an append only type of dataset and you do
<p>There are a few options when choosing this approach.</p>
<h4 id="option-1">Option 1</h4>
-<p>Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in
-parquet file
-format. This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.</p>
+<p>Use the HDFSParquetImporter tool. As the name suggests, this only works if your existing dataset is in parquet file format.
+This tool essentially starts a Spark Job to read the existing parquet dataset and converts it into a HUDI managed dataset by re-writing all the data.</p>
<h4 id="option-2">Option 2</h4>
<p>For huge datasets, this could be as simple as : for partition in [list of partitions in source dataset] {
@@ -385,7 +388,7 @@ format. This tool essentially starts a Spark Job to read the existing parquet da
<p>Write your own custom logic of how to load an existing dataset into a Hudi managed one. Please read about the RDD API
<a href="quickstart.html">here</a>.</p>
-<div class="highlighter-rouge"><pre class="highlight"><code>Using the HDFSParquetImporter Tool. Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be
+<div class="highlighter-rouge"><pre class="highlight"><code>Using the HDFSParquetImporter Tool. Once hudi has been built via `mvn clean install -DskipTests`, the shell can be
fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
hoodie->hdfsparquetimport
diff --git a/content/news.html b/content/news.html
index 645bae0..43d92a3 100644
--- a/content/news.html
+++ b/content/news.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" news, blog, updates, release notes, announcements">
+<meta name="keywords" content="apache, hudi, news, blog, updates, release notes, announcements">
<title>News | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -266,7 +270,7 @@
<a href="tag_news.html">news</a>
</span>
- <p> We will be presenting Hoodie & general concepts around how incremental processing works at Uber.
+ <p> We will be presenting Hudi & general concepts around how incremental processing works at Uber.
Catch our talk “Incremental Processing on Hadoop At Uber”
</p>
diff --git a/content/news_archive.html b/content/news_archive.html
index 4d80715..d1986b5 100644
--- a/content/news_archive.html
+++ b/content/news_archive.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" news, blog, updates, release notes, announcements">
+<meta name="keywords" content="news, blog, updates, release notes, announcements">
<title>News | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
diff --git a/content/powered_by.html b/content/powered_by.html
index 8f4b0d4..99991ca 100644
--- a/content/powered_by.html
+++ b/content/powered_by.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" talks">
+<meta name="keywords" content="hudi, talks, presentation">
<title>Talks & Powered By | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -383,7 +387,6 @@ October 2018, Spark+AI Summit Europe, London, UK</p>
</ol>
-
<div class="tags">
</div>
diff --git a/content/privacy.html b/content/privacy.html
index 704bd3d..1804b9f 100644
--- a/content/privacy.html
+++ b/content/privacy.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content=" privacy">
+<meta name="keywords" content="hudi, privacy">
<title>Privacy Policy | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
diff --git a/content/quickstart.html b/content/quickstart.html
index a73534d..b7781b3 100644
--- a/content/quickstart.html
+++ b/content/quickstart.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content="quickstart, quickstart">
+<meta name="keywords" content="hudi, quickstart">
<title>Quickstart | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -362,7 +366,8 @@ $ mvn clean install -DskipTests -DskipITs -Dhive11
<h2 id="version-compatibility">Version Compatibility</h2>
-<p>Hudi requires Java 8 to be installed. Hudi works with Spark-2.x versions. We have verified that Hudi works with the following combination of Hadoop/Hive/Spark.</p>
+<p>Hudi requires Java 8 to be installed on a *nix system. Hudi works with Spark-2.x versions.
+Further, we have verified that Hudi works with the following combination of Hadoop/Hive/Spark.</p>
<table>
<thead>
@@ -395,8 +400,9 @@ $ mvn clean install -DskipTests -DskipITs -Dhive11
</tbody>
</table>
-<p>If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues. We are limited by our bandwidth to certify other combinations.
-It would be of great help if you can reach out to us with your setup and experience with hoodie.</p>
+<p>If your environment has other versions of hadoop/hive/spark, please try out Hudi and let us know if there are any issues.
+We are limited by our bandwidth to certify other combinations (e.g Docker on Windows).
+It would be of great help if you can reach out to us with your setup and experience with hudi.</p>
<h2 id="generate-a-hudi-dataset">Generate a Hudi Dataset</h2>
@@ -424,7 +430,7 @@ Use the RDD API to perform more involved actions on a Hudi dataset</p>
<h4 id="datasource-api">DataSource API</h4>
-<p>Run <strong>hoodie-spark/src/test/java/HoodieJavaApp.java</strong> class, to place a two commits (commit 1 => 100 inserts, commit 2 => 100 updates to previously inserted 100 records) onto your HDFS/local filesystem. Use the wrapper script
+<p>Run <strong>hoodie-spark/src/test/java/HoodieJavaApp.java</strong> class, to place a two commits (commit 1 => 100 inserts, commit 2 => 100 updates to previously inserted 100 records) onto your DFS/local filesystem. Use the wrapper script
to run from command-line</p>
<div class="highlighter-rouge"><pre class="highlight"><code>cd hoodie-spark
@@ -679,9 +685,9 @@ data infrastructure is brought up in a local docker cluster within your computer
<h3 id="setting-up-docker-cluster">Setting up Docker Cluster</h3>
-<h4 id="build-hoodie">Build Hoodie</h4>
+<h4 id="build-hudi">Build Hudi</h4>
-<p>The first step is to build hoodie
+<p>The first step is to build hudi
<code class="highlighter-rouge">
cd <HUDI_WORKSPACE>
mvn package -DskipTests
@@ -801,7 +807,7 @@ automatically initializes the datasets in the file-system if they do not exist y
<div class="highlighter-rouge"><pre class="highlight"><code>docker exec -it adhoc-2 /bin/bash
# Run the following spark-submit command to execute the delta-streamer and ingest to stock_ticks_cow dataset in HDFS
-spark-submit --class com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer $HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts --target-base-path /user/hive/warehouse/stock_ticks_cow --target-table stock_ticks_cow --props /var/demo/config/kafka-source.properties
+spark-submit --class com.uber.hoodie.utilities.deltastreamer.HoodieDeltaStreamer $HUDI_UTILITIES_BUNDLE --storage-type COPY_ON_WRITE --source-class com.uber.hoodie.utilities.sources.JsonKafkaSource --source-ordering-field ts --target-base-path /user/hive/warehouse/stock_ticks_cow --target-table stock_ticks_cow --props /var/demo/config/kafka-source.properties --schemaprovider-class com.uber.hoodie.utilities.schema.FilebasedSchemaProvider
....
....
2018-09-24 22:20:00 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint:54 - OutputCommitCoordinator stopped!
@@ -1329,7 +1335,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
Again, You can use Hudi CLI to manually schedule and run compaction</p>
<div class="highlighter-rouge"><pre class="highlight"><code>docker exec -it adhoc-1 /bin/bash
-^[[Aroot@adhoc-1:/opt# /var/hoodie/ws/hoodie-cli/hoodie-cli.sh
+root@adhoc-1:/opt# /var/hoodie/ws/hoodie-cli/hoodie-cli.sh
============================================
* *
* _ _ _ _ *
@@ -1514,7 +1520,7 @@ scala> spark.sql("select `_hoodie_commit_time`, symbol, ts, volume, open, clo
<h2 id="testing-hudi-in-local-docker-environment">Testing Hudi in Local Docker environment</h2>
-<p>You can bring up a hadoop docker environment containing Hadoop, Hive and Spark services with support for hoodie.
+<p>You can bring up a hadoop docker environment containing Hadoop, Hive and Spark services with support for hudi.
<code class="highlighter-rouge">
$ mvn pre-integration-test -DskipTests
</code>
diff --git a/content/s3_hoodie.html b/content/s3_hoodie.html
index 217005c..0366721 100644
--- a/content/s3_hoodie.html
+++ b/content/s3_hoodie.html
@@ -4,8 +4,8 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="In this page, we go over how to configure Hudi with S3 filesystem.">
-<meta name="keywords" content=" sql hive s3 spark presto">
-<title>S3 Filesystem (experimental) | Hudi</title>
+<meta name="keywords" content="hudi, hive, aws, s3, spark, presto">
+<title>S3 Filesystem | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -158,7 +162,7 @@
- <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the S3 Filesystem (experimental) page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:dev@hudi.apache.org?subject=Hudi Documentation feedback&body=I have some feedback about the S3 Filesystem page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> Feedback</a>
<li>
@@ -176,7 +180,7 @@
searchInput: document.getElementById('search-input'),
resultsContainer: document.getElementById('results-container'),
dataSource: 'search.json',
- searchResultTemplate: '<li><a href="{url}" title="S3 Filesystem (experimental)">{title}</a></li>',
+ searchResultTemplate: '<li><a href="{url}" title="S3 Filesystem">{title}</a></li>',
noResultsText: 'No results found.',
limit: 10,
fuzzy: true,
@@ -327,7 +331,7 @@
<!-- Content Column -->
<div class="col-md-9">
<div class="post-header">
- <h1 class="post-title-main">S3 Filesystem (experimental)</h1>
+ <h1 class="post-title-main">S3 Filesystem</h1>
</div>
@@ -343,11 +347,11 @@
- <p>Hudi works with HDFS by default. There is an experimental work going on Hoodie-S3 compatibility.</p>
+ <p>In this page, we explain how to get your Hudi spark job to store into AWS S3.</p>
<h2 id="aws-configs">AWS configs</h2>
-<p>There are two configurations required for Hoodie-S3 compatibility:</p>
+<p>There are two configurations required for Hudi-S3 compatibility:</p>
<ul>
<li>Adding AWS Credentials for Hudi</li>
@@ -415,7 +419,6 @@ export HOODIE_ENV_fs_DOT_s3n_DOT_impl=org.apache.hadoop.fs.s3a.S3AFileSystem
</ul>
-
<div class="tags">
</div>
diff --git a/content/search.json b/content/search.json
index 3f7eb15..0473b34 100644
--- a/content/search.json
+++ b/content/search.json
@@ -6,7 +6,7 @@
{
"title": "Admin Guide",
"tags": "",
-"keywords": "admin",
+"keywords": "hudi, administration, operation, devops",
"url": "admin_guide.html",
"summary": "This section offers an overview of tools available to operate an ecosystem of Hudi datasets"
}
@@ -17,7 +17,7 @@
{
"title": "Community",
"tags": "",
-"keywords": "usecases",
+"keywords": "hudi, use cases, big data, apache",
"url": "community.html",
"summary": ""
}
@@ -28,7 +28,7 @@
{
"title": "Comparison",
"tags": "",
-"keywords": "usecases",
+"keywords": "apache, hudi, kafka, kudu, hive, hbase, stream processing",
"url": "comparison.html",
"summary": ""
}
@@ -39,7 +39,7 @@
{
"title": "Concepts",
"tags": "",
-"keywords": "concepts",
+"keywords": "hudi, design, storage, views, timeline",
"url": "concepts.html",
"summary": "Here we introduce some basic concepts & give a broad technical overview of Hudi"
}
@@ -50,7 +50,7 @@
{
"title": "Configurations",
"tags": "",
-"keywords": "configurations",
+"keywords": "garbage collection, hudi, jvm, configs, tuning",
"url": "configurations.html",
"summary": "Here we list all possible configurations and what they mean"
}
@@ -61,7 +61,7 @@
{
"title": "Developer Setup",
"tags": "",
-"keywords": "developer setup",
+"keywords": "hudi, ide, developer, setup",
"url": "contributing.html",
"summary": ""
}
@@ -72,9 +72,9 @@
{
-"title": "GCS Filesystem (experimental)",
+"title": "GCS Filesystem",
"tags": "",
-"keywords": "sql hive gcs spark presto",
+"keywords": "hudi, hive, google cloud, storage, spark, presto",
"url": "gcs_hoodie.html",
"summary": "In this page, we go over how to configure hudi with Google Cloud Storage."
}
@@ -85,7 +85,7 @@
{
"title": "Implementation",
"tags": "",
-"keywords": "implementation",
+"keywords": "hudi, index, storage, compaction, cleaning, implementation",
"url": "implementation.html",
"summary": ""
}
@@ -96,7 +96,7 @@
{
"title": "Incremental Processing",
"tags": "",
-"keywords": "incremental processing",
+"keywords": "hudi, incremental, batch, stream, processing, Hive, ETL, Spark SQL",
"url": "incremental_processing.html",
"summary": "In this page, we will discuss some available tools for ingesting data incrementally & consuming the changes."
}
@@ -107,7 +107,7 @@
{
"title": "What is Hudi?",
"tags": "getting_started",
-"keywords": "homepage",
+"keywords": "big data, stream processing, cloud, hdfs, storage, upserts, change capture",
"url": "index.html",
"summary": "Hudi brings stream processing to big data, providing fresh data while being an order of magnitude efficient over traditional batch processing."
}
@@ -118,7 +118,7 @@
{
"title": "Migration Guide",
"tags": "",
-"keywords": "migration guide",
+"keywords": "hudi, migration, use case",
"url": "migration_guide.html",
"summary": "In this page, we will discuss some available tools for migrating your existing dataset into a Hudi dataset"
}
@@ -140,7 +140,7 @@
{
"title": "News",
"tags": "",
-"keywords": "news, blog, updates, release notes, announcements",
+"keywords": "apache, hudi, news, blog, updates, release notes, announcements",
"url": "news.html",
"summary": ""
}
@@ -162,7 +162,7 @@
{
"title": "Talks & Powered By",
"tags": "",
-"keywords": "talks",
+"keywords": "hudi, talks, presentation",
"url": "powered_by.html",
"summary": ""
}
@@ -173,7 +173,7 @@
{
"title": "Privacy Policy",
"tags": "",
-"keywords": "privacy",
+"keywords": "hudi, privacy",
"url": "privacy.html",
"summary": ""
}
@@ -184,7 +184,7 @@
{
"title": "Quickstart",
"tags": "quickstart",
-"keywords": "quickstart",
+"keywords": "hudi, quickstart",
"url": "quickstart.html",
"summary": ""
}
@@ -193,9 +193,9 @@
{
-"title": "S3 Filesystem (experimental)",
+"title": "S3 Filesystem",
"tags": "",
-"keywords": "sql hive s3 spark presto",
+"keywords": "hudi, hive, aws, s3, spark, presto",
"url": "s3_hoodie.html",
"summary": "In this page, we go over how to configure Hudi with S3 filesystem."
}
@@ -210,7 +210,7 @@
{
"title": "SQL Queries",
"tags": "",
-"keywords": "sql hive spark presto",
+"keywords": "hudi, hive, spark, sql, presto",
"url": "sql_queries.html",
"summary": "In this page, we go over how to enable SQL queries on Hudi built tables."
}
@@ -221,7 +221,7 @@
{
"title": "Use Cases",
"tags": "",
-"keywords": "usecases",
+"keywords": "hudi, data ingestion, etl, real time, use cases",
"url": "use_cases.html",
"summary": "Following are some sample use-cases for Hudi, which illustrate the benefits in terms of faster processing & increased efficiency"
}
diff --git a/content/sql_queries.html b/content/sql_queries.html
index 6936191..d7fa8cc 100644
--- a/content/sql_queries.html
+++ b/content/sql_queries.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="In this page, we go over how to enable SQL queries on Hudi built tables.">
-<meta name="keywords" content=" sql hive spark presto">
+<meta name="keywords" content="hudi, hive, spark, sql, presto">
<title>SQL Queries | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -368,8 +372,6 @@ to using the Hive Serde to read the data (planning/executions is still Spark). T
towards Parquet reading, which we will address in the next method based on path filters.
However benchmarks have not revealed any real performance degradation with Hudi & SparkSQL, compared to native support.</p>
-<div class="bs-callout bs-callout-info">Get involved to improve this integration <a href="https://github.com/uber/hoodie/issues/7">here</a> and <a href="https://issues.apache.org/jira/browse/SPARK-19351">here</a> </div>
-
<p>Sample command is provided below to spin up Spark Shell</p>
<div class="highlighter-rouge"><pre class="highlight"><code>$ spark-shell --jars hoodie-spark-bundle-x.y.z-SNAPSHOT.jar --driver-class-path /etc/hive/conf --packages com.databricks:spark-avro_2.11:4.0.0 --conf spark.sql.hive.convertMetastoreParquet=false --num-executors 10 --driver-memory 7g --executor-memory 2g --master yarn-client
diff --git a/content/strata-talk.html b/content/strata-talk.html
index 13a8375..58b6f8a 100644
--- a/content/strata-talk.html
+++ b/content/strata-talk.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="">
-<meta name="keywords" content="news, ">
+<meta name="keywords" content="">
<title>Hudi entered Apache Incubator | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
diff --git a/content/use_cases.html b/content/use_cases.html
index 6df8c34..dcdf403 100644
--- a/content/use_cases.html
+++ b/content/use_cases.html
@@ -4,7 +4,7 @@
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1">
<meta name="description" content="Following are some sample use-cases for Hudi, which illustrate the benefits in terms of faster processing & increased efficiency">
-<meta name="keywords" content=" usecases">
+<meta name="keywords" content="hudi, data ingestion, etl, real time, use cases">
<title>Use Cases | Hudi</title>
<link rel="stylesheet" href="css/syntax.css">
@@ -149,6 +149,10 @@
<li><a href="https://cwiki.apache.org/confluence/pages/viewrecentblogposts.action?key=HUDI" target="_blank">Blog</a></li>
+
+ <li><a href="https://projects.apache.org/project.html?incubator-hudi" target="_blank">Team</a></li>
+
+
</ul>
</li>
@@ -350,7 +354,7 @@ In most (if not all) Hadoop deployments, it is unfortunately solved in a pieceme
even though this data is arguably the most valuable for the entire organization.</p>
<p>For RDBMS ingestion, Hudi provides <strong>faster loads via Upserts</strong>, as opposed costly & inefficient bulk loads. For e.g, you can read the MySQL BIN log or <a href="https://sqoop.apache.org/docs/1.4.2/SqoopUserGuide.html#_incremental_imports">Sqoop Incremental Import</a> and apply them to an
-equivalent Hudi table on HDFS. This would be much faster/efficient than a <a href="https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457">bulk merge job</a>
+equivalent Hudi table on DFS. This would be much faster/efficient than a <a href="https://sqoop.apache.org/docs/1.4.0-incubating/SqoopUserGuide.html#id1770457">bulk merge job</a>
or <a href="http://hortonworks.com/blog/four-step-strategy-incremental-updates-hive/">complicated handcrafted merge workflows</a></p>
<p>For NoSQL datastores like <a href="http://cassandra.apache.org/">Cassandra</a> / <a href="http://www.project-voldemort.com/voldemort/">Voldemort</a> / <a href="https://hbase.apache.org/">HBase</a>, even moderately big installations store billions of rows.
@@ -367,13 +371,13 @@ This is absolutely perfect for lower scale (<a href="https://blog.twitter.com/20
But, typically these systems end up getting abused for less interactive queries also since data on Hadoop is intolerably stale. This leads to under utilization & wasteful hardware/license costs.</p>
<p>On the other hand, interactive SQL solutions on Hadoop such as Presto & SparkSQL excel in <strong>queries that finish within few seconds</strong>.
-By bringing <strong>data freshness to a few minutes</strong>, Hudi can provide a much efficient alternative, as well unlock real-time analytics on <strong>several magnitudes larger datasets</strong> stored in HDFS.
+By bringing <strong>data freshness to a few minutes</strong>, Hudi can provide a much efficient alternative, as well unlock real-time analytics on <strong>several magnitudes larger datasets</strong> stored in DFS.
Also, Hudi has no external dependencies (like a dedicated HBase cluster, purely used for real-time analytics) and thus enables faster analytics on much fresher analytics, without increasing the operational overhead.</p>
<h2 id="incremental-processing-pipelines">Incremental Processing Pipelines</h2>
<p>One fundamental ability Hadoop provides is to build a chain of datasets derived from each other via DAGs expressed as workflows.
-Workflows often depend on new data being output by multiple upstream workflows and traditionally, availability of new data is indicated by a new HDFS Folder/Hive Partition.
+Workflows often depend on new data being output by multiple upstream workflows and traditionally, availability of new data is indicated by a new DFS Folder/Hive Partition.
Let’s take a concrete example to illustrate this. An upstream workflow <code class="highlighter-rouge">U</code> can create a Hive partition for every hour, with data for that hour (event_time) at the end of each hour (processing_time), providing effective freshness of 1 hour.
Then, a downstream workflow <code class="highlighter-rouge">D</code>, kicks off immediately after <code class="highlighter-rouge">U</code> finishes, and does its own processing for the next hour, increasing the effective latency to 2 hours.</p>
@@ -388,19 +392,18 @@ like 15 mins, and providing an end-end latency of 30 mins at <code class="highli
<div class="bs-callout bs-callout-info">To achieve this, Hudi has embraced similar concepts from stream processing frameworks like <a href="https://spark.apache.org/docs/latest/streaming-programming-guide.html#join-operations">Spark Streaming</a> , Pub/Sub systems like <a href="http://kafka.apache.org/documentation/#theconsumer">Kafka</a>
or database replication technologies like <a href="https://docs.oracle.com/cd/E11882_01/server.112/e16545/xstrm_cncpt.htm#XSTRM187">Oracle XStream</a>.
-For the more curious, a more detailed explanation of the benefits of Incremetal Processing (compared to Stream Processing & Batch Processing) can be found <a href="https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop">here</a></div>
+For the more curious, a more detailed explanation of the benefits of Incremental Processing (compared to Stream Processing & Batch Processing) can be found <a href="https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop">here</a></div>
-<h2 id="data-dispersal-from-hadoop">Data Dispersal From Hadoop</h2>
+<h2 id="data-dispersal-from-dfs">Data Dispersal From DFS</h2>
<p>A popular use-case for Hadoop, is to crunch data and then disperse it back to an online serving store, to be used by an application.
For e.g, a Spark Pipeline can <a href="https://eng.uber.com/telematics/">determine hard braking events on Hadoop</a> and load them into a serving store like ElasticSearch, to be used by the Uber application to increase safe driving. Typical architectures for this employ a <code class="highlighter-rouge">queue</code> between Hadoop and serving store, to prevent overwhelming the target serving store.
-A popular choice for this queue is Kafka and this model often results in <strong>redundant storage of same data on HDFS (for offline analysis on computed results) and Kafka (for dispersal)</strong></p>
+A popular choice for this queue is Kafka and this model often results in <strong>redundant storage of same data on DFS (for offline analysis on computed results) and Kafka (for dispersal)</strong></p>
<p>Once again Hudi can efficiently solve this problem, by having the Spark Pipeline upsert output from
each run into a Hudi dataset, which can then be incrementally tailed (just like a Kafka topic) for new data & written into the serving store.</p>
-
<div class="tags">
</div>
[incubator-hudi-site] 07/19: Dockerized doc build
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit ada1ba23399ce8566279580ff84f94f1999a3fb0
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Fri Feb 15 20:53:49 2019 -0800
Dockerized doc build
- Fixed Dockerfile with Ruby 2.6+
- Tested along with docker-compose
- Documented docker commands
- Tweaks to json version
- Update gitignore & remove .DS_Store
---
docs/.DS_Store | Bin 8196 -> 0 bytes
docs/.gitignore | 1 +
docs/Dockerfile | 12 ++++++++----
docs/Gemfile.lock | 2 +-
docs/README.md | 10 +++++++++-
docs/community.md | 4 ++--
docs/docker-compose.yml | 13 +++++++++++++
docs/index.md | 3 +--
8 files changed, 35 insertions(+), 10 deletions(-)
diff --git a/docs/.DS_Store b/docs/.DS_Store
deleted file mode 100644
index 83b1f95..0000000
Binary files a/docs/.DS_Store and /dev/null differ
diff --git a/docs/.gitignore b/docs/.gitignore
index f380cae..e52ea46 100644
--- a/docs/.gitignore
+++ b/docs/.gitignore
@@ -2,3 +2,4 @@ _site
.sass-cache
.jekyll-metadata
.ruby-version
+.DS_Store
diff --git a/docs/Dockerfile b/docs/Dockerfile
index b1fa52c..89cc254 100644
--- a/docs/Dockerfile
+++ b/docs/Dockerfile
@@ -1,5 +1,4 @@
-FROM ruby:2.1
-MAINTAINER mrafayaleem@gmail.com
+FROM ruby:2.6
RUN apt-get clean \
&& mv /var/lib/apt/lists /var/lib/apt/lists.broke \
@@ -8,7 +7,7 @@ RUN apt-get clean \
RUN apt-get update
RUN apt-get install -y \
- node \
+ nodejs \
python-pygments \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/
@@ -16,11 +15,16 @@ RUN apt-get install -y \
WORKDIR /tmp
ADD Gemfile /tmp/
ADD Gemfile.lock /tmp/
+
+RUN gem install bundler
+RUN gem install jekyll
RUN bundle install
+RUN bundle update --bundler
+
VOLUME /src
EXPOSE 4000
WORKDIR /src
-ENTRYPOINT ["jekyll"]
+ENTRYPOINT ["bundle", "exec", "jekyll", "serve", "--force_polling", "-H", "0.0.0.0", "-P", "4000"]
diff --git a/docs/Gemfile.lock b/docs/Gemfile.lock
index 8359d57..b72b9b1 100644
--- a/docs/Gemfile.lock
+++ b/docs/Gemfile.lock
@@ -103,7 +103,7 @@ GEM
gemoji (~> 2.0)
html-pipeline (~> 2.2)
jekyll (>= 3.0)
- json (1.8.6)
+ json (2.1.0)
kramdown (1.11.1)
liquid (3.0.6)
listen (3.0.6)
diff --git a/docs/README.md b/docs/README.md
index 6c5030d..0995250 100644
--- a/docs/README.md
+++ b/docs/README.md
@@ -7,11 +7,19 @@ This folder contains resources that build the [Apache Hudi website](https://hudi
The site is based on a [Jekyll](https://jekyllrb.com/) theme hosted [here](idratherbewriting.com/documentation-theme-jekyll/) with detailed instructions.
-To build the docs, first you need to install
+#### Docker
+
+Simply run `docker-compose build --no-cache && docker-compose up` from the `docs` folder and the site should be up & running at `http://localhost:4000`
+
+
+#### Host OS
+
+To build directly on host OS (\*nix), first you need to install
- gem, ruby (using apt-get/brew)
- bundler (`gem install bundler`)
- jekyll (`gem install jekyll`)
+- Update bundler `bundle update --bundler`
and then run the following from `docs` folder to serve a local site
diff --git a/docs/community.md b/docs/community.md
index d2f207e..c508191 100644
--- a/docs/community.md
+++ b/docs/community.md
@@ -13,10 +13,10 @@ issues or pull requests against this repo. Before you do so, please sign the
Also, be sure to write unit tests for your bug fix or feature to show that it works as expected.
If the reviewer feels this contributions needs to be in the release notes, please add it to CHANGELOG.md as well.
-If you want to participate in day-day conversations, please join our [slack group](https://hoodielib.slack.com/x-147852474016-157730502112/signup).
+If you want to participate in day-day conversations, please join our [slack group](https://join.slack.com/t/apache-hudi/signup).
If you are from select pre-listed email domains, you can self signup. Others, please subscribe to dev@hudi.apache.org
-## Becoming a Committer
+## Becoming a Committer
Hoodie has adopted a lot of guidelines set forth in [Google Chromium project](https://www.chromium.org/getting-involved/become-a-committer), to determine committership proposals. However, given this is a much younger project, we would have the contribution bar to be 10-15 non-trivial patches instead.
Additionally, we expect active engagement with the community over a few months, in terms of conference/meetup talks, helping out with issues/questions on slack/github.
diff --git a/docs/docker-compose.yml b/docs/docker-compose.yml
new file mode 100644
index 0000000..7c454e3
--- /dev/null
+++ b/docs/docker-compose.yml
@@ -0,0 +1,13 @@
+version: '3.3'
+services:
+ server:
+ build:
+ context: .
+ dockerfile: Dockerfile
+ image: hudi_docs/latest
+ ports:
+ - '4000:4000'
+ volumes:
+ - ".:/src"
+networks:
+ default:
diff --git a/docs/index.md b/docs/index.md
index 8fa056e..c198431 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -10,7 +10,7 @@ summary: "Hudi lowers data latency across the board, while simultaneously achiev
-Hudi (pronounced “Hoodie”) manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) and serve them out via two types of tables
+Hudi (pronounced “Hoodie”) manages storage of large analytical datasets on [HDFS](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) or cloud and serves them out via two types of tables
* **Read Optimized Table** - Provides excellent query performance via purely columnar storage (e.g. [Parquet](https://parquet.apache.org/))
* **Near-Real time Table** - Provides queries on real-time data, using a combination of columnar & row based storage (e.g Parquet + [Avro](http://avro.apache.org/docs/current/mr.html))
@@ -23,4 +23,3 @@ By carefully managing how data is laid out in storage & how it’s exposed to qu
Hudi broadly consists of a self contained Spark library to build datasets and integrations with existing query engines for data access.
{% include callout.html content="Hudi is a new project. Near Real-Time Table implementation is currently underway. Get involved [here](https://github.com/uber/hoodie/projects/1)" type="info" %}
-
[incubator-hudi-site] 05/19: Add delta streamer transformer option
to docs
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit d445077a576be96a5ba0924a3a122f0552b1586c
Author: vinoth chandar <vi...@users.noreply.github.com>
AuthorDate: Tue Feb 12 16:00:32 2019 -0800
Add delta streamer transformer option to docs
---
docs/incremental_processing.md | 7 ++++++-
1 file changed, 6 insertions(+), 1 deletion(-)
diff --git a/docs/incremental_processing.md b/docs/incremental_processing.md
index fb9839f..c2afad6 100644
--- a/docs/incremental_processing.md
+++ b/docs/incremental_processing.md
@@ -85,7 +85,12 @@ Usage: <main class> [options]
exist first time around. If exists, expected to be a Hudi dataset)
* --target-table
name of the target table in Hive
-
+ --transformer-class
+ subclass of com.uber.hoodie.utilities.transform.Transformer. UDF to
+ transform raw source dataset to a target dataset (conforming to target
+ schema) before writing. Default : Not set. E:g -
+ com.uber.hoodie.utilities.transform.SqlQueryBasedTransformer (which
+ allows a SQL query template to be passed as a transformation function)
```
[incubator-hudi-site] 18/19: Simplifying site navigation
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit aa361cc190f23805b5b4b6cd69a6a49e62c45b81
Author: Vinoth Chandar <vi...@uber.com>
AuthorDate: Sat Mar 9 23:02:18 2019 -0800
Simplifying site navigation
- Removed overview and migration guide from sidebar
- Migration guide linked off quickstart
- Moved detailed implementation notes to cwiki
- Merged performance, tuning into a new "performance" page
- Rename "incremental processing" to simply "writing data"
- Rename "SQL Queries" to simply "Querying data"
- Internal linking for Admin guide page
---
docs/_data/sidebars/mydoc_sidebar.yml | 35 ++-
docs/admin_guide.md | 18 +-
docs/configurations.md | 54 ----
docs/implementation.md | 278 ---------------------
docs/performance.md | 94 +++++++
docs/{sql_queries.md => querying_data.md} | 4 +-
docs/quickstart.md | 12 +-
.../{incremental_processing.md => writing_data.md} | 4 +-
8 files changed, 127 insertions(+), 372 deletions(-)
diff --git a/docs/_data/sidebars/mydoc_sidebar.yml b/docs/_data/sidebars/mydoc_sidebar.yml
index 118bd89..8cf59af 100644
--- a/docs/_data/sidebars/mydoc_sidebar.yml
+++ b/docs/_data/sidebars/mydoc_sidebar.yml
@@ -10,11 +10,6 @@ entries:
output: web
folderitems:
- - title: Overview
- url: /index.html
- output: web
- type: homepage
-
- title: Quickstart
url: /quickstart.html
output: web
@@ -27,6 +22,10 @@ entries:
url: /powered_by.html
output: web
+ - title: Comparison
+ url: /comparison.html
+ output: web
+
- title: Documentation
output: web
folderitems:
@@ -35,30 +34,24 @@ entries:
url: /concepts.html
output: web
- - title: Implementation
- url: /implementation.html
- output: web
-
- - title: Configurations
- url: /configurations.html
+ - title: Writing Data
+ url: /writing_data.html
output: web
- - title: SQL Queries
- url: /sql_queries.html
+ - title: Querying Data
+ url: /querying_data.html
output: web
- - title: Migration Guide
- url: /migration_guide.html
+ - title: Configuration
+ url: /configurations.html
output: web
- - title: Incremental Processing
- url: /incremental_processing.html
+ - title: Performance
+ url: /performance.html
output: web
- - title: Admin Guide
+ - title: Administering
url: /admin_guide.html
output: web
- - title: Comparison
- url: /comparison.html
- output: web
+
diff --git a/docs/admin_guide.md b/docs/admin_guide.md
index 58dbd15..3fbf1a2 100644
--- a/docs/admin_guide.md
+++ b/docs/admin_guide.md
@@ -1,5 +1,5 @@
---
-title: Admin Guide
+title: Administering Hudi Pipelines
keywords: hudi, administration, operation, devops
sidebar: mydoc_sidebar
permalink: admin_guide.html
@@ -9,13 +9,13 @@ summary: This section offers an overview of tools available to operate an ecosys
Admins/ops can gain visibility into Hudi datasets/pipelines in the following ways
- - Administering via the Admin CLI
- - Graphite metrics
- - Spark UI of the Hudi Application
+ - [Administering via the Admin CLI](#admin-cli)
+ - [Graphite metrics](#metrics)
+ - [Spark UI of the Hudi Application](#spark-ui)
-This section provides a glimpse into each of these, with some general guidance on troubleshooting
+This section provides a glimpse into each of these, with some general guidance on [troubleshooting](#troubleshooting)
-## Admin CLI
+## Admin CLI {#admin-cli}
Once hudi has been built, the shell can be fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
A hudi dataset resides on DFS, in a location referred to as the **basePath** and we would need this location in order to connect to a Hudi dataset.
@@ -385,7 +385,7 @@ Compaction successfully repaired
```
-## Metrics
+## Metrics {#metrics}
Once the Hudi Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hudi datasets
@@ -400,7 +400,7 @@ These metrics can then be plotted on a standard tool like grafana. Below is a sa
{% include image.html file="hudi_commit_duration.png" alt="hudi_commit_duration.png" max-width="1000" %}
-## Troubleshooting Failures
+## Troubleshooting Failures {#troubleshooting}
Section below generally aids in debugging Hudi failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)
@@ -425,7 +425,7 @@ First of all, please confirm if you do indeed have duplicates **AFTER** ensuring
- If duplicates span files across partitionpath, then this means your application is generating different partitionPaths for same recordKey, Please fix your app
- if duplicates span multiple files within the same partitionpath, please engage with mailing list. This should not happen. You can use the `records deduplicate` command to fix your data.
-#### Spark failures
+#### Spark failures {#spark-ui}
Typical upsert() DAG looks like below. Note that Hudi client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
Also Spark UI shows sortByKey twice due to the probe job also being shown, nonetheless its just a single sort.
diff --git a/docs/configurations.md b/docs/configurations.md
index dd2fa8a..d86d0ce 100644
--- a/docs/configurations.md
+++ b/docs/configurations.md
@@ -331,57 +331,3 @@ Controls memory usage for compaction and merges, performed internally by Hudi
<span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span>
-### Tuning
-
-Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
-
-**Input Parallelism** : By default, Hudi tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
-
-**Off-heap memory** : Hudi writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
-
-**Spark Memory** : Typically, hudi needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
-
-**Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
-
-**Timeseries/Log data** : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
- - Consider tuning the bloom filter accuracy via `.bloomFilterFPP()/bloomFilterNumEntries()` to achieve your target index look up time
- - Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.
-
-**GC Tuning** : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
-[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions :
-
-```
--XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
-````
-
-If it keeps OOMing still, reduce spark memory conservatively: `spark.memory.fraction=0.2, spark.memory.storageFraction=0.2` allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)
-
-Below is a full working production config
-
-```
- spark.driver.extraClassPath /etc/hive/conf
- spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
- spark.driver.maxResultSize 2g
- spark.driver.memory 4g
- spark.executor.cores 1
- spark.executor.extraJavaOptions -XX:+PrintFlagsFinal -XX:+PrintReferenceGC -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintAdaptiveSizePolicy -XX:+UnlockDiagnosticVMOptions -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
- spark.executor.id driver
- spark.executor.instances 300
- spark.executor.memory 6g
- spark.rdd.compress true
-
- spark.kryoserializer.buffer.max 512m
- spark.serializer org.apache.spark.serializer.KryoSerializer
- spark.shuffle.memoryFraction 0.2
- spark.shuffle.service.enabled true
- spark.sql.hive.convertMetastoreParquet false
- spark.storage.memoryFraction 0.6
- spark.submit.deployMode cluster
- spark.task.cpus 1
- spark.task.maxFailures 4
-
- spark.yarn.driver.memoryOverhead 1024
- spark.yarn.executor.memoryOverhead 3072
- spark.yarn.max.executor.failures 100
-
-````
diff --git a/docs/implementation.md b/docs/implementation.md
deleted file mode 100644
index 54966e2..0000000
--- a/docs/implementation.md
+++ /dev/null
@@ -1,278 +0,0 @@
----
-title: Implementation
-keywords: hudi, index, storage, compaction, cleaning, implementation
-sidebar: mydoc_sidebar
-toc: false
-permalink: implementation.html
----
-
-Hudi (pronounced “Hoodie”) is implemented as a Spark library, which makes it easy to integrate into existing data pipelines or ingestion
-libraries (which we will refer to as `Hudi clients`). Hudi Clients prepare an `RDD[HoodieRecord]` that contains the data to be upserted and
-Hudi upsert/insert is merely a Spark DAG, that can be broken into two big pieces.
-
- - **Indexing** : A big part of Hudi's efficiency comes from indexing the mapping from record keys to the file ids, to which they belong to.
- This index also helps the `HoodieWriteClient` separate upserted records into inserts and updates, so they can be treated differently.
- `HoodieReadClient` supports operations such as `filterExists` (used for de-duplication of table) and an efficient batch `read(keys)` api, that
- can read out the records corresponding to the keys using the index much quickly, than a typical scan via a query. The index is also atomically
- updated each commit, and is also rolled back when commits are rolled back.
-
- - **Storage** : The storage part of the DAG is responsible for taking an `RDD[HoodieRecord]`, that has been tagged as
- an insert or update via index lookup, and writing it out efficiently onto storage.
-
-## Index
-
-Hudi currently provides two choices for indexes : `BloomIndex` and `HBaseIndex` to map a record key into the file id to which it belongs to. This enables
-us to speed up upserts significantly, without scanning over every record in the dataset. Hudi Indices can be classified based on
-their ability to lookup records across partition. A `global` index does not need partition information for finding the file-id for a record key
-but a `non-global` does.
-
-#### HBase Index (global)
-
-Here, we just use HBase in a straightforward way to store the mapping above. The challenge with using HBase (or any external key-value store
- for that matter) is performing rollback of a commit and handling partial index updates.
- Since the HBase table is indexed by record key and not commit Time, we would have to scan all the entries which will be prohibitively expensive.
- Insteead, we store the commit time with the value and discard its value if it does not belong to a valid commit.
-
-#### Bloom Index (non-global)
-
-This index is built by adding bloom filters with a very high false positive tolerance (e.g: 1/10^9), to the parquet file footers.
-The advantage of this index over HBase is the obvious removal of a big external dependency, and also nicer handling of rollbacks & partial updates
-since the index is part of the data file itself.
-
-At runtime, checking the Bloom Index for a given set of record keys effectively amounts to checking all the bloom filters within a given
-partition, against the incoming records, using a Spark join. Much of the engineering effort towards the Bloom index has gone into scaling this join
-by caching the incoming RDD[HoodieRecord] and dynamically tuning join parallelism, to avoid hitting Spark limitations like 2GB maximum
-for partition size. As a result, Bloom Index implementation has been able to handle single upserts upto 5TB, in a reliable manner.
-
-
-## Storage
-
-The implementation specifics of the two storage types, introduced in [concepts](concepts.html) section, are detailed below.
-
-
-#### Copy On Write
-
-The Spark DAG for this storage, is relatively simpler. The key goal here is to group the tagged Hudi record RDD, into a series of
-updates and inserts, by using a partitioner. To achieve the goals of maintaining file sizes, we first sample the input to obtain a `workload profile`
-that understands the spread of inserts vs updates, their distribution among the partitions etc. With this information, we bin-pack the
-records such that
-
- - For updates, the latest version of the that file id, is rewritten once, with new values for all records that have changed
- - For inserts, the records are first packed onto the smallest file in each partition path, until it reaches the configured maximum size.
- Any remaining records after that, are again packed into new file id groups, again meeting the size requirements.
-
-In this storage, index updation is a no-op, since the bloom filters are already written as a part of committing data.
-
-In the case of Copy-On-Write, a single parquet file constitutes one `file slice` which contains one complete version of
-the file
-
-{% include image.html file="hudi_log_format_v2.png" alt="hudi_log_format_v2.png" max-width="1000" %}
-
-#### Merge On Read
-
-In the Merge-On-Read storage model, there are 2 logical components - one for ingesting data (both inserts/updates) into the dataset
- and another for creating compacted views. The former is hereby referred to as `Writer` while the later
- is referred as `Compactor`.
-
-##### Merge On Read Writer
-
- At a high level, Merge-On-Read Writer goes through same stages as Copy-On-Write writer in ingesting data.
- The key difference here is that updates are appended to latest log (delta) file belonging to the latest file slice
- without merging. For inserts, Hudi supports 2 modes:
-
- 1. Inserts to Log Files - This is done for datasets that have an indexable log files (for eg global index)
- 2. Inserts to parquet files - This is done for datasets that do not have indexable log files, for eg bloom index
- embedded in parquer files. Hudi treats writing new records in the same way as inserting to Copy-On-Write files.
-
-As in the case of Copy-On-Write, the input tagged records are partitioned such that all upserts destined to
-a `file id` are grouped together. This upsert-batch is written as one or more log-blocks written to log-files.
-Hudi allows clients to control log file sizes (See [Storage Configs](../configurations))
-
-The WriteClient API is same for both Copy-On-Write and Merge-On-Read writers.
-
-With Merge-On-Read, several rounds of data-writes would have resulted in accumulation of one or more log-files.
-All these log-files along with base-parquet (if exists) constitute a `file slice` which represents one complete version
-of the file.
-
-#### Compactor
-
-Realtime Readers will perform in-situ merge of these delta log-files to provide the most recent (committed) view of
-the dataset. To keep the query-performance in check and eventually achieve read-optimized performance, Hudi supports
-compacting these log-files asynchronously to create read-optimized views.
-
-Asynchronous Compaction involves 2 steps:
-
- * `Compaction Schedule` : Hudi Write Client exposes API to create Compaction plans which contains the list of `file slice`
- to be compacted atomically in a single compaction commit. Hudi allows pluggable strategies for choosing
- file slices for each compaction runs. This step is typically done inline by Writer process as Hudi expects
- only one schedule is being generated at a time which allows Hudi to enforce the constraint that pending compaction
- plans do not step on each other file-slices. This constraint allows for multiple concurrent `Compactors` to run at
- the same time. Some of the common strategies used for choosing `file slice` for compaction are:
- * BoundedIO - Limit the number of file slices chosen for a compaction plan by expected total IO (read + write)
- needed to complete compaction run
- * Log File Size - Prefer file-slices with larger amounts of delta log data to be merged
- * Day Based - Prefer file slice belonging to latest day partitions
-
- * `Compactor` : Hudi provides a separate API in Write Client to execute a compaction plan. The compaction
- plan (just like a commit) is identified by a timestamp. Most of the design and implementation complexities for Async
- Compaction is for guaranteeing snapshot isolation to readers and writer when
- multiple concurrent compactors are running. Typical compactor deployment involves launching a separate
- spark application which executes pending compactions when they become available. The core logic of compacting
- file slices in the Compactor is very similar to that of merging updates in a Copy-On-Write table. The only
- difference being in the case of compaction, there is an additional step of merging the records in delta log-files.
-
-Here are the main API to lookup and execute a compaction plan.
-
-```
- Main API in HoodieWriteClient for running Compaction:
- /**
- * Performs Compaction corresponding to instant-time
- * @param compactionInstantTime Compaction Instant Time
- * @return
- * @throws IOException
- */
- public JavaRDD<WriteStatus> compact(String compactionInstantTime) throws IOException;
-
- To lookup all pending compactions, use the API defined in HoodieReadClient
-
- /**
- * Return all pending compactions with instant time for clients to decide what to compact next.
- * @return
- */
- public List<Pair<String, HoodieCompactionPlan>> getPendingCompactions();
-```
-API for scheduling compaction
-
-```
-
- /**
- * Schedules a new compaction instant
- * @param extraMetadata
- * @return Compaction Instant timestamp if a new compaction plan is scheduled
- */
- Optional<String> scheduleCompaction(Optional<Map<String, String>> extraMetadata) throws IOException;
-```
-
-Refer to __hoodie-client/src/test/java/HoodieClientExample.java__ class for an example of how compaction
-is scheduled and executed.
-
-##### Deployment Models
-
-These are typical Hudi Writer and Compaction deployment models
-
- * `Inline Compaction` : At each round, a single spark application ingests new batch to dataset. It then optionally decides to schedule
- a compaction run and executes it in sequence.
- * `Single Dedicated Async Compactor` : The Spark application which brings in new changes to dataset (writer) periodically
- schedules compaction. The Writer application does not run compaction inline. A separate spark applications periodically
- probes for pending compaction and executes the compaction.
- * ` Multi Async Compactors` : This mode is similar to `Single Dedicated Async Compactor` mode. The main difference being
- now there can be more than one spark application picking different compactions and executing them in parallel.
- In order to ensure compactors do not step on each other, they use coordination service like zookeeper to pickup unique
- pending compaction instants and run them.
-
-The Compaction process requires one executor per file-slice in the compaction plan. So, the best resource allocation
-strategy (both in terms of speed and resource usage) for clusters supporting dynamic allocation is to lookup the compaction
-plan to be run to figure out the number of file slices being compacted and choose that many number of executors.
-
-## Async Compaction Design Deep-Dive (Optional)
-
-For the purpose of this section, it is important to distinguish between 2 types of commits as pertaining to the file-group:
-
-A commit which generates a merged and read-optimized file-slice is called `snapshot commit` (SC) with respect to that file-group.
-A commit which merely appended the new/updated records assigned to the file-group into a new log block is called `delta commit` (DC)
-with respect to that file-group.
-
-### Algorithm
-
-The algorithm is described with an illustration. Let us assume a scenario where there are commits SC1, DC2, DC3 that have
-already completed on a data-set. Commit DC4 is currently ongoing with the writer (ingestion) process using it to upsert data.
-Let us also imagine there are a set of file-groups (FG1 … FGn) in the data-set whose latest version (`File-Slice`)
-contains the base file created by commit SC1 (snapshot-commit in columnar format) and a log file containing row-based
-log blocks of 2 delta-commits (DC2 and DC3).
-
-{% include image.html file="async_compac_1.png" alt="async_compac_1.png" max-width="1000" %}
-
- * Writer (Ingestion) that is going to commit "DC4" starts. The record updates in this batch are grouped by file-groups
- and appended in row formats to the corresponding log file as delta commit. Let us imagine a subset of file-groups has
- this new log block (delta commit) DC4 added.
- * Before the writer job completes, it runs the compaction strategy to decide which file-group to compact by compactor
- and creates a new compaction-request commit SC5. This commit file is marked as “requested” with metadata denoting
- which fileIds to compact (based on selection policy). Writer completes without running compaction (will be run async).
-
- {% include image.html file="async_compac_2.png" alt="async_compac_2.png" max-width="1000" %}
-
- * Writer job runs again ingesting next batch. It starts with commit DC6. It reads the earliest inflight compaction
- request marker commit in timeline order and collects the (fileId, Compaction Commit Id “CcId” ) pairs from meta-data.
- Ingestion DC6 ensures a new file-slice with base-commit “CcId” gets allocated for the file-group.
- The Writer will simply append records in row-format to the first log-file (as delta-commit) assuming the
- base-file (“Phantom-Base-File”) will be created eventually by the compactor.
-
- {% include image.html file="async_compac_3.png" alt="async_compac_3.png" max-width="1000" %}
-
- * Compactor runs at some time and commits at “Tc” (concurrently or before/after Ingestion DC6). It reads the commit-timeline
- and finds the first unprocessed compaction request marker commit. Compactor reads the commit’s metadata finding the
- file-slices to be compacted. It compacts the file-slice and creates the missing base-file (“Phantom-Base-File”)
- with “CCId” as the commit-timestamp. Compactor then marks the compaction commit timestamp as completed.
- It is important to realize that at data-set level, there could be different file-groups requesting compaction at
- different commit timestamps.
-
- {% include image.html file="async_compac_4.png" alt="async_compac_4.png" max-width="1000" %}
-
- * Near Real-time reader interested in getting the latest snapshot will have 2 cases. Let us assume that the
- incremental ingestion (writer at DC6) happened before the compaction (some time “Tc”’).
- The below description is with regards to compaction from file-group perspective.
- * `Reader querying at time between ingestion completion time for DC6 and compaction finish “Tc”`:
- Hudi’s implementation will be changed to become aware of file-groups currently waiting for compaction and
- merge log-files corresponding to DC2-DC6 with the base-file corresponding to SC1. In essence, Hudi will create
- a pseudo file-slice by combining the 2 file-slices starting at base-commits SC1 and SC5 to one.
- For file-groups not waiting for compaction, the reader behavior is essentially the same - read latest file-slice
- and merge on the fly.
- * `Reader querying at time after compaction finished (> “Tc”)` : In this case, reader will not find any pending
- compactions in the timeline and will simply have the current behavior of reading the latest file-slice and
- merging on-the-fly.
-
- * Read-Optimized View readers will query against the latest columnar base-file for each file-groups.
-
-The above algorithm explains Async compaction w.r.t a single compaction run on a single file-group. It is important
-to note that multiple compaction plans can be run concurrently as they are essentially operating on different
-file-groups.
-
-## Performance
-
-In this section, we go over some real world performance numbers for Hudi upserts, incremental pull and compare them against
-the conventional alternatives for achieving these tasks.
-
-#### Upsert vs Bulk Loading
-
-Following shows the speed up obtained for NoSQL ingestion, by switching from bulk loads off HBase to Parquet to incrementally upserting
-on a Hudi dataset, on 5 tables ranging from small to huge.
-
-{% include image.html file="hudi_upsert_perf1.png" alt="hudi_upsert_perf1.png" max-width="1000" %}
-
-
-Given Hudi can build the dataset incrementally, it opens doors for also scheduling ingesting more frequently thus reducing latency, with
-significant savings on the overall compute cost.
-
-
-{% include image.html file="hudi_upsert_perf2.png" alt="hudi_upsert_perf2.png" max-width="1000" %}
-
-Hudi upserts have been stress tested upto 4TB in a single commit across the t1 table.
-
-
-
-#### Copy On Write Regular Query Performance
-
-The major design goal for copy-on-write storage was to achieve the latency reduction & efficiency gains in previous section,
-with no impact on queries. Following charts compare the Hudi vs non-Hudi datasets across Hive/Presto/Spark queries.
-
-**Hive**
-
-{% include image.html file="hudi_query_perf_hive.png" alt="hudi_query_perf_hive.png" max-width="800" %}
-
-**Spark**
-
-{% include image.html file="hudi_query_perf_spark.png" alt="hudi_query_perf_spark.png" max-width="1000" %}
-
-**Presto**
-
-{% include image.html file="hudi_query_perf_presto.png" alt="hudi_query_perf_presto.png" max-width="1000" %}
diff --git a/docs/performance.md b/docs/performance.md
new file mode 100644
index 0000000..6795171
--- /dev/null
+++ b/docs/performance.md
@@ -0,0 +1,94 @@
+---
+title: Implementation
+keywords: hudi, index, storage, compaction, cleaning, implementation
+sidebar: mydoc_sidebar
+toc: false
+permalink: performance.html
+---
+## Performance
+
+In this section, we go over some real world performance numbers for Hudi upserts, incremental pull and compare them against
+the conventional alternatives for achieving these tasks. Following shows the speed up obtained for NoSQL ingestion,
+by switching from bulk loads off HBase to Parquet to incrementally upserting on a Hudi dataset, on 5 tables ranging from small to huge.
+
+{% include image.html file="hudi_upsert_perf1.png" alt="hudi_upsert_perf1.png" max-width="1000" %}
+
+Given Hudi can build the dataset incrementally, it opens doors for also scheduling ingesting more frequently thus reducing latency, with
+significant savings on the overall compute cost.
+
+{% include image.html file="hudi_upsert_perf2.png" alt="hudi_upsert_perf2.png" max-width="1000" %}
+
+Hudi upserts have been stress tested upto 4TB in a single commit across the t1 table.
+
+### Tuning
+
+Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
+
+**Input Parallelism** : By default, Hudi tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
+
+**Off-heap memory** : Hudi writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
+
+**Spark Memory** : Typically, hudi needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
+
+**Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
+
+**Timeseries/Log data** : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
+ - Consider tuning the bloom filter accuracy via `.bloomFilterFPP()/bloomFilterNumEntries()` to achieve your target index look up time
+ - Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.
+
+**GC Tuning** : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
+[Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions :
+
+```
+-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+````
+
+If it keeps OOMing still, reduce spark memory conservatively: `spark.memory.fraction=0.2, spark.memory.storageFraction=0.2` allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)
+
+Below is a full working production config
+
+```
+ spark.driver.extraClassPath /etc/hive/conf
+ spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.driver.maxResultSize 2g
+ spark.driver.memory 4g
+ spark.executor.cores 1
+ spark.executor.extraJavaOptions -XX:+PrintFlagsFinal -XX:+PrintReferenceGC -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintAdaptiveSizePolicy -XX:+UnlockDiagnosticVMOptions -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.executor.id driver
+ spark.executor.instances 300
+ spark.executor.memory 6g
+ spark.rdd.compress true
+
+ spark.kryoserializer.buffer.max 512m
+ spark.serializer org.apache.spark.serializer.KryoSerializer
+ spark.shuffle.memoryFraction 0.2
+ spark.shuffle.service.enabled true
+ spark.sql.hive.convertMetastoreParquet false
+ spark.storage.memoryFraction 0.6
+ spark.submit.deployMode cluster
+ spark.task.cpus 1
+ spark.task.maxFailures 4
+
+ spark.yarn.driver.memoryOverhead 1024
+ spark.yarn.executor.memoryOverhead 3072
+ spark.yarn.max.executor.failures 100
+
+````
+
+
+#### Read Optimized Query Performance
+
+The major design goal for read optimized view is to achieve the latency reduction & efficiency gains in previous section,
+with no impact on queries. Following charts compare the Hudi vs non-Hudi datasets across Hive/Presto/Spark queries and demonstrate this.
+
+**Hive**
+
+{% include image.html file="hudi_query_perf_hive.png" alt="hudi_query_perf_hive.png" max-width="800" %}
+
+**Spark**
+
+{% include image.html file="hudi_query_perf_spark.png" alt="hudi_query_perf_spark.png" max-width="1000" %}
+
+**Presto**
+
+{% include image.html file="hudi_query_perf_presto.png" alt="hudi_query_perf_presto.png" max-width="1000" %}
diff --git a/docs/sql_queries.md b/docs/querying_data.md
similarity index 98%
rename from docs/sql_queries.md
rename to docs/querying_data.md
index 4dc7493..452c92d 100644
--- a/docs/sql_queries.md
+++ b/docs/querying_data.md
@@ -1,8 +1,8 @@
---
-title: SQL Queries
+title: Querying Hudi Datasets
keywords: hudi, hive, spark, sql, presto
sidebar: mydoc_sidebar
-permalink: sql_queries.html
+permalink: querying_data.html
toc: false
summary: In this page, we go over how to enable SQL queries on Hudi built tables.
---
diff --git a/docs/quickstart.md b/docs/quickstart.md
index e19bedf..ff33184 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -8,11 +8,10 @@ permalink: quickstart.html
---
-## Download Hudi
-Check out code and pull it into Intellij as a normal maven project.
+## Download Hudi
-Normally build the maven project, from command line
+Check out code and pull it into Intellij as a normal maven project. Normally build the maven project, from command line
```
$ mvn clean install -DskipTests -DskipITs
@@ -23,10 +22,11 @@ To work with older version of Hive (pre Hive-1.2.1), use
$ mvn clean install -DskipTests -DskipITs -Dhive11
```
-{% include callout.html content="You might want to add your spark jars folder to project dependencies under 'Module Setttings', to be able to run Spark from IDE" type="info" %}
-
-{% include note.html content="Setup your local hadoop/hive test environment, so you can play with entire ecosystem. See [this](http://www.bytearray.io/2016/05/setting-up-hadoopyarnsparkhive-on-mac.html) for reference" %}
+{% include callout.html content="You might want to add your spark jars folder to project dependencies under 'Module Setttings', to be able to run Spark from IDE.
+Setup your local hadoop/hive test environment, so you can play with entire ecosystem.
+See [this](http://www.bytearray.io/2016/05/setting-up-hadoopyarnsparkhive-on-mac.html) for reference" type="info" %}
+<br/>Please refer to [migration guide](migration_guide.html), for recommended ways to migrate your existing dataset to Hudi.
## Version Compatibility
diff --git a/docs/incremental_processing.md b/docs/writing_data.md
similarity index 99%
rename from docs/incremental_processing.md
rename to docs/writing_data.md
index 63f4f39..28fd03e 100644
--- a/docs/incremental_processing.md
+++ b/docs/writing_data.md
@@ -1,8 +1,8 @@
---
-title: Incremental Processing
+title: Writing Hudi Datasets
keywords: hudi, incremental, batch, stream, processing, Hive, ETL, Spark SQL
sidebar: mydoc_sidebar
-permalink: incremental_processing.html
+permalink: writing_data.html
toc: false
summary: In this page, we will discuss some available tools for ingesting data incrementally & consuming the changes.
---
[incubator-hudi-site] 02/19: Initial commit with documentation.
Replacing some occurrences of Hoodie with Hudi
Posted by vi...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
vinoth pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/incubator-hudi-site.git
commit 3799e69eb92a905d37d122b28ac773286c72ea77
Author: Nishith Agarwal <na...@uber.com>
AuthorDate: Sun Feb 3 22:39:12 2019 -0800
Initial commit with documentation. Replacing some occurrences of Hoodie with Hudi
---
docs/.gitignore | 4 +
docs/404.md | 6 +
docs/Dockerfile | 26 +
docs/Gemfile | 10 +
docs/Gemfile.lock | 156 +
docs/_config.yml | 84 +
docs/_data/alerts.yml | 15 +
docs/_data/sidebars/mydoc_sidebar.yml | 66 +
docs/_data/strings.yml | 5 +
docs/_data/tags.yml | 10 +
docs/_data/topnav.yml | 30 +
docs/_includes/archive.html | 15 +
docs/_includes/callout.html | 1 +
docs/_includes/custom/getting_started_series.html | 19 +
.../custom/getting_started_series_next.html | 10 +
docs/_includes/custom/series_acme.html | 19 +
docs/_includes/custom/series_acme_next.html | 30 +
docs/_includes/custom/sidebarconfigs.html | 19 +
docs/_includes/custom/usermap.html | 14 +
docs/_includes/custom/usermapcomplex.html | 91 +
docs/_includes/disqus.html | 16 +
docs/_includes/feedback.html | 13 +
docs/_includes/footer.html | 9 +
docs/_includes/google_analytics.html | 6 +
docs/_includes/head.html | 47 +
docs/_includes/head_print.html | 33 +
docs/_includes/image.html | 1 +
docs/_includes/important.html | 1 +
docs/_includes/initialize_shuffle.html | 130 +
docs/_includes/inline_image.html | 1 +
docs/_includes/links.html | 44 +
docs/_includes/note.html | 1 +
docs/_includes/sidebar.html | 56 +
docs/_includes/taglogic.html | 32 +
docs/_includes/tip.html | 1 +
docs/_includes/toc.html | 21 +
docs/_includes/topnav.html | 75 +
docs/_includes/warning.html | 1 +
docs/_layouts/default.html | 80 +
docs/_layouts/default_print.html | 25 +
docs/_layouts/none.html | 3 +
docs/_layouts/page.html | 70 +
docs/_layouts/page_print.html | 15 +
docs/_layouts/post.html | 41 +
docs/_posts/2016-12-30-strata-talk-2017.md | 11 +
docs/admin_guide.md | 444 ++
docs/api_docs.md | 10 +
docs/code_and_design.md | 38 +
docs/community.md | 22 +
docs/comparison.md | 61 +
docs/concepts.md | 159 +
docs/configurations.md | 203 +
docs/css/bootstrap.min.css | 5 +
docs/css/customstyles.css | 1181 ++++
docs/css/font-awesome.min.css | 4 +
docs/css/fonts/FontAwesome.otf | Bin 0 -> 93888 bytes
docs/css/fonts/fontawesome-webfont.eot | Bin 0 -> 60767 bytes
docs/css/fonts/fontawesome-webfont.svg | 565 ++
docs/css/fonts/fontawesome-webfont.ttf | Bin 0 -> 122092 bytes
docs/css/fonts/fontawesome-webfont.woff | Bin 0 -> 71508 bytes
docs/css/fonts/fontawesome-webfont.woff2 | Bin 0 -> 56780 bytes
docs/css/lavish-bootstrap.css | 5898 ++++++++++++++++++++
docs/css/modern-business.css | 93 +
docs/css/printstyles.css | 160 +
docs/css/syntax.css | 60 +
docs/css/theme-blue.css | 103 +
docs/css/theme-green.css | 99 +
docs/dev_setup.md | 13 +
docs/feed.xml | 32 +
docs/fonts/FontAwesome.otf | Bin 0 -> 85908 bytes
docs/fonts/fontawesome-webfont.eot | Bin 0 -> 56006 bytes
docs/fonts/fontawesome-webfont.svg | 520 ++
docs/fonts/fontawesome-webfont.ttf | Bin 0 -> 112160 bytes
docs/fonts/fontawesome-webfont.woff | Bin 0 -> 65452 bytes
docs/fonts/glyphicons-halflings-regular.eot | Bin 0 -> 20127 bytes
docs/fonts/glyphicons-halflings-regular.svg | 288 +
docs/fonts/glyphicons-halflings-regular.ttf | Bin 0 -> 45404 bytes
docs/fonts/glyphicons-halflings-regular.woff | Bin 0 -> 23424 bytes
docs/fonts/glyphicons-halflings-regular.woff2 | Bin 0 -> 18028 bytes
docs/gcs_filesystem.md | 62 +
docs/images/androidsdkmanagericon.png | Bin 0 -> 795 bytes
docs/images/async_compac_1.png | Bin 0 -> 60344 bytes
docs/images/async_compac_2.png | Bin 0 -> 54164 bytes
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docs/images/authorizegithubscreen2.png | Bin 0 -> 76388 bytes
docs/images/authorizeongithub.png | Bin 0 -> 22571 bytes
docs/images/company_logo.png | Bin 0 -> 3105 bytes
docs/images/company_logo_big.png | Bin 0 -> 9588 bytes
docs/images/favicon.ico | Bin 0 -> 1150 bytes
docs/images/helpapi-01.png | Bin 0 -> 91640 bytes
docs/images/helpapi.svg | 1661 ++++++
docs/images/hoodie_commit_duration.png | Bin 0 -> 869144 bytes
docs/images/hoodie_cow.png | Bin 0 -> 31136 bytes
docs/images/hoodie_intro_1.png | Bin 0 -> 23478 bytes
docs/images/hoodie_log_format_v2.png | Bin 0 -> 223676 bytes
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docs/images/hoodie_query_perf_presto.png | Bin 0 -> 33727 bytes
docs/images/hoodie_query_perf_spark.png | Bin 0 -> 29384 bytes
docs/images/hoodie_timeline.png | Bin 0 -> 23093 bytes
docs/images/hoodie_upsert_dag.png | Bin 0 -> 503771 bytes
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docs/images/hoodie_upsert_perf2.png | Bin 0 -> 18954 bytes
docs/images/illustratoroptions.png | Bin 0 -> 118175 bytes
docs/images/itermexample.png | Bin 0 -> 68886 bytes
docs/images/jekyll.png | Bin 0 -> 5375 bytes
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docs/implementation.md | 275 +
docs/incremental_processing.md | 233 +
docs/index.md | 26 +
docs/js/customscripts.js | 55 +
docs/js/jekyll-search.js | 1 +
docs/js/jquery.ba-throttle-debounce.min.js | 9 +
docs/js/jquery.localScroll.min.js | 7 +
docs/js/jquery.navgoco.min.js | 8 +
docs/js/jquery.scrollTo.min.js | 7 +
docs/js/jquery.shuffle.min.js | 1588 ++++++
docs/js/mydoc_scroll.html | 240 +
docs/js/toc.js | 82 +
docs/licenses/LICENSE | 21 +
docs/licenses/LICENSE-BSD-NAVGOCO.txt | 27 +
docs/migration_guide.md | 71 +
docs/pages/news/news.html | 32 +
docs/pages/news/news_archive.html | 41 +
docs/powered_by.md | 40 +
docs/quickstart.md | 1247 +++++
docs/roadmap.md | 14 +
docs/s3_filesystem.md | 79 +
docs/search.json | 33 +
docs/sitemap.xml | 24 +
docs/sql_queries.md | 68 +
docs/use_cases.md | 77 +
135 files changed, 17349 insertions(+)
diff --git a/docs/.gitignore b/docs/.gitignore
new file mode 100644
index 0000000..f380cae
--- /dev/null
+++ b/docs/.gitignore
@@ -0,0 +1,4 @@
+_site
+.sass-cache
+.jekyll-metadata
+.ruby-version
diff --git a/docs/404.md b/docs/404.md
new file mode 100644
index 0000000..a7b58c0
--- /dev/null
+++ b/docs/404.md
@@ -0,0 +1,6 @@
+---
+title: "Page Not Found"
+search: exclude
+---
+
+Sorry, but the page you were trying to view does not exist. Try searching for it or looking at the URL to see if it looks correct.
diff --git a/docs/Dockerfile b/docs/Dockerfile
new file mode 100644
index 0000000..b1fa52c
--- /dev/null
+++ b/docs/Dockerfile
@@ -0,0 +1,26 @@
+FROM ruby:2.1
+MAINTAINER mrafayaleem@gmail.com
+
+RUN apt-get clean \
+ && mv /var/lib/apt/lists /var/lib/apt/lists.broke \
+ && mkdir -p /var/lib/apt/lists/partial
+
+RUN apt-get update
+
+RUN apt-get install -y \
+ node \
+ python-pygments \
+ && apt-get clean \
+ && rm -rf /var/lib/apt/lists/
+
+WORKDIR /tmp
+ADD Gemfile /tmp/
+ADD Gemfile.lock /tmp/
+RUN bundle install
+
+VOLUME /src
+EXPOSE 4000
+
+WORKDIR /src
+ENTRYPOINT ["jekyll"]
+
diff --git a/docs/Gemfile b/docs/Gemfile
new file mode 100644
index 0000000..b301eda
--- /dev/null
+++ b/docs/Gemfile
@@ -0,0 +1,10 @@
+source "https://rubygems.org"
+
+
+gem "jekyll", "3.3.1"
+
+
+group :jekyll_plugins do
+ gem "jekyll-feed", "~> 0.6"
+ gem 'github-pages', '~> 106'
+end
diff --git a/docs/Gemfile.lock b/docs/Gemfile.lock
new file mode 100644
index 0000000..65eae02
--- /dev/null
+++ b/docs/Gemfile.lock
@@ -0,0 +1,156 @@
+GEM
+ remote: https://rubygems.org/
+ specs:
+ activesupport (4.2.7)
+ i18n (~> 0.7)
+ json (~> 1.7, >= 1.7.7)
+ minitest (~> 5.1)
+ thread_safe (~> 0.3, >= 0.3.4)
+ tzinfo (~> 1.1)
+ addressable (2.4.0)
+ coffee-script (2.4.1)
+ coffee-script-source
+ execjs
+ coffee-script-source (1.12.2)
+ colorator (1.1.0)
+ concurrent-ruby (1.0.5)
+ ethon (0.11.0)
+ ffi (>= 1.3.0)
+ execjs (2.7.0)
+ faraday (0.13.1)
+ multipart-post (>= 1.2, < 3)
+ ffi (1.9.24)
+ forwardable-extended (2.6.0)
+ gemoji (2.1.0)
+ github-pages (106)
+ activesupport (= 4.2.7)
+ github-pages-health-check (= 1.2.0)
+ jekyll (= 3.6.3)
+ jekyll-avatar (= 0.4.2)
+ jekyll-coffeescript (= 1.0.1)
+ jekyll-feed (= 0.8.0)
+ jekyll-gist (= 1.4.0)
+ jekyll-github-metadata (= 2.2.0)
+ jekyll-mentions (= 1.2.0)
+ jekyll-paginate (= 1.1.0)
+ jekyll-redirect-from (= 0.11.0)
+ jekyll-relative-links (= 0.2.1)
+ jekyll-sass-converter (= 1.3.0)
+ jekyll-seo-tag (= 2.1.0)
+ jekyll-sitemap (= 0.12.0)
+ jekyll-swiss (= 0.4.0)
+ jemoji (= 0.7.0)
+ kramdown (= 1.11.1)
+ liquid (= 3.0.6)
+ listen (= 3.0.6)
+ mercenary (~> 0.3)
+ minima (= 2.0.0)
+ rouge (= 1.11.1)
+ terminal-table (~> 1.4)
+ github-pages-health-check (1.2.0)
+ addressable (~> 2.3)
+ net-dns (~> 0.8)
+ octokit (~> 4.0)
+ public_suffix (~> 1.4)
+ typhoeus (~> 0.7)
+ html-pipeline (2.7.1)
+ activesupport (>= 2)
+ nokogiri (>= 1.4)
+ i18n (0.9.1)
+ concurrent-ruby (~> 1.0)
+ jekyll (3.6.3)
+ addressable (~> 2.4)
+ colorator (~> 1.0)
+ jekyll-sass-converter (~> 1.0)
+ jekyll-watch (~> 1.1)
+ kramdown (~> 1.3)
+ liquid (~> 3.0)
+ mercenary (~> 0.3.3)
+ pathutil (~> 0.9)
+ rouge (~> 1.7)
+ safe_yaml (~> 1.0)
+ jekyll-avatar (0.4.2)
+ jekyll (~> 3.0)
+ jekyll-coffeescript (1.0.1)
+ coffee-script (~> 2.2)
+ jekyll-feed (0.8.0)
+ jekyll (~> 3.3)
+ jekyll-gist (1.4.0)
+ octokit (~> 4.2)
+ jekyll-github-metadata (2.2.0)
+ jekyll (~> 3.1)
+ octokit (~> 4.0, != 4.4.0)
+ jekyll-mentions (1.2.0)
+ activesupport (~> 4.0)
+ html-pipeline (~> 2.3)
+ jekyll (~> 3.0)
+ jekyll-paginate (1.1.0)
+ jekyll-redirect-from (0.11.0)
+ jekyll (>= 2.0)
+ jekyll-relative-links (0.2.1)
+ jekyll (~> 3.3)
+ jekyll-sass-converter (1.3.0)
+ sass (~> 3.2)
+ jekyll-seo-tag (2.1.0)
+ jekyll (~> 3.3)
+ jekyll-sitemap (0.12.0)
+ jekyll (~> 3.3)
+ jekyll-swiss (0.4.0)
+ jekyll-watch (1.5.1)
+ listen (~> 3.0)
+ jemoji (0.7.0)
+ activesupport (~> 4.0)
+ gemoji (~> 2.0)
+ html-pipeline (~> 2.2)
+ jekyll (>= 3.0)
+ json (1.8.6)
+ kramdown (1.11.1)
+ liquid (3.0.6)
+ listen (3.0.6)
+ rb-fsevent (>= 0.9.3)
+ rb-inotify (>= 0.9.7)
+ mercenary (0.3.6)
+ mini_portile2 (2.3.0)
+ minima (2.0.0)
+ minitest (5.11.1)
+ multipart-post (2.0.0)
+ net-dns (0.8.0)
+ nokogiri (1.8.2)
+ mini_portile2 (~> 2.3.0)
+ octokit (4.8.0)
+ sawyer (~> 0.8.0, >= 0.5.3)
+ pathutil (0.16.1)
+ forwardable-extended (~> 2.6)
+ public_suffix (1.5.3)
+ rb-fsevent (0.10.2)
+ rb-inotify (0.9.10)
+ ffi (>= 0.5.0, < 2)
+ rouge (1.11.1)
+ safe_yaml (1.0.4)
+ sass (3.5.5)
+ sass-listen (~> 4.0.0)
+ sass-listen (4.0.0)
+ rb-fsevent (~> 0.9, >= 0.9.4)
+ rb-inotify (~> 0.9, >= 0.9.7)
+ sawyer (0.8.1)
+ addressable (>= 2.3.5, < 2.6)
+ faraday (~> 0.8, < 1.0)
+ terminal-table (1.8.0)
+ unicode-display_width (~> 1.1, >= 1.1.1)
+ thread_safe (0.3.6)
+ typhoeus (0.8.0)
+ ethon (>= 0.8.0)
+ tzinfo (1.2.4)
+ thread_safe (~> 0.1)
+ unicode-display_width (1.3.0)
+
+PLATFORMS
+ ruby
+
+DEPENDENCIES
+ github-pages (~> 106)
+ jekyll (= 3.6.3)
+ jekyll-feed (~> 0.6)
+
+BUNDLED WITH
+ 1.14.3
diff --git a/docs/_config.yml b/docs/_config.yml
new file mode 100644
index 0000000..781bdb6
--- /dev/null
+++ b/docs/_config.yml
@@ -0,0 +1,84 @@
+
+output: web
+# this property is useful for conditional filtering of content that is separate from the PDF.
+
+topnav_title: Hudi
+# this appears on the top navigation bar next to the home button
+
+site_title: Hudi
+# this appears in the html browser tab for the site title (seen mostly by search engines, not users)
+
+github_editme_path:
+# if you're using Github, provide the basepath to the branch you've created for reviews, following the sample here. if not, leave this value blank.
+
+disqus_shortname:
+# if you're using disqus for comments, add the shortname here. if not, leave this value blank.
+
+host: 127.0.0.1
+# the preview server used. Leave as is.
+
+port: 4000
+# the port where the preview is rendered. You can leave this as is unless you have other Jekyll builds using this same port that might cause conflicts. in that case, use another port such as 4006.
+
+exclude:
+ - .idea/
+ - .gitignore
+# these are the files and directories that jekyll will exclude from the build
+
+feedback_subject_line: Hudi Documentation
+
+feedback_email: dev@hudi.apache.org
+# used as a contact email for the Feedback link in the top navigation bar
+
+# feedback_disable: true
+# if you uncomment the previous line, the Feedback link gets removed
+
+# feedback_text: "Need help?"
+# if you uncomment the previous line, it changes the Feedback text
+
+# feedback_link: "http://helpy.io/"
+# if you uncomment the previous line, it changes where the feedback link points to
+
+highlighter: rouge
+# library used for syntax highlighting
+
+markdown: kramdown
+kramdown:
+ input: GFM
+ auto_ids: true
+ hard_wrap: false
+ syntax_highlighter: rouge
+
+# filter used to process markdown. note that kramdown differs from github-flavored markdown in some subtle ways
+
+defaults:
+ -
+ scope:
+ path: ""
+ type: "pages"
+ values:
+ layout: "page"
+ comments: true
+ search: true
+ sidebar: mydoc_sidebar
+
+ -
+ scope:
+ path: ""
+ type: "posts"
+ values:
+ layout: "post"
+ comments: true
+ search: true
+ sidebar: mydoc_sidebar
+
+# these are defaults used for the frontmatter for these file types
+
+sidebars:
+- mydoc_sidebar
+
+description: "Apache Hudi (pronounced “Hoodie”) is a Spark Library, that provides upserts and incremental processing capaibilities on Hadoop datasets"
+# the description is used in the feed.xml file
+
+# needed for sitemap.xml file only
+url: https://github.com/apache/incubator-hudi
diff --git a/docs/_data/alerts.yml b/docs/_data/alerts.yml
new file mode 100644
index 0000000..157e162
--- /dev/null
+++ b/docs/_data/alerts.yml
@@ -0,0 +1,15 @@
+tip: '<div class="alert alert-success" role="alert"><i class="fa fa-check-square-o"></i> <b>Tip: </b>'
+note: '<div class="alert alert-info" role="alert"><i class="fa fa-info-circle"></i> <b>Note: </b>'
+important: '<div class="alert alert-warning" role="alert"><i class="fa fa-warning"></i> <b>Important: </b>'
+warning: '<div class="alert alert-danger" role="alert"><i class="fa fa-exclamation-circle"></i> <b>Warning: </b>'
+end: '</div>'
+
+callout_danger: '<div class="bs-callout bs-callout-danger">'
+callout_default: '<div class="bs-callout bs-callout-default">'
+callout_primary: '<div class="bs-callout bs-callout-primary">'
+callout_success: '<div class="bs-callout bs-callout-success">'
+callout_info: '<div class="bs-callout bs-callout-info">'
+callout_warning: '<div class="bs-callout bs-callout-warning">'
+
+hr_faded: '<hr class="faded"/>'
+hr_shaded: '<hr class="shaded"/>'
\ No newline at end of file
diff --git a/docs/_data/sidebars/mydoc_sidebar.yml b/docs/_data/sidebars/mydoc_sidebar.yml
new file mode 100644
index 0000000..c4f6c46
--- /dev/null
+++ b/docs/_data/sidebars/mydoc_sidebar.yml
@@ -0,0 +1,66 @@
+# This is your sidebar TOC. The sidebar code loops through sections here and provides the appropriate formatting.
+
+entries:
+- title: sidebar
+ product: Documentation
+ version:
+ folders:
+
+ - title: Getting Started
+ output: web
+ folderitems:
+
+ - title: Overview
+ url: /index.html
+ output: web
+ type: homepage
+
+ - title: Quickstart
+ url: /quickstart.html
+ output: web
+
+ - title: Use Cases
+ url: /use_cases.html
+ output: web
+
+ - title: Talks & Powered By
+ url: /powered_by.html
+ output: web
+
+ - title: Documentation
+ output: web
+ folderitems:
+
+ - title: Concepts
+ url: /concepts.html
+ output: web
+
+ - title: Implementation
+ url: /implementation.html
+ output: web
+
+ - title: Configurations
+ url: /configurations.html
+ output: web
+
+ - title: SQL Queries
+ url: /sql_queries.html
+ output: web
+
+ - title: Migration Guide
+ url: /migration_guide.html
+ output: web
+
+ - title: Incremental Processing
+ url: /incremental_processing.html
+ output: web
+
+ - title: Admin Guide
+ url: /admin_guide.html
+ output: web
+
+ - title: Comparison
+ url: /comparison.html
+ output: web
+
+
diff --git a/docs/_data/strings.yml b/docs/_data/strings.yml
new file mode 100644
index 0000000..d7c1392
--- /dev/null
+++ b/docs/_data/strings.yml
@@ -0,0 +1,5 @@
+
+
+# placed here for translation purposes
+search_placeholder_text: search...
+search_no_results_text: No results found.
diff --git a/docs/_data/tags.yml b/docs/_data/tags.yml
new file mode 100644
index 0000000..0ad9ce5
--- /dev/null
+++ b/docs/_data/tags.yml
@@ -0,0 +1,10 @@
+allowed-tags:
+ - getting_started
+ - overview
+ - quickstart
+ - concepts
+ - sql_queries
+ - incremental_processing
+ - configurations
+ - news
+ - troubleshooting
diff --git a/docs/_data/topnav.yml b/docs/_data/topnav.yml
new file mode 100644
index 0000000..190573a
--- /dev/null
+++ b/docs/_data/topnav.yml
@@ -0,0 +1,30 @@
+## Topnav single links
+## if you want to list an external url, use external_url instead of url. the theme will apply a different link base.
+topnav:
+- title: Topnav
+ items:
+ - title: News
+ url: /news
+ - title: Community
+ url: /community.html
+ - title: Github
+ external_url: https://github.com/uber/hoodie
+
+#Topnav dropdowns
+topnav_dropdowns:
+- title: Topnav dropdowns
+ folders:
+ - title: Developer Resources
+ folderitems:
+ - title: Setup
+ url: /dev_setup.html
+ output: web
+ - title: API Docs
+ url: /api_docs.html
+ output: web
+ - title: Code Structure
+ url: /code_and_design.html
+ output: web
+ - title: Roadmap
+ url: /roadmap.html
+ output: web
diff --git a/docs/_includes/archive.html b/docs/_includes/archive.html
new file mode 100644
index 0000000..275850c
--- /dev/null
+++ b/docs/_includes/archive.html
@@ -0,0 +1,15 @@
+---
+layout: default
+type: archive
+---
+
+<div class="post-header">
+ <h1 class="post-title-main">{{ page.title }}</h1>
+</div>
+<div class="post-content">
+
+{{ content }}
+</div>
+
+
+
diff --git a/docs/_includes/callout.html b/docs/_includes/callout.html
new file mode 100644
index 0000000..d492b18
--- /dev/null
+++ b/docs/_includes/callout.html
@@ -0,0 +1 @@
+<div markdown="span" class="bs-callout bs-callout-{{include.type}}">{{include.content}}</div>
diff --git a/docs/_includes/custom/getting_started_series.html b/docs/_includes/custom/getting_started_series.html
new file mode 100644
index 0000000..5b573a9
--- /dev/null
+++ b/docs/_includes/custom/getting_started_series.html
@@ -0,0 +1,19 @@
+<div class="seriesContext">
+ <div class="btn-group">
+ <button type="button" data-toggle="dropdown" class="btn btn-primary dropdown-toggle">Getting Started <span class="caret"></span></button>
+ <ol class="dropdown-menu">
+ {% assign pages = site.pages | sort:"weight" %}
+ {% for p in pages %}
+ {% if p.series == "Getting Started" %}
+ {% if p.url == page.url %}
+ <li class="active"> → {{p.title}}</li>
+ {% else %}
+ <li>
+ <a href="{{p.url | remove: "/"}}">{{p.title}}</a>
+ </li>
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+ </ol>
+ </div>
+</div>
\ No newline at end of file
diff --git a/docs/_includes/custom/getting_started_series_next.html b/docs/_includes/custom/getting_started_series_next.html
new file mode 100644
index 0000000..c464214
--- /dev/null
+++ b/docs/_includes/custom/getting_started_series_next.html
@@ -0,0 +1,10 @@
+<p>{% assign series_pages = site.tags.series_acme %}
+ {% for p in pages %}
+ {% if p.series == "Getting Started" %}
+ {% assign nextTopic = page.weight | plus: "1" %}
+ {% if p.weight == nextTopic %}
+ <a href="{{p.url | remove: "/"}}"><button type="button" class="btn btn-primary">Next: {{p.title}}</button></a>
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+</p>
\ No newline at end of file
diff --git a/docs/_includes/custom/series_acme.html b/docs/_includes/custom/series_acme.html
new file mode 100644
index 0000000..b9ebf44
--- /dev/null
+++ b/docs/_includes/custom/series_acme.html
@@ -0,0 +1,19 @@
+<div class="seriesContext">
+ <div class="btn-group">
+ <button type="button" data-toggle="dropdown" class="btn btn-primary dropdown-toggle">Series Demo <span class="caret"></span></button>
+ <ol class="dropdown-menu">
+ {% assign pages = site.pages | sort:"weight" %}
+ {% for p in pages %}
+ {% if p.series == "ACME series" %}
+ {% if p.url == page.url %}
+ <li class="active"> → {{p.weight}}. {{p.title}}</li>
+ {% else %}
+ <li>
+ <a href="{{p.url | remove: "/"}}">{{p.weight}}. {{p.title}}</a>
+ </li>
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+ </ol>
+ </div>
+</div>
\ No newline at end of file
diff --git a/docs/_includes/custom/series_acme_next.html b/docs/_includes/custom/series_acme_next.html
new file mode 100644
index 0000000..9c9a11a
--- /dev/null
+++ b/docs/_includes/custom/series_acme_next.html
@@ -0,0 +1,30 @@
+<div class="seriesContext">
+ <a>
+ {% assign pages = site.pages | sort:"weight" %}
+ {% for pg in pages %}
+ {% if pg.series == "ACME series" %}
+ {% if pg.weight > page.weight %}
+ <a href="{{pg.url | remove: '/'}}"><button type="button" class="btn btn-primary">Next: {{pg.title}}</button></a>
+ {% break %}
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+ </a>
+
+ <div class="btn-group">
+ <button type="button" data-toggle="dropdown" class="btn btn-primary dropdown-toggle">Jump to: <span class="caret"></span></button>
+ <ol class="dropdown-menu">
+ {% for pg in pages %}
+ {% if pg.series == "ACME series" %}
+ {% if pg.url == page.url %}
+ <li class="active"> → {{pg.weight}}. {{pg.title}}</li>
+ {% else %}
+ <li>
+ <a href="{{pg.url | remove: '/'}}">{{pg.title}}</a>
+ </li>
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+ </ol>
+ </div>
+</div>
\ No newline at end of file
diff --git a/docs/_includes/custom/sidebarconfigs.html b/docs/_includes/custom/sidebarconfigs.html
new file mode 100644
index 0000000..cfdacc4
--- /dev/null
+++ b/docs/_includes/custom/sidebarconfigs.html
@@ -0,0 +1,19 @@
+{% if page.sidebar == "home_sidebar" %}
+{% assign sidebar = site.data.sidebars.home_sidebar.entries %}
+
+{% elsif page.sidebar == "mydoc_sidebar" %}
+{% assign sidebar = site.data.sidebars.mydoc_sidebar.entries %}
+
+{% else %}
+{% assign sidebar = site.data.sidebars.home_sidebar.entries %}
+{% endif %}
+
+
+
+{% comment %}
+sidebar configuration for print files
+{% endcomment %}
+
+{% if site.product == "mydoc" %}
+{% assign sidebar_pdf = site.data.sidebars.mydoc_sidebar.entries %}
+{% endif %}
diff --git a/docs/_includes/custom/usermap.html b/docs/_includes/custom/usermap.html
new file mode 100644
index 0000000..f90b5c2
--- /dev/null
+++ b/docs/_includes/custom/usermap.html
@@ -0,0 +1,14 @@
+
+<div id="userMap">
+<div class="content"><a href="p2_sample1.html"><div class="box box1">Connect to ADB</div></a></div>
+<div class="arrow">→</div>
+<div class="content"><a href="p2_sample2.html"><div class="box box2">Download and Build the Starter Kit</div></a></div>
+<div class="arrow">→</div>
+<div class="content"><a href="p2_sample3.html"><div class="box box3">Take a Tour</div></a></div>
+<div class="arrow">→</div>
+<div class="content"><a href="p2_sample4.html"><div class="box box4">Load Your Widgets</div></a></div>
+<div class="arrow">→</div>
+<div class="content"><a href="p2_sample5.html"><div class="box box5">Query for Something</div></a></div>
+<div class="clearfix"></div>
+
+</div>
diff --git a/docs/_includes/custom/usermapcomplex.html b/docs/_includes/custom/usermapcomplex.html
new file mode 100644
index 0000000..c75a652
--- /dev/null
+++ b/docs/_includes/custom/usermapcomplex.html
@@ -0,0 +1,91 @@
+<div id="userMap">
+
+ <!-- Button trigger modal -->
+<button type="button" class="btn btn-default btn-lg modalButton1" data-toggle="modal" data-target="#myModal1">Get Started</button>
+
+ <!-- Modal -->
+ <div class="modal fade" id="myModal1" tabindex="-1" role="dialog" aria-labelledby="myModalLabel">
+ <div class="modal-dialog" role="document">
+ <div class="modal-content">
+ <div class="modal-header">
+ <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button>
+ <h4 class="modal-title" id="myModalLabel">Get Started</h4>
+ </div>
+ <div class="modal-body">
+<p>This is just dummy text ... Your first steps should be to get started. You will need to do the following:</p>
+
+ <ul>
+ <li><a href="p2_sample6.html">Sample 6</a></li>
+ <li><a href="p2_sample7.html">Sample 7</a></li>
+ <li><a href="p2_sample8.html">Sample 8</a></li>
+ </ul>
+ <p>If you run into any of these setup issues, you must solve them before you can continue on.</p>
+
+ </div>
+ <div class="modal-footer">
+ <button type="button" class="btn btn-default" data-dismiss="modal">Close</button>
+ </div>
+ </div>
+ </div>
+ </div>
+ <span class="complexArrow">→</span>
+
+ <!-- Button trigger modal -->
+ <button type="button" class="btn btn-default btn-lg modalButton2" data-toggle="modal" data-target="#myModal2">Build your widgets</button>
+ <!-- Modal -->
+ <div class="modal fade" id="myModal2" tabindex="-1" role="dialog" aria-labelledby="myModalLabel">
+ <div class="modal-dialog" role="document">
+ <div class="modal-content">
+ <div class="modal-header">
+ <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button>
+ <h4 class="modal-title" id="myModalLabel">Build your widgets</h4>
+ </div>
+ <div class="modal-body">
+ <p>In this step, you will build the widgets for your system. The widgets form the various components that blah blah blah this is dummy text power the nuclear capabilities of your energy transformer into deep space using wormhole technology and warp drive speeds.</p>
+
+ <p>In order to configure your widgets, you will need to follow these topics:</p>
+ <ul>
+ <li><a href="p2_sample9.html">Sample 9</a></li>
+ <li><a href="p2_sample10.html">Sample 10</a></li>
+ <li><a href="p2_sample11.html">Sample 11</a></li>
+ </ul>
+ </div>
+ <div class="modal-footer">
+ <button type="button" class="btn btn-default" data-dismiss="modal">Close</button>
+ </div>
+ </div>
+ </div>
+ </div>
+
+ <span class="complexArrow">→</span>
+
+ <!-- Button trigger modal -->
+<button type="button" class="btn btn-default btn-lg modalButton3" data-toggle="modal" data-target="#myModal3">Publish your app</button>
+ <!-- Modal -->
+ <div class="modal fade" id="myModal3" tabindex="-1" role="dialog" aria-labelledby="myModalLabel">
+ <div class="modal-dialog" role="document">
+ <div class="modal-content">
+ <div class="modal-header">
+ <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button>
+ <h4 class="modal-title" id="myModalLabel">Publish your app</h4>
+ </div>
+ <div class="modal-body">
+ <p>After you've configured all the necessary components to build your space transformer, you need to publish your app. Of course this content is also just dummy text. Pay no particular attention to the content but rather the format and placement of the map.</p>
+ <p>To publish your app, see the following:
+ <ul>
+ <li><a href="p2_sample12.html">Sample 12</a></li>
+ <li><a href="p2_sample13.html">Sample 13</a></li>
+ <li><a href="p2_sample14.html">Sample 14</a></li>
+ </ul>
+ </div>
+ <div class="modal-footer">
+ <button type="button" class="btn btn-default" data-dismiss="modal">Close</button>
+ </div>
+ </div>
+ </div>
+ </div>
+
+
+<div class="clearfix"></div>
+
+</div>
diff --git a/docs/_includes/disqus.html b/docs/_includes/disqus.html
new file mode 100644
index 0000000..4fad7a2
--- /dev/null
+++ b/docs/_includes/disqus.html
@@ -0,0 +1,16 @@
+{% if site.disqus_shortname %}
+
+ <div id="disqus_thread"></div>
+ <script type="text/javascript">
+ /* * * CONFIGURATION VARIABLES: EDIT BEFORE PASTING INTO YOUR WEBPAGE * * */
+ var disqus_shortname = '{{site.disqus_shortname}}'; // required: replace example with your forum shortname
+
+ /* * * DON'T EDIT BELOW THIS LINE * * */
+ (function() {
+ var dsq = document.createElement('script'); dsq.type = 'text/javascript'; dsq.async = true;
+ dsq.src = '//' + disqus_shortname + '.disqus.com/embed.js';
+ (document.getElementsByTagName('head')[0] || document.getElementsByTagName('body')[0]).appendChild(dsq);
+ })();
+ </script>
+ <noscript>Please enable JavaScript to view the <a href="https://disqus.com/?ref_noscript">comments powered by Disqus.</a></noscript>
+{% endif %}
\ No newline at end of file
diff --git a/docs/_includes/feedback.html b/docs/_includes/feedback.html
new file mode 100644
index 0000000..4b55e44
--- /dev/null
+++ b/docs/_includes/feedback.html
@@ -0,0 +1,13 @@
+<li>
+{% if site.feedback_text %}
+ {% assign feedback_text = site.feedback_text %}
+{% else %}
+ {% assign feedback_text = "Feedback" %}
+{% endif %}
+
+{% if site.feedback_link %}
+ <a class="email" title="Submit feedback" href="{{site.feedback_link}}">{{feedback_text}}</a>
+{% else %}
+ <a class="email" title="Submit feedback" href="#" onclick="javascript:window.location='mailto:{{site.feedback_email}}?subject={{site.feedback_subject_line}} feedback&body=I have some feedback about the {{page.title}} page: ' + window.location.href;"><i class="fa fa-envelope-o"></i> {{feedback_text}}</a>
+{% endif %}
+<li>
diff --git a/docs/_includes/footer.html b/docs/_includes/footer.html
new file mode 100755
index 0000000..9847670
--- /dev/null
+++ b/docs/_includes/footer.html
@@ -0,0 +1,9 @@
+<footer>
+ <div class="row">
+ <div class="col-lg-12 footer">
+ ©{{ site.time | date: "%Y" }} {{site.company_name}}. All rights reserved. <br />
+{% if page.last_updated %}<span>Page last updated:</span> {{page.last_updated}}<br/>{% endif %} Site last generated: {{ site.time | date: "%b %-d, %Y" }} <br />
+ <!--<p><img src="{{ "images/company_logo.png" }}" alt="Company logo"/></p>-->
+ </div>
+ </div>
+</footer>
diff --git a/docs/_includes/google_analytics.html b/docs/_includes/google_analytics.html
new file mode 100644
index 0000000..56b2ee8
--- /dev/null
+++ b/docs/_includes/google_analytics.html
@@ -0,0 +1,6 @@
+<!-- the google_analytics_id gets auto inserted from the config file -->
+
+{% if site.google_analytics %}
+
+<script>(function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)})(window,document,'script','//www.google-analytics.com/analytics.js','ga');ga('create','{{site.google_analytics}}','auto');ga('require','displayfeatures');ga('send','pageview');</script>
+{% endif %}
\ No newline at end of file
diff --git a/docs/_includes/head.html b/docs/_includes/head.html
new file mode 100644
index 0000000..9a6f74e
--- /dev/null
+++ b/docs/_includes/head.html
@@ -0,0 +1,47 @@
+<meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<meta name="description" content="{% if page.summary %}{{ page.summary | strip_html | strip_newlines | truncate: 160 }}{% endif %}">
+<meta name="keywords" content="{{page.tags}}{% if page.tags %}, {% endif %} {{page.keywords}}">
+<title>{{ page.title }} | {{ site.site_title }}</title>
+<link rel="stylesheet" href="{{ "css/syntax.css" }}">
+
+
+<link rel="stylesheet" type="text/css" href="https://maxcdn.bootstrapcdn.com/font-awesome/4.5.0/css/font-awesome.min.css">
+<!--<link rel="stylesheet" type="text/css" href="css/bootstrap.min.css">-->
+<link rel="stylesheet" href="{{ "css/modern-business.css" }}">
+<link rel="stylesheet" href="{{ "css/lavish-bootstrap.css" }}">
+<link rel="stylesheet" href="{{ "css/customstyles.css" }}">
+<link rel="stylesheet" href="{{ "css/theme-blue.css" }}">
+
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/2.1.4/jquery.min.js"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery-cookie/1.4.1/jquery.cookie.min.js"></script>
+<script src="{{ "js/jquery.navgoco.min.js" }}"></script>
+
+
+<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.4/js/bootstrap.min.js"></script>
+<script src="https://cdnjs.cloudflare.com/ajax/libs/anchor-js/2.0.0/anchor.min.js"></script>
+<script src="{{ "js/toc.js" }}"></script>
+<script src="{{ "js/customscripts.js" }}"></script>
+
+<script>
+ (function(i,s,o,g,r,a,m){i['GoogleAnalyticsObject']=r;i[r]=i[r]||function(){
+ (i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),
+ m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)
+ })(window,document,'script','https://www.google-analytics.com/analytics.js','ga');
+
+ ga('create', 'UA-93561550-1', 'auto');
+ ga('send', 'pageview');
+
+</script>
+
+<link rel="shortcut icon" href="{{ "images/favicon.ico" }}">
+
+<!-- HTML5 Shim and Respond.js IE8 support of HTML5 elements and media queries -->
+<!-- WARNING: Respond.js doesn't work if you view the page via file:// -->
+<!--[if lt IE 9]>
+<script src="https://oss.maxcdn.com/libs/html5shiv/3.7.0/html5shiv.js"></script>
+<script src="https://oss.maxcdn.com/libs/respond.js/1.4.2/respond.min.js"></script>
+<![endif]-->
+
+<link rel="alternate" type="application/rss+xml" title="{{ site.title }}" href="{{ "feed.xml" | prepend: site.url }}">
diff --git a/docs/_includes/head_print.html b/docs/_includes/head_print.html
new file mode 100644
index 0000000..8f10c28
--- /dev/null
+++ b/docs/_includes/head_print.html
@@ -0,0 +1,33 @@
+<meta charset="utf-8">
+<meta http-equiv="X-UA-Compatible" content="IE=edge">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<meta name="description" content="{% if page.summary %}{{ page.summary | strip_html | strip_newlines | truncate: 160 }}{% endif %}">
+<meta name="keywords" content="{{page.tags}}{% if page.tags %}, {% endif %} {{page.keywords}}">
+<title>{% if page.homepage == true %} {{site.homepage_title}} {% elsif page.title %}{{ page.title }}{% endif %} | {{ site.site_title }}</title>
+
+
+<link rel="stylesheet" href="{{ "/css/syntax.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/font-awesome.min.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/bootstrap.min.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/modern-business.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/lavish-bootstrap.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/customstyles.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/theme-green.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/syntax.css" | prepend: site.baseurl | prepend: site.url }}">
+<link rel="stylesheet" href="{{ "/css/printstyles.css" | prepend: site.baseurl }}">
+
+<script>
+ Prince.addScriptFunc("datestamp", function() {
+ return "PDF last generated: {{ site.time | date: '%B %d, %Y' }}";
+ });
+</script>
+
+<script>
+ Prince.addScriptFunc("guideName", function() {
+ return "{{site.print_title}} User Guide";
+ });
+</script>
+
+
+
+
diff --git a/docs/_includes/image.html b/docs/_includes/image.html
new file mode 100644
index 0000000..7b3b0fa
--- /dev/null
+++ b/docs/_includes/image.html
@@ -0,0 +1 @@
+<figure>{% if {{include.url}} %}<a class="no_icon" target="_blank" href="{{include.url}}">{% endif %}<img class="docimage" src="images/{{include.file}}" alt="{{include.alt}}" {% if {{include.max-width}} %}style="max-width: {{include.max-width}}px"{% endif %} />{% if {{include.url}} %}</a>{% endif %}{% if {{include.caption}} %}<figcaption>{{include.caption}}</figcaption>{% endif %}</figure>
diff --git a/docs/_includes/important.html b/docs/_includes/important.html
new file mode 100644
index 0000000..af8824b
--- /dev/null
+++ b/docs/_includes/important.html
@@ -0,0 +1 @@
+<div markdown="span" class="alert alert-warning" role="alert"><i class="fa fa-warning"></i> <b>Important:</b> {{include.content}}</div>
\ No newline at end of file
diff --git a/docs/_includes/initialize_shuffle.html b/docs/_includes/initialize_shuffle.html
new file mode 100644
index 0000000..9a0f048
--- /dev/null
+++ b/docs/_includes/initialize_shuffle.html
@@ -0,0 +1,130 @@
+<script type="text/javascript">
+$(document).ready(function() {
+ $('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
+});
+
+</script>
+<!-- shuffle -->
+<script>
+var shuffleme = (function( $ ) {
+ 'use strict';
+
+ var $grid = $('#grid'),
+ $filterOptions = $('.filter-options'),
+ $sizer = $grid.find('.shuffle_sizer'),
+
+ init = function() {
+
+ // None of these need to be executed synchronously
+ setTimeout(function() {
+ listen();
+ setupFilters();
+ }, 100);
+
+ // instantiate the plugin
+ $grid.shuffle({
+ itemSelector: '[class*="col-"]',
+ sizer: $sizer
+ });
+ },
+
+ // Set up button clicks
+ setupFilters = function() {
+ var $btns = $filterOptions.children();
+ $btns.on('click', function() {
+ var $this = $(this),
+ isActive = $this.hasClass( 'active' ),
+ group = isActive ? 'all' : $this.data('group');
+
+ // Hide current label, show current label in title
+ if ( !isActive ) {
+ $('.filter-options .active').removeClass('active');
+ }
+
+ $this.toggleClass('active');
+
+ // Filter elements
+ $grid.shuffle( 'shuffle', group );
+ });
+
+ $btns = null;
+ },
+
+ // Re layout shuffle when images load. This is only needed
+ // below 768 pixels because the .picture-item height is auto and therefore
+ // the height of the picture-item is dependent on the image
+ // I recommend using imagesloaded to determine when an image is loaded
+ // but that doesn't support IE7
+ listen = function() {
+ var debouncedLayout = $.throttle( 300, function() {
+ $grid.shuffle('update');
+ });
+
+ // Get all images inside shuffle
+ $grid.find('img').each(function() {
+ var proxyImage;
+
+ // Image already loaded
+ if ( this.complete && this.naturalWidth !== undefined ) {
+ return;
+ }
+
+ // If none of the checks above matched, simulate loading on detached element.
+ proxyImage = new Image();
+ $( proxyImage ).on('load', function() {
+ $(this).off('load');
+ debouncedLayout();
+ });
+
+ proxyImage.src = this.src;
+ });
+
+ // Because this method doesn't seem to be perfect.
+ setTimeout(function() {
+ debouncedLayout();
+ }, 500);
+ };
+
+ return {
+ init: init
+ };
+}( jQuery ));
+
+
+
+$(document).ready(function() {
+ shuffleme.init();
+});
+
+ </script>
+
+ <!-- new attempt-->
+
+ <script>
+ $(document).ready(function() {
+
+ /* initialize shuffle plugin */
+ var $grid = $('#grid');
+
+ $grid.shuffle({
+ itemSelector: '.item' // the selector for the items in the grid
+ });
+
+});</script>
+
+<script>
+$('#filter a').click(function (e) {
+ e.preventDefault();
+
+ // set active class
+ $('#filter a').removeClass('active');
+ $(this).addClass('active');
+
+ // get group name from clicked item
+ var groupName = $(this).attr('data-group');
+
+ // reshuffle grid
+ $grid.shuffle('shuffle', groupName );
+});</script>
+
+
diff --git a/docs/_includes/inline_image.html b/docs/_includes/inline_image.html
new file mode 100644
index 0000000..1e7fd18
--- /dev/null
+++ b/docs/_includes/inline_image.html
@@ -0,0 +1 @@
+<img class="inline" src="images/{{include.file}}" alt="{{include.alt}}" />
diff --git a/docs/_includes/links.html b/docs/_includes/links.html
new file mode 100644
index 0000000..4f99e94
--- /dev/null
+++ b/docs/_includes/links.html
@@ -0,0 +1,44 @@
+{% comment %}Get links from each sidebar, as listed in the _config.yml file under sidebars{% endcomment %}
+
+{% for sidebar in site.sidebars %}
+{% for entry in site.data.sidebars[sidebar].entries %}
+{% for folder in entry.folders %}
+{% for folderitem in folder.folderitems %}
+{% if folderitem.url contains "html#" %}
+[{{folderitem.url | remove: "/" }}]: {{folderitem.url | remove: "/"}}
+{% else %}
+[{{folderitem.url | remove: "/" | remove: ".html"}}]: {{folderitem.url | remove: "/"}}
+{% endif %}
+{% for subfolders in folderitem.subfolders %}
+{% for subfolderitem in subfolders.subfolderitems %}
+[{{subfolderitem.url | remove: "/" | remove: ".html"}}]: {{subfolderitem.url | remove: "/"}}
+{% endfor %}
+{% endfor %}
+{% endfor %}
+{% endfor %}
+{% endfor %}
+{% endfor %}
+
+
+{% comment %} Get links from topnav {% endcomment %}
+
+{% for entry in site.data.topnav.topnav %}
+{% for item in entry.items %}
+{% if item.external_url == null %}
+[{{item.url | remove: "/" | remove: ".html"}}]: {{item.url | remove: "/"}}
+{% endif %}
+{% endfor %}
+{% endfor %}
+
+{% comment %}Get links from topnav dropdowns {% endcomment %}
+
+{% for entry in site.data.topnav.topnav_dropdowns %}
+{% for folder in entry.folders %}
+{% for folderitem in folder.folderitems %}
+{% if folderitem.external_url == null %}
+[{{folderitem.url | remove: "/" | remove: ".html"}}]: {{folderitem.url | remove: "/"}}
+{% endif %}
+{% endfor %}
+{% endfor %}
+{% endfor %}
+
diff --git a/docs/_includes/note.html b/docs/_includes/note.html
new file mode 100644
index 0000000..2c1cfe9
--- /dev/null
+++ b/docs/_includes/note.html
@@ -0,0 +1 @@
+<div markdown="span" class="alert alert-info" role="alert"><i class="fa fa-info-circle"></i> <b>Note:</b> {{include.content}}</div>
diff --git a/docs/_includes/sidebar.html b/docs/_includes/sidebar.html
new file mode 100644
index 0000000..1a9c236
--- /dev/null
+++ b/docs/_includes/sidebar.html
@@ -0,0 +1,56 @@
+{% include custom/sidebarconfigs.html %}
+
+<ul id="mysidebar" class="nav">
+ <li class="sidebarTitle">{{sidebar[0].product}} {{sidebar[0].version}}</li>
+ {% for entry in sidebar %}
+ {% for folder in entry.folders %}
+ {% if folder.output contains "web" %}
+ <li>
+ <a href="#">{{ folder.title }}</a>
+ <ul>
+ {% for folderitem in folder.folderitems %}
+ {% if folderitem.output contains "web" %}
+ {% if folderitem.external_url %}
+ <li><a href="{{folderitem.external_url}}" target="_blank">{{folderitem.title}}</a></li>
+ {% elsif page.url == folderitem.url %}
+ <li class="active"><a href="{{folderitem.url | remove: "/"}}">{{folderitem.title}}</a></li>
+ {% else %}
+ <li><a href="{{folderitem.url | remove: "/"}}">{{folderitem.title}}</a></li>
+ {% endif %}
+ {% for subfolders in folderitem.subfolders %}
+ {% if subfolders.output contains "web" %}
+ <li class="subfolders">
+ <a href="#">{{ subfolders.title }}</a>
+ <ul>
+ {% for subfolderitem in subfolders.subfolderitems %}
+ {% if subfolderitem.output contains "web" %}
+ {% if subfolderitem.external_url %}
+ <li><a href="{{subfolderitem.external_url}}" target="_blank">{{subfolderitem.title}}</a></li>
+ {% elsif page.url == subfolderitem.url %}
+ <li class="active"><a href="{{subfolderitem.url | remove: "/"}}">{{subfolderitem.title}}</a></li>
+ {% else %}
+ <li><a href="{{subfolderitem.url | remove: "/"}}">{{subfolderitem.title}}</a></li>
+ {% endif %}
+ {% endif %}
+ {% endfor %}
+ </ul>
+ </li>
+ {% endif %}
+ {% endfor %}
+ {% endif %}
+ {% endfor %}
+ </ul>
+ {% endif %}
+ {% endfor %}
+ {% endfor %}
+ <!-- if you aren't using the accordion, uncomment this block:
+ <p class="external">
+ <a href="#" id="collapseAll">Collapse All</a> | <a href="#" id="expandAll">Expand All</a>
+ </p>
+ -->
+ </li>
+</ul>
+</div>
+
+<!-- this highlights the active parent class in the navgoco sidebar. this is critical so that the parent expands when you're viewing a page. This must appear below the sidebar code above. Otherwise, if placed inside customscripts.js, the script runs before the sidebar code runs and the class never gets inserted.-->
+<script>$("li.active").parents('li').toggleClass("active");</script>
diff --git a/docs/_includes/taglogic.html b/docs/_includes/taglogic.html
new file mode 100644
index 0000000..c2f76b0
--- /dev/null
+++ b/docs/_includes/taglogic.html
@@ -0,0 +1,32 @@
+<p>The following pages and posts are tagged with <button type="button" style="cursor: default" class="btn btn-default navbar-btn">{{page.tagName}}</button></p>
+<table><thead><tr><th>Title</th><th>Type</th><th>Excerpt</th></tr></thead>
+ <tbody>
+ {% assign thisTag = page.tagName %}
+ {% for page in site.pages %}
+ {% for tag in page.tags %}
+ {% if tag == thisTag %}
+
+ <tr><td><a href="{{ page.url | remove: "/" }}">{{page.title}}</a></td>
+ <td><span class="label label-default">Page</span></td>
+ <td>{% if page.summary %} {{ page.summary | strip_html | strip_newlines | truncate: 160 }} {% else %} {{ page.content | truncatewords: 50 | strip_html }} {% endif %}</td>
+ </tr>
+ {% endif %}
+ {% endfor %}
+ {% endfor %}
+
+ {% assign thisTag = page.tagName %}
+ {% for post in site.posts %}
+ {% for tag in post.tags %}
+ {% if tag == thisTag %}
+
+ <tr><td><a href="{{ post.url | remove: "/" }}">{{post.title}}</a></td>
+ <td><span class="label label-primary">Post</span></td>
+ <td>{% if post.summary %} {{ post.summary | strip_html | strip_newlines | truncate: 160 }} {% else %} {{ post.content | truncatewords: 50 | strip_html }} {% endif %}</td>
+ </tr>
+ {% endif %}
+ {% endfor %}
+ {% endfor %}
+
+ </tbody>
+</table>
+
diff --git a/docs/_includes/tip.html b/docs/_includes/tip.html
new file mode 100644
index 0000000..faf48af
--- /dev/null
+++ b/docs/_includes/tip.html
@@ -0,0 +1 @@
+<div markdown="span" class="alert alert-success" role="alert"><i class="fa fa-check-square-o"></i> <b>Tip:</b> {{include.content}}</div>
\ No newline at end of file
diff --git a/docs/_includes/toc.html b/docs/_includes/toc.html
new file mode 100644
index 0000000..067141a
--- /dev/null
+++ b/docs/_includes/toc.html
@@ -0,0 +1,21 @@
+
+<!-- this handles the automatic toc. use ## for subheads to auto-generate the on-page minitoc. if you use html tags, you must supply an ID for the heading element in order for it to appear in the minitoc. -->
+<script>
+$( document ).ready(function() {
+ // Handler for .ready() called.
+
+$('#toc').toc({ minimumHeaders: 0, listType: 'ul', showSpeed: 0, headers: 'h2,h3,h4' });
+
+/* this offset helps account for the space taken up by the floating toolbar. */
+$('#toc').on('click', 'a', function() {
+ var target = $(this.getAttribute('href'))
+ , scroll_target = target.offset().top
+
+ $(window).scrollTop(scroll_target - 10);
+ return false
+})
+
+});
+</script>
+
+<div id="toc"></div>
diff --git a/docs/_includes/topnav.html b/docs/_includes/topnav.html
new file mode 100644
index 0000000..8748605
--- /dev/null
+++ b/docs/_includes/topnav.html
@@ -0,0 +1,75 @@
+<!-- Navigation -->
+<nav class="navbar navbar-inverse navbar-fixed-top">
+ <div class="container topnavlinks">
+ <div class="navbar-header">
+ <button type="button" class="navbar-toggle" data-toggle="collapse" data-target="#bs-example-navbar-collapse-1">
+ <span class="sr-only">Toggle navigation</span>
+ <span class="icon-bar"></span>
+ <span class="icon-bar"></span>
+ <span class="icon-bar"></span>
+ </button>
+ <a class="fa fa-home fa-lg navbar-brand" href="index.html"> <span class="projectTitle"> {{site.topnav_title}}</span></a>
+ </div>
+ <div class="collapse navbar-collapse" id="bs-example-navbar-collapse-1">
+ <ul class="nav navbar-nav navbar-right">
+ <!-- entries without drop-downs appear here -->
+ {% for entry in site.data.topnav.topnav %}
+ {% for item in entry.items %}
+ {% if item.external_url %}
+ <li><a href="{{item.external_url}}" target="_blank">{{item.title}}</a></li>
+ {% elsif page.url contains item.url %}
+ <li class="active"><a href="{{item.url | remove: "/"}}">{{item.title}}</a></li>
+ {% else %}
+ <li><a href="{{item.url | remove: "/"}}">{{item.title}}</a></li>
+ {% endif %}
+ {% endfor %}
+ {% endfor %}
+ <!-- entries with drop-downs appear here -->
+ <!-- conditional logic to control which topnav appears for the audience defined in the configuration file.-->
+ {% for entry in site.data.topnav.topnav_dropdowns %}
+ {% for folder in entry.folders %}
+ <li class="dropdown">
+ <a href="#" class="dropdown-toggle" data-toggle="dropdown">{{ folder.title }}<b class="caret"></b></a>
+ <ul class="dropdown-menu">
+ {% for folderitem in folder.folderitems %}
+ {% if folderitem.external_url %}
+ <li><a href="{{folderitem.external_url}}" target="_blank">{{folderitem.title}}</a></li>
+ {% elsif page.url contains folderitem.url %}
+ <li class="dropdownActive"><a href="{{folderitem.url | remove: "/"}}">{{folderitem.title}}</a></li>
+ {% else %}
+ <li><a href="{{folderitem.url | remove: "/"}}">{{folderitem.title}}</a></li>
+ {% endif %}
+ {% endfor %}
+ </ul>
+ </li>
+ {% endfor %}
+ {% endfor %}
+ {% if site.feedback_disable == null or site.feedback_disable == false %}
+ {% include feedback.html %}
+ {% endif %}
+ <!--comment out this block if you want to hide search-->
+ <li>
+ <!--start search-->
+ <div id="search-demo-container">
+ <input type="text" id="search-input" placeholder="{{site.data.strings.search_placeholder_text}}">
+ <ul id="results-container"></ul>
+ </div>
+ <script src="{{ "js/jekyll-search.js"}}" type="text/javascript"></script>
+ <script type="text/javascript">
+ SimpleJekyllSearch.init({
+ searchInput: document.getElementById('search-input'),
+ resultsContainer: document.getElementById('results-container'),
+ dataSource: '{{ "search.json" }}',
+ searchResultTemplate: '<li><a href="{url}" title="{{page.title | replace: "'", "\"}}">{title}</a></li>',
+ noResultsText: '{{site.data.strings.search_no_results_text}}',
+ limit: 10,
+ fuzzy: true,
+ })
+ </script>
+ <!--end search-->
+ </li>
+ </ul>
+ </div>
+ </div>
+ <!-- /.container -->
+</nav>
diff --git a/docs/_includes/warning.html b/docs/_includes/warning.html
new file mode 100644
index 0000000..e08268c
--- /dev/null
+++ b/docs/_includes/warning.html
@@ -0,0 +1 @@
+<div markdown="span" class="alert alert-danger" role="alert"><i class="fa fa-exclamation-circle"></i> <b>Warning:</b> {{include.content}}</div>
\ No newline at end of file
diff --git a/docs/_layouts/default.html b/docs/_layouts/default.html
new file mode 100644
index 0000000..90c1c4e
--- /dev/null
+++ b/docs/_layouts/default.html
@@ -0,0 +1,80 @@
+<!DOCTYPE html>
+<head>
+ {% include head.html %}
+ <script>
+ $(document).ready(function() {
+ // Initialize navgoco with default options
+ $("#mysidebar").navgoco({
+ caretHtml: '',
+ accordion: true,
+ openClass: 'active', // open
+ save: false, // leave false or nav highlighting doesn't work right
+ cookie: {
+ name: 'navgoco',
+ expires: false,
+ path: '/'
+ },
+ slide: {
+ duration: 400,
+ easing: 'swing'
+ }
+ });
+
+ $("#collapseAll").click(function(e) {
+ e.preventDefault();
+ $("#mysidebar").navgoco('toggle', false);
+ });
+
+ $("#expandAll").click(function(e) {
+ e.preventDefault();
+ $("#mysidebar").navgoco('toggle', true);
+ });
+
+ });
+
+ </script>
+ <script>
+ $(function () {
+ $('[data-toggle="tooltip"]').tooltip()
+ })
+ </script>
+ {% if page.datatable == true %}
+ <link rel="stylesheet" type="text/css" href="//cdn.datatables.net/1.10.5/css/jquery.dataTables.css">
+ <script type="text/javascript" charset="utf8" src="//cdn.datatables.net/1.10.5/js/jquery.dataTables.js"></script>
+ <script>
+ $(document).ready(function(){
+
+ $('table.datatable').DataTable( {
+ paging: false,
+ stateSave: true
+ }
+ );
+ </script>
+ {% endif %}
+
+</head>
+<body>
+{% include topnav.html %}
+<!-- Page Content -->
+<div class="container">
+ <div class="col-lg-12"> </div>
+ <!-- Content Row -->
+ <div class="row">
+ <!-- Sidebar Column -->
+ <div class="col-md-3">
+
+ {% include sidebar.html %}
+ <!-- Content Column -->
+ <div class="col-md-9">
+ {{content}}
+ </div>
+ <!-- /.row -->
+</div>
+<!-- /.container -->
+ </div>
+
+</body>
+{% if site.google_analytics %}
+{% include google_analytics.html %}
+{% endif %}
+</html>
\ No newline at end of file
diff --git a/docs/_layouts/default_print.html b/docs/_layouts/default_print.html
new file mode 100644
index 0000000..4bf619b
--- /dev/null
+++ b/docs/_layouts/default_print.html
@@ -0,0 +1,25 @@
+<!DOCTYPE html>
+<html lang="en">
+<html>
+<head>
+ {% include head_print.html %}
+
+
+</head>
+
+<body class="{% if page.type == "title"%}title{% elsif page.type == "frontmatter" %}frontmatter{% elsif page.type == "first_page" %}first_page{% endif %} print">
+
+<!-- Page Content -->
+<div class="container">
+ <!-- Content Column -->
+ <div class="col-md-9">
+
+ {{content}}
+ </div>
+
+</div> <!-- /.container -->
+
+</body>
+
+</html>
+
diff --git a/docs/_layouts/none.html b/docs/_layouts/none.html
new file mode 100644
index 0000000..60887a9
--- /dev/null
+++ b/docs/_layouts/none.html
@@ -0,0 +1,3 @@
+---
+---
+{{content}}
\ No newline at end of file
diff --git a/docs/_layouts/page.html b/docs/_layouts/page.html
new file mode 100644
index 0000000..d7aedc4
--- /dev/null
+++ b/docs/_layouts/page.html
@@ -0,0 +1,70 @@
+---
+layout: default
+---
+
+<div class="post-header">
+ <h1 class="post-title-main">{{ page.title }}</h1>
+</div>
+
+{% if page.simple_map == true %}
+
+<script>
+ $(document).ready ( function(){
+ $('.box{{page.box_number}}').addClass('active');
+ });
+</script>
+
+{% include custom/{{page.map_name}}.html %}
+
+{% elsif page.complex_map == true %}
+
+<script>
+ $(document).ready ( function(){
+ $('.modalButton{{page.box_number}}').addClass('active');
+ });
+</script>
+
+{% include custom/{{page.map_name}}.html %}
+
+{% endif %}
+
+<div class="post-content">
+
+ {% if page.summary %}
+ <div class="summary">{{page.summary}}</div>
+ {% endif %}
+
+ {% unless page.toc == false %}
+ {% include toc.html %}
+ {% endunless %}
+
+
+ {% if site.github_editme_path %}
+
+ <a target="_blank" href="https://github.com/{{site.github_editme_path}}{% unless page.url contains "index.html" %}pages/{% endunless %}{{page.folder}}{{page.url | remove: ".html" | append: ".md"}}" class="btn btn-default githubEditButton" role="button"><i class="fa fa-github fa-lg"></i> Edit me</a>
+
+ {% endif %}
+
+ {{content}}
+
+ <div class="tags">
+ {% if page.tags != null %}
+ <b>Tags: </b>
+ {% assign projectTags = site.data.tags.allowed-tags %}
+ {% for tag in page.tags %}
+ {% if projectTags contains tag %}
+ <a href="{{ "tag_" | append: tag | append: ".html" }}" class="btn btn-default navbar-btn cursorNorm" role="button">{{page.tagName}}{{tag}}</a>
+ {% endif %}
+ {% endfor %}
+ {% endif %}
+ </div>
+
+ {% if site.disqus %}
+{% include disqus.html %}
+ {% endif %}
+
+</div>
+
+{{site.data.alerts.hr_shaded}}
+
+{% include footer.html %}
diff --git a/docs/_layouts/page_print.html b/docs/_layouts/page_print.html
new file mode 100644
index 0000000..9e04604
--- /dev/null
+++ b/docs/_layouts/page_print.html
@@ -0,0 +1,15 @@
+---
+layout: default_print
+comments: true
+---
+<div class="post-header">
+ <h1 class="post-title-main" id="{{page.permalink | replace: '/', '' }}">{{ page.title }}</h1>
+</div>
+
+<div class="post-content">
+
+ {% if page.summary %}
+ <div class="summary">{{page.summary}}</div>
+ {% endif %}
+ {{ content }}
+</div>
diff --git a/docs/_layouts/post.html b/docs/_layouts/post.html
new file mode 100644
index 0000000..9067ebd
--- /dev/null
+++ b/docs/_layouts/post.html
@@ -0,0 +1,41 @@
+---
+layout: default
+---
+<article class="post" itemscope itemtype="http://schema.org/BlogPosting">
+
+ <header class="post-header">
+ <h1 class="post-title" itemprop="name headline">{{ page.title }}</h1>
+ <p class="post-meta"><time datetime="{{ page.date | date_to_xmlschema }}" itemprop="datePublished">{{ page.date | date: "%b %-d, %Y" }}</time> {% if page.author %}<span itemprop="author" itemscope itemtype="http://schema.org/Person"><span itemprop="name">/ {{ page.author }}</span></span>{% endif %}{% if page.tags != null %}/
+ {% assign projectTags = site.data.tags.allowed-tags %}
+ {% for tag in page.tags %}
+ {% if projectTags contains tag %}
+ <a href="{{ "tag_" | append: tag | append: ".html"}}">{{tag}}</a>{% unless forloop.last %}, {% endunless%}
+ {% endif %}
+ {% endfor %}
+ {% endif %}
+
+ </p>
+
+
+ </header>
+
+ <div class="post-content" itemprop="articleBody">
+
+ {% if page.summary %}
+ <div class="summary">{{page.summary}}</div>
+ {% endif %}
+
+ {{ content }}
+ </div>
+
+
+
+</article>
+
+{% if site.disqus %}
+{% include disqus.html %}
+{% endif %}
+
+{{site.data.alerts.hr_shaded}}
+
+{% include footer.html %}
diff --git a/docs/_posts/2016-12-30-strata-talk-2017.md b/docs/_posts/2016-12-30-strata-talk-2017.md
new file mode 100644
index 0000000..88b923e
--- /dev/null
+++ b/docs/_posts/2016-12-30-strata-talk-2017.md
@@ -0,0 +1,11 @@
+---
+title: "Connect with us at Strata San Jose March 2017"
+categories: update
+permalink: strata-talk.html
+tags: [news]
+---
+
+We will be presenting Hoodie & general concepts around how incremental processing works at Uber.
+Catch our talk **"Incremental Processing on Hadoop At Uber"**
+
+{% include links.html %}
diff --git a/docs/admin_guide.md b/docs/admin_guide.md
new file mode 100644
index 0000000..7f7e610
--- /dev/null
+++ b/docs/admin_guide.md
@@ -0,0 +1,444 @@
+---
+title: Admin Guide
+keywords: admin
+sidebar: mydoc_sidebar
+permalink: admin_guide.html
+toc: false
+summary: This section offers an overview of tools available to operate an ecosystem of Hudi datasets
+---
+
+Admins/ops can gain visibility into Hudi datasets/pipelines in the following ways
+
+ - Administering via the Admin CLI
+ - Graphite metrics
+ - Spark UI of the Hudi Application
+
+This section provides a glimpse into each of these, with some general guidance on troubleshooting
+
+## Admin CLI
+
+Once hoodie has been built via `mvn clean install -DskipTests`, the shell can be fired by via `cd hoodie-cli && ./hoodie-cli.sh`.
+A hoodie dataset resides on HDFS, in a location referred to as the **basePath** and we would need this location in order to connect to a Hoodie dataset.
+Hoodie library effectively manages this HDFS dataset internally, using .hoodie subfolder to track all metadata
+
+To initialize a hoodie table, use the following command.
+
+```
+18/09/06 15:56:52 INFO annotation.AutowiredAnnotationBeanPostProcessor: JSR-330 'javax.inject.Inject' annotation found and supported for autowiring
+============================================
+* *
+* _ _ _ _ *
+* | | | | | (_) *
+* | |__| | ___ ___ __| |_ ___ *
+* | __ |/ _ \ / _ \ / _` | |/ _ \ *
+* | | | | (_) | (_) | (_| | | __/ *
+* |_| |_|\___/ \___/ \__,_|_|\___| *
+* *
+============================================
+
+Welcome to Hoodie CLI. Please type help if you are looking for help.
+hoodie->create --path /user/hive/warehouse/table1 --tableName hoodie_table_1 --tableType COPY_ON_WRITE
+.....
+18/09/06 15:57:15 INFO table.HoodieTableMetaClient: Finished Loading Table of type COPY_ON_WRITE from ...
+```
+
+To see the description of hoodie table, use the command:
+```
+hoodie:hoodie_table_1->desc
+18/09/06 15:57:19 INFO timeline.HoodieActiveTimeline: Loaded instants []
+ _________________________________________________________
+ | Property | Value |
+ |========================================================|
+ | basePath | ... |
+ | metaPath | ... |
+ | fileSystem | hdfs |
+ | hoodie.table.name | hoodie_table_1 |
+ | hoodie.table.type | COPY_ON_WRITE |
+ | hoodie.archivelog.folder| |
+```
+
+Following is a sample command to connect to a Hoodie dataset contains uber trips.
+
+```
+hoodie:trips->connect --path /app/uber/trips
+
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: Attempting to load the commits under /app/uber/trips/.hoodie with suffix .commit
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: Attempting to load the commits under /app/uber/trips/.hoodie with suffix .inflight
+16/10/05 23:20:37 INFO model.HoodieTableMetadata: All commits :HoodieCommits{commitList=[20161002045850, 20161002052915, 20161002055918, 20161002065317, 20161002075932, 20161002082904, 20161002085949, 20161002092936, 20161002105903, 20161002112938, 20161002123005, 20161002133002, 20161002155940, 20161002165924, 20161002172907, 20161002175905, 20161002190016, 20161002192954, 20161002195925, 20161002205935, 20161002215928, 20161002222938, 20161002225915, 20161002232906, 20161003003028, 201 [...]
+Metadata for table trips loaded
+hoodie:trips->
+```
+
+Once connected to the dataset, a lot of other commands become available. The shell has contextual autocomplete help (press TAB) and below is a list of all commands, few of which are reviewed in this section
+are reviewed
+
+
+```
+hoodie:trips->help
+* ! - Allows execution of operating system (OS) commands
+* // - Inline comment markers (start of line only)
+* ; - Inline comment markers (start of line only)
+* addpartitionmeta - Add partition metadata to a dataset, if not present
+* clear - Clears the console
+* cls - Clears the console
+* commit rollback - Rollback a commit
+* commits compare - Compare commits with another Hoodie dataset
+* commit showfiles - Show file level details of a commit
+* commit showpartitions - Show partition level details of a commit
+* commits refresh - Refresh the commits
+* commits show - Show the commits
+* commits sync - Compare commits with another Hoodie dataset
+* connect - Connect to a hoodie dataset
+* date - Displays the local date and time
+* exit - Exits the shell
+* help - List all commands usage
+* quit - Exits the shell
+* records deduplicate - De-duplicate a partition path contains duplicates & produce repaired files to replace with
+* script - Parses the specified resource file and executes its commands
+* stats filesizes - File Sizes. Display summary stats on sizes of files
+* stats wa - Write Amplification. Ratio of how many records were upserted to how many records were actually written
+* sync validate - Validate the sync by counting the number of records
+* system properties - Shows the shell's properties
+* utils loadClass - Load a class
+* version - Displays shell version
+
+hoodie:trips->
+```
+
+
+#### Inspecting Commits
+
+The task of upserting or inserting a batch of incoming records is known as a **commit** in Hoodie. A commit provides basic atomicity guarantees such that only commited data is available for querying.
+Each commit has a monotonically increasing string/number called the **commit number**. Typically, this is the time at which we started the commit.
+
+To view some basic information about the last 10 commits,
+
+
+```
+hoodie:trips->commits show --sortBy "Total Bytes Written" --desc true --limit 10
+ ________________________________________________________________________________________________________________________________________________________________________
+ | CommitTime | Total Bytes Written| Total Files Added| Total Files Updated| Total Partitions Written| Total Records Written| Total Update Records Written| Total Errors|
+ |=======================================================================================================================================================================|
+ ....
+ ....
+ ....
+hoodie:trips->
+
+```
+
+At the start of each write, Hoodie also writes a .inflight commit to the .hoodie folder. You can use the timestamp there to estimate how long the commit has been inflight
+
+
+```
+$ hdfs dfs -ls /app/uber/trips/.hoodie/*.inflight
+-rw-r--r-- 3 vinoth supergroup 321984 2016-10-05 23:18 /app/uber/trips/.hoodie/20161005225920.inflight
+```
+
+
+#### Drilling Down to a specific Commit
+
+To understand how the writes spread across specific partiions,
+
+
+```
+hoodie:trips->commit showpartitions --commit 20161005165855 --sortBy "Total Bytes Written" --desc true --limit 10
+ __________________________________________________________________________________________________________________________________________
+ | Partition Path| Total Files Added| Total Files Updated| Total Records Inserted| Total Records Updated| Total Bytes Written| Total Errors|
+ |=========================================================================================================================================|
+ ....
+ ....
+```
+
+If you need file level granularity , we can do the following
+
+
+```
+hoodie:trips->commit showfiles --commit 20161005165855 --sortBy "Partition Path"
+ ________________________________________________________________________________________________________________________________________________________
+ | Partition Path| File ID | Previous Commit| Total Records Updated| Total Records Written| Total Bytes Written| Total Errors|
+ |=======================================================================================================================================================|
+ ....
+ ....
+```
+
+
+#### FileSystem View
+
+Hudi views each partition as a collection of file-groups with each file-group containing a list of file-slices in commit
+order (See Concepts). The below commands allow users to view the file-slices for a data-set.
+
+```
+ hoodie:stock_ticks_mor->show fsview all
+ ....
+ _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta File Size| Delta Files |
+ |==============================================================================================================================================================================================================================================================================================================================================================================================================|
+ | 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]|
+
+
+
+ hoodie:stock_ticks_mor->show fsview latest --partitionPath "2018/08/31"
+ ......
+ ___________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________ [...]
+ | Partition | FileId | Base-Instant | Data-File | Data-File Size| Num Delta Files| Total Delta Size| Delta Size - compaction scheduled| Delta Size - compaction unscheduled| Delta To Base Ratio - compaction scheduled| Delta To Base Ratio - compaction unscheduled| Delta Files - compaction scheduled | Delta Files - compaction unscheduled|
+ |========================================================================================================================================================================================================================================================================================================================================================================================================================================================================================================== [...]
+ | 2018/08/31| 111415c3-f26d-4639-86c8-f9956f245ac3| 20181002180759| hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/111415c3-f26d-4639-86c8-f9956f245ac3_0_20181002180759.parquet| 432.5 KB | 1 | 20.8 KB | 20.8 KB | 0.0 B | 0.0 B | 0.0 B | [HoodieLogFile {hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/.111415c3-f26d-4639-86c8-f9956f245ac3_20181002180759.log.1}]| [] |
+
+ hoodie:stock_ticks_mor->
+```
+
+
+#### Statistics
+
+Since Hoodie directly manages file sizes for HDFS dataset, it might be good to get an overall picture
+
+
+```
+hoodie:trips->stats filesizes --partitionPath 2016/09/01 --sortBy "95th" --desc true --limit 10
+ ________________________________________________________________________________________________
+ | CommitTime | Min | 10th | 50th | avg | 95th | Max | NumFiles| StdDev |
+ |===============================================================================================|
+ | <COMMIT_ID> | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 93.9 MB | 2 | 2.3 KB |
+ ....
+ ....
+```
+
+In case of Hoodie write taking much longer, it might be good to see the write amplification for any sudden increases
+
+
+```
+hoodie:trips->stats wa
+ __________________________________________________________________________
+ | CommitTime | Total Upserted| Total Written| Write Amplifiation Factor|
+ |=========================================================================|
+ ....
+ ....
+```
+
+
+#### Archived Commits
+
+In order to limit the amount of growth of .commit files on HDFS, Hoodie archives older .commit files (with due respect to the cleaner policy) into a commits.archived file.
+This is a sequence file that contains a mapping from commitNumber => json with raw information about the commit (same that is nicely rolled up above).
+
+
+#### Compactions
+
+To get an idea of the lag between compaction and writer applications, use the below command to list down all
+pending compactions.
+
+```
+hoodie:trips->compactions show all
+ ___________________________________________________________________
+ | Compaction Instant Time| State | Total FileIds to be Compacted|
+ |==================================================================|
+ | <INSTANT_1> | REQUESTED| 35 |
+ | <INSTANT_2> | INFLIGHT | 27 |
+
+```
+
+To inspect a specific compaction plan, use
+
+```
+hoodie:trips->compaction show --instant <INSTANT_1>
+ _________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | Partition Path| File Id | Base Instant | Data File Path | Total Delta Files| getMetrics |
+ |================================================================================================================================================================================================================================================
+ | 2018/07/17 | <UUID> | <INSTANT_1> | viewfs://ns-default/.../../UUID_<INSTANT>.parquet | 1 | {TOTAL_LOG_FILES=1.0, TOTAL_IO_READ_MB=1230.0, TOTAL_LOG_FILES_SIZE=2.51255751E8, TOTAL_IO_WRITE_MB=991.0, TOTAL_IO_MB=2221.0}|
+
+```
+
+To manually schedule or run a compaction, use the below command. This command uses spark launcher to perform compaction
+operations. NOTE : Make sure no other application is scheduling compaction for this dataset concurrently
+
+```
+hoodie:trips->help compaction schedule
+Keyword: compaction schedule
+Description: Schedule Compaction
+ Keyword: sparkMemory
+ Help: Spark executor memory
+ Mandatory: false
+ Default if specified: '__NULL__'
+ Default if unspecified: '1G'
+
+* compaction schedule - Schedule Compaction
+```
+
+```
+hoodie:trips->help compaction run
+Keyword: compaction run
+Description: Run Compaction for given instant time
+ Keyword: tableName
+ Help: Table name
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: parallelism
+ Help: Parallelism for hoodie compaction
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: schemaFilePath
+ Help: Path for Avro schema file
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: sparkMemory
+ Help: Spark executor memory
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: retry
+ Help: Number of retries
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+ Keyword: compactionInstant
+ Help: Base path for the target hoodie dataset
+ Mandatory: true
+ Default if specified: '__NULL__'
+ Default if unspecified: '__NULL__'
+
+* compaction run - Run Compaction for given instant time
+```
+
+##### Validate Compaction
+
+Validating a compaction plan : Check if all the files necessary for compactions are present and are valid
+
+```
+hoodie:stock_ticks_mor->compaction validate --instant 20181005222611
+...
+
+ COMPACTION PLAN VALID
+
+ ___________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error|
+ |==========================================================================================================================================================================================================================|
+ | 05320e98-9a57-4c38-b809-a6beaaeb36bd| 20181005222445 | hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/05320e98-9a57-4c38-b809-a6beaaeb36bd_0_20181005222445.parquet| 1 | true | |
+
+
+
+hoodie:stock_ticks_mor->compaction validate --instant 20181005222601
+
+ COMPACTION PLAN INVALID
+
+ _______________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________
+ | File Id | Base Instant Time| Base Data File | Num Delta Files| Valid| Error |
+ |=====================================================================================================================================================================================================================================================================================================|
+ | 05320e98-9a57-4c38-b809-a6beaaeb36bd| 20181005222445 | hdfs://namenode:8020/user/hive/warehouse/stock_ticks_mor/2018/08/31/05320e98-9a57-4c38-b809-a6beaaeb36bd_0_20181005222445.parquet| 1 | false| All log files specified in compaction operation is not present. Missing .... |
+
+
+```
+
+##### NOTE
+
+The following commands must be executed without any other writer/ingestion application running.
+
+Sometimes, it becomes necessary to remove a fileId from a compaction-plan inorder to speed-up or unblock compaction
+operation. Any new log-files that happened on this file after the compaction got scheduled will be safely renamed
+so that are preserved. Hudi provides the following CLI to support it
+
+
+##### UnScheduling Compaction
+
+```
+hoodie:trips->compaction unscheduleFileId --fileId <FileUUID>
+....
+No File renames needed to unschedule file from pending compaction. Operation successful.
+
+```
+
+In other cases, an entire compaction plan needs to be reverted. This is supported by the following CLI
+```
+hoodie:trips->compaction unschedule --compactionInstant <compactionInstant>
+.....
+No File renames needed to unschedule pending compaction. Operation successful.
+```
+
+##### Repair Compaction
+
+The above compaction unscheduling operations could sometimes fail partially (e:g -> HDFS temporarily unavailable). With
+partial failures, the compaction operation could become inconsistent with the state of file-slices. When you run
+`compaction validate`, you can notice invalid compaction operations if there is one. In these cases, the repair
+command comes to the rescue, it will rearrange the file-slices so that there is no loss and the file-slices are
+consistent with the compaction plan
+
+```
+hoodie:stock_ticks_mor->compaction repair --instant 20181005222611
+......
+Compaction successfully repaired
+.....
+```
+
+
+## Metrics
+
+Once the Hoodie Client is configured with the right datasetname and environment for metrics, it produces the following graphite metrics, that aid in debugging hoodie datasets
+
+ - **Commit Duration** - This is amount of time it took to successfully commit a batch of records
+ - **Rollback Duration** - Similarly, amount of time taken to undo partial data left over by a failed commit (happens everytime automatically after a failing write)
+ - **File Level metrics** - Shows the amount of new files added, versions, deleted (cleaned) in each commit
+ - **Record Level Metrics** - Total records inserted/updated etc per commit
+ - **Partition Level metrics** - number of partitions upserted (super useful to understand sudden spikes in commit duration)
+
+These metrics can then be plotted on a standard tool like grafana. Below is a sample commit duration chart.
+
+{% include image.html file="hoodie_commit_duration.png" alt="hoodie_commit_duration.png" max-width="1000" %}
+
+
+## Troubleshooting Failures
+
+Section below generally aids in debugging Hoodie failures. Off the bat, the following metadata is added to every record to help triage issues easily using standard Hadoop SQL engines (Hive/Presto/Spark)
+
+ - **_hoodie_record_key** - Treated as a primary key within each HDFS partition, basis of all updates/inserts
+ - **_hoodie_commit_time** - Last commit that touched this record
+ - **_hoodie_file_name** - Actual file name containing the record (super useful to triage duplicates)
+ - **_hoodie_partition_path** - Path from basePath that identifies the partition containing this record
+
+{% include callout.html content="Note that as of now, Hoodie assumes the application passes in the same deterministic partitionpath for a given recordKey. i.e the uniqueness of record key is only enforced within each partition" type="warning" %}
+
+
+#### Missing records
+
+Please check if there were any write errors using the admin commands above, during the window at which the record could have been written.
+If you do find errors, then the record was not actually written by Hoodie, but handed back to the application to decide what to do with it.
+
+#### Duplicates
+
+First of all, please confirm if you do indeed have duplicates **AFTER** ensuring the query is accessing the Hoodie datasets [properly](sql_queries.html) .
+
+ - If confirmed, please use the metadata fields above, to identify the physical files & partition files containing the records .
+ - If duplicates span files across partitionpath, then this means your application is generating different partitionPaths for same recordKey, Please fix your app
+ - if duplicates span multiple files within the same partitionpath, please engage with mailing list. This should not happen. You can use the `records deduplicate` command to fix your data.
+
+#### Spark failures
+
+Typical upsert() DAG looks like below. Note that Hoodie client also caches intermediate RDDs to intelligently profile workload and size files and spark parallelism.
+Also Spark UI shows sortByKey twice due to the probe job also being shown, nonetheless its just a single sort.
+
+
+{% include image.html file="hoodie_upsert_dag.png" alt="hoodie_upsert_dag.png" max-width="1000" %}
+
+
+At a high level, there are two steps
+
+**Index Lookup to identify files to be changed**
+
+ - Job 1 : Triggers the input data read, converts to HoodieRecord object and then stops at obtaining a spread of input records to target partition paths
+ - Job 2 : Load the set of file names which we need check against
+ - Job 3 & 4 : Actual lookup after smart sizing of spark join parallelism, by joining RDDs in 1 & 2 above
+ - Job 5 : Have a tagged RDD of recordKeys with locations
+
+**Performing the actual writing of data**
+
+ - Job 6 : Lazy join of incoming records against recordKey, location to provide a final set of HoodieRecord which now contain the information about which file/partitionpath they are found at (or null if insert). Then also profile the workload again to determine sizing of files
+ - Job 7 : Actual writing of data (update + insert + insert turned to updates to maintain file size)
+
+Depending on the exception source (Hoodie/Spark), the above knowledge of the DAG can be used to pinpoint the actual issue. The most often encountered failures result from YARN/HDFS temporary failures.
+In the future, a more sophisticated debug/management UI would be added to the project, that can help automate some of this debugging.
diff --git a/docs/api_docs.md b/docs/api_docs.md
new file mode 100644
index 0000000..24bfd6b
--- /dev/null
+++ b/docs/api_docs.md
@@ -0,0 +1,10 @@
+---
+title: API Docs
+keywords: usecases
+sidebar: mydoc_sidebar
+permalink: api_docs.html
+---
+
+Work In Progress
+
+
diff --git a/docs/code_and_design.md b/docs/code_and_design.md
new file mode 100644
index 0000000..3baaa97
--- /dev/null
+++ b/docs/code_and_design.md
@@ -0,0 +1,38 @@
+---
+title: Code Structure
+keywords: usecases
+sidebar: mydoc_sidebar
+permalink: code_and_design.html
+---
+
+## Code & Project Structure
+
+ * hoodie-client : Spark client library to take a bunch of inserts + updates and apply them to a Hoodie table
+ * hoodie-common : Common code shared between different artifacts of Hoodie
+
+ ## HoodieLogFormat
+
+ The following diagram depicts the LogFormat for Hoodie MergeOnRead. Each logfile consists of one or more log blocks.
+ Each logblock follows the format shown below.
+
+ | Field | Description |
+ |-------------- |------------------|
+ | MAGIC | A magic header that marks the start of a block |
+ | VERSION | The version of the LogFormat, this helps define how to switch between different log format as it evolves |
+ | TYPE | The type of the log block |
+ | HEADER LENGTH | The length of the headers, 0 if no headers |
+ | HEADER | Metadata needed for a log block. For eg. INSTANT_TIME, TARGET_INSTANT_TIME, SCHEMA etc. |
+ | CONTENT LENGTH | The length of the content of the log block |
+ | CONTENT | The content of the log block, for example, for a DATA_BLOCK, the content is (number of records + actual records) in byte [] |
+ | FOOTER LENGTH | The length of the footers, 0 if no footers |
+ | FOOTER | Metadata needed for a log block. For eg. index entries, a bloom filter for records in a DATA_BLOCK etc. |
+ | LOGBLOCK LENGTH | The total number of bytes written for a log block, typically the SUM(everything_above). This is a LONG. This acts as a reverse pointer to be able to traverse the log in reverse.|
+
+
+ {% include image.html file="hoodie_log_format_v2.png" alt="hoodie_log_format_v2.png" %}
+
+
+
+
+
+
diff --git a/docs/community.md b/docs/community.md
new file mode 100644
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--- /dev/null
+++ b/docs/community.md
@@ -0,0 +1,22 @@
+---
+title: Community
+keywords: usecases
+sidebar: mydoc_sidebar
+toc: false
+permalink: community.html
+---
+
+## Contributing
+We :heart: contributions. If you find a bug in the library or would like to add new features, go ahead and open
+issues or pull requests against this repo. Before you do so, please sign the
+[Apache CLA](https://www.apache.org/licenses/icla.pdf).
+Also, be sure to write unit tests for your bug fix or feature to show that it works as expected.
+If the reviewer feels this contributions needs to be in the release notes, please add it to CHANGELOG.md as well.
+
+If you want to participate in day-day conversations, please join our [slack group](https://hoodielib.slack.com/x-147852474016-157730502112/signup).
+If you are from select pre-listed email domains, you can self signup. Others, please subscribe to dev@hudi.apache.org
+
+## Becoming a Committer
+
+Hoodie has adopted a lot of guidelines set forth in [Google Chromium project](https://www.chromium.org/getting-involved/become-a-committer), to determine committership proposals. However, given this is a much younger project, we would have the contribution bar to be 10-15 non-trivial patches instead.
+Additionally, we expect active engagement with the community over a few months, in terms of conference/meetup talks, helping out with issues/questions on slack/github.
diff --git a/docs/comparison.md b/docs/comparison.md
new file mode 100644
index 0000000..36a2ec5
--- /dev/null
+++ b/docs/comparison.md
@@ -0,0 +1,61 @@
+---
+title: Comparison
+keywords: usecases
+sidebar: mydoc_sidebar
+permalink: comparison.html
+toc: false
+---
+
+Apache Hudi fills a big void for processing data on top of HDFS, and thus mostly co-exists nicely with these technologies. However,
+it would be useful to understand how Hudi fits into the current big data ecosystem, contrasting it with a few related systems
+and bring out the different tradeoffs these systems have accepted in their design.
+
+## Kudu
+
+[Apache Kudu](https://kudu.apache.org) is a storage system that has similar goals as Hudi, which is to bring real-time analytics on petabytes of data via first
+class support for `upserts`. A key differentiator is that Kudu also attempts to serve as a datastore for OLTP workloads, something that Hudi does not aspire to be.
+Consequently, Kudu does not support incremental pulling (as of early 2017), something Hudi does to enable incremental processing use cases.
+
+
+Kudu diverges from a distributed file system abstraction and HDFS altogether, with its own set of storage servers talking to each other via RAFT.
+Hudi, on the other hand, is designed to work with an underlying Hadoop compatible filesystem (HDFS,S3 or Ceph) and does not have its own fleet of storage servers,
+instead relying on Apache Spark to do the heavy-lifting. Thu, Hudi can be scaled easily, just like other Spark jobs, while Kudu would require hardware
+& operational support, typical to datastores like HBase or Vertica. We have not at this point, done any head to head benchmarks against Kudu (given RTTable is WIP).
+But, if we were to go with results shared by [CERN](https://db-blog.web.cern.ch/blog/zbigniew-baranowski/2017-01-performance-comparison-different-file-formats-and-storage-engines) ,
+we expect Hudi to positioned at something that ingests parquet with superior performance.
+
+
+## Hive Transactions
+
+[Hive Transactions/ACID](https://cwiki.apache.org/confluence/display/Hive/Hive+Transactions) is another similar effort, which tries to implement storage like
+`merge-on-read`, on top of ORC file format. Understandably, this feature is heavily tied to Hive and other efforts like [LLAP](https://cwiki.apache.org/confluence/display/Hive/LLAP).
+Hive transactions does not offer the read-optimized storage option or the incremental pulling, that Hudi does. In terms of implementation choices, Hudi leverages
+the full power of a processing framework like Spark, while Hive transactions feature is implemented underneath by Hive tasks/queries kicked off by user or the Hive metastore.
+Based on our production experience, embedding Hudi as a library into existing Spark pipelines was much easier and less operationally heavy, compared with the other approach.
+Hudi is also designed to work with non-hive enginers like Presto/Spark and will incorporate file formats other than parquet over time.
+
+## HBase
+
+Even though [HBase](https://hbase.apache.org) is ultimately a key-value store for OLTP workloads, users often tend to associate HBase with analytics given the proximity to Hadoop.
+Given HBase is heavily write-optimized, it supports sub-second upserts out-of-box and Hive-on-HBase lets users query that data. However, in terms of actual performance for analytical workloads,
+hybrid columnar storage formats like Parquet/ORC handily beat HBase, since these workloads are predominantly read-heavy. Hudi bridges this gap between faster data and having
+analytical storage formats. From an operational perspective, arming users with a library that provides faster data, is more scalable, than managing a big farm of HBase region servers,
+just for analytics. Finally, HBase does not support incremental processing primitives like `commit times`, `incremental pull` as first class citizens like Hudi.
+
+## Stream Processing
+
+A popular question, we get is : "How does Hudi relate to stream processing systems?", which we will try to answer here. Simply put, Hudi can integrate with
+batch (`copy-on-write storage`) and streaming (`merge-on-read storage`) jobs of today, to store the computed results in Hadoop. For Spark apps, this can happen via direct
+integration of Hudi library with Spark/Spark streaming DAGs. In case of Non-Spark processing systems (eg: Flink, Hive), the processing can be done in the respective systems
+and later sent into a Hudi table via a Kafka topic/HDFS intermediate file. In more conceptual level, data processing
+pipelines just consist of three components : `source`, `processing`, `sink`, with users ultimately running queries against the sink to use the results of the pipeline.
+Hudi can act as either a source or sink, that stores data on HDFS. Applicability of Hudi to a given stream processing pipeline ultimately boils down to suitability
+of Presto/SparkSQL/Hive for your queries.
+
+More advanced use cases revolve around the concepts of [incremental processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop), which effectively
+uses Hudi even inside the `processing` engine to speed up typical batch pipelines. For e.g: Hudi can be used as a state store inside a processing DAG (similar
+to how [rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend) is used by Flink). This is an item on the roadmap
+and will eventually happen as a [Beam Runner](https://github.com/uber/hoodie/issues/8)
+
+
+
diff --git a/docs/concepts.md b/docs/concepts.md
new file mode 100644
index 0000000..5ce3fc6
--- /dev/null
+++ b/docs/concepts.md
@@ -0,0 +1,159 @@
+---
+title: Concepts
+keywords: concepts
+sidebar: mydoc_sidebar
+permalink: concepts.html
+toc: false
+summary: "Here we introduce some basic concepts & give a broad technical overview of Hudi"
+---
+
+Apache Hudi (pronounced “Hudi”) provides the following primitives over datasets on HDFS
+
+ * Upsert (how do I change the dataset?)
+ * Incremental consumption (how do I fetch data that changed?)
+
+
+In order to achieve this, Hudi maintains a `timeline` of all activity performed on the dataset, that helps provide `instantaenous` views of the dataset,
+while also efficiently supporting retrieval of data in the order of arrival into the dataset.
+Such key activities include
+
+ * `COMMITS` - A single commit captures information about an **atomic write** of a batch of records into a dataset.
+ Commits are identified by a monotonically increasing timestamp, denoting the start of the write operation.
+ * `CLEANS` - Background activity that gets rid of older versions of files in the dataset, that are no longer needed.
+ * `DELTA_COMMITS` - A single commit captures information about an **atomic write** of a batch of records into a
+ MergeOnRead storage type of dataset
+ * `COMPACTIONS` - Background activity to reconcile differential data structures within Hudi e.g: moving updates from row based log files to columnar formats.
+
+
+{% include image.html file="Hudi_timeline.png" alt="Hudi_timeline.png" %}
+
+Example above shows upserts happenings between 10:00 and 10:20 on a Hudi dataset, roughly every 5 mins, leaving commit metadata on the Hudi timeline, along
+with other background cleaning/compactions. One key observation to make is that the commit time indicates the `arrival time` of the data (10:20AM), while the actual data
+organization reflects the actual time or `event time`, the data was intended for (hourly buckets from 07:00). These are two key concepts when reasoning about tradeoffs between latency and completeness of data.
+
+When there is late arriving data (data intended for 9:00 arriving >1 hr late at 10:20), we can see the upsert producing new data into even older time buckets/folders.
+With the help of the timeline, an incremental query attempting to get all new data that was committed successfully since 10:00 hours, is able to very efficiently consume
+only the changed files without say scanning all the time buckets > 07:00.
+
+## Terminologies
+
+ * `Hudi Dataset`
+ A structured hive/spark dataset managed by Hudi. Hudi supports both partitioned and non-partitioned Hive tables.
+ * `Commit`
+ A commit marks a new batch of data applied to a dataset. Hudi maintains monotonically increasing timestamps to track commits and guarantees that a commit is atomically
+ published.
+ * `Commit Timeline`
+ Commit Timeline refers to the sequence of Commits that was applied in order on a dataset over its lifetime.
+ * `File Slice`
+ Hudi provides efficient handling of updates by having a fixed mapping between record key to a logical file Id.
+ Hudi uses MVCC to provide atomicity and isolation of readers from a writer. This means that a logical fileId will
+ have many physical versions of it. Each of these physical version of a file represents a complete view of the
+ file as of a commit and is called File Slice
+ * `File Group`
+ A file-group is a file-slice timeline. It is a list of file-slices in commit order. It is identified by `file id`
+
+
+## Storage Types
+
+Hudi storage types capture how data is indexed & laid out on the filesystem, and how the above primitives and timeline activities are implemented on top of
+such organization (i.e how data is written). This is not to be confused with the notion of Read Optimized & Near-Real time tables, which are merely how the underlying data is exposed
+to the queries (i.e how data is read).
+
+Hudi (will) supports the following storage types.
+
+| Storage Type | Supported Tables |
+|-------------- |------------------|
+| Copy On Write | Read Optimized |
+| Merge On Read | Read Optimized + Near Real-time |
+
+ - Copy On Write : A heavily read optimized storage type, that simply creates new versions of files corresponding to the records that changed.
+ - Merge On Read : Also provides a near-real time datasets in the order of 5 mins, by shifting some of the write cost, to the reads and merging incoming and on-disk data on-the-fly
+
+{% include callout.html content="Hudi is a young project. merge-on-read is currently underway. Get involved [here](https://github.com/uber/Hudi/projects/1)" type="info" %}
+
+Regardless of the storage type, Hudi organizes a datasets into a directory structure under a `basepath`,
+very similar to Hive tables. Dataset is broken up into partitions, which are folders containing files for that partition.
+Each partition uniquely identified by its `partitionpath`, which is relative to the basepath.
+
+Within each partition, records are distributed into multiple files. Each file is identified by an unique `file id` and the `commit` that
+produced the file. Multiple files can share the same file id but written at different commits, in case of updates.
+
+Each record is uniquely identified by a `record key` and mapped to a file id forever. This mapping between record key
+and file id, never changes once the first version of a record has been written to a file. In short, the
+ `file id` identifies a group of files, that contain all versions of a group of records.
+
+
+## Copy On Write
+
+As mentioned above, each commit on Copy On Write storage, produces new versions of files. In other words, we implicitly compact every
+commit, such that only columnar data exists. As a result, the write amplification (number of bytes written for 1 byte of incoming data)
+ is much higher, where read amplification is close to zero. This is a much desired property for a system like Hadoop, which is predominantly read-heavy.
+
+Following illustrates how this works conceptually, when data written into copy-on-write storage and two queries running on top of it.
+
+
+{% include image.html file="Hudi_cow.png" alt="Hudi_cow.png" %}
+
+
+As data gets written, updates to existing file ids, produce a new version for that file id stamped with the commit and
+inserts allocate a new file id and write its first version for that file id. These file versions and their commits are color coded above.
+Normal SQL queries running against such dataset (eg: select count(*) counting the total records in that partition), first checks the timeline for latest commit
+and filters all but latest versions of each file id. As you can see, an old query does not see the current inflight commit's files colored in pink,
+but a new query starting after the commit picks up the new data. Thus queries are immune to any write failures/partial writes and only run on committed data.
+
+The intention of copy on write storage, is to fundamentally improve how datasets are managed today on Hadoop through
+
+ - First class support for atomically updating data at file-level, instead of rewriting whole tables/partitions
+ - Ability to incremental consume changes, as opposed to wasteful scans or fumbling with heuristical approaches
+ - Tight control file sizes to keep query performance excellent (small files hurt query performance considerably).
+
+
+## Merge On Read
+
+Merge on read storage is a superset of copy on write, in the sense it still provides a read optimized view of the dataset via the Read Optmized table.
+But, additionally stores incoming upserts for each file id, onto a `row based append log`, that enables providing near real-time data to the queries
+ by applying the append log, onto the latest version of each file id on-the-fly during query time. Thus, this storage type attempts to balance read and write amplication intelligently, to provide near real-time queries.
+The most significant change here, would be to the compactor, which now carefully chooses which append logs need to be compacted onto
+their columnar base data, to keep the query performance in check (larger append logs would incur longer merge times with merge data on query side)
+
+Following illustrates how the storage works, and shows queries on both near-real time table and read optimized table.
+
+{% include image.html file="Hudi_mor.png" alt="Hudi_mor.png" max-width="1000" %}
+
+
+There are lot of interesting things happening in this example, which bring out the subleties in the approach.
+
+ - We now have commits every 1 minute or so, something we could not do in the other storage type.
+ - Within each file id group, now there is an append log, which holds incoming updates to records in the base columnar files. In the example, the append logs hold
+ all the data from 10:05 to 10:10. The base columnar files are still versioned with the commit, as before.
+ Thus, if one were to simply look at base files alone, then the storage layout looks exactly like a copy on write table.
+ - A periodic compaction process reconciles these changes from the append log and produces a new version of base file, just like what happened at 10:05 in the example.
+ - There are two ways of querying the same underlying storage: ReadOptimized (RO) Table and Near-Realtime (RT) table, depending on whether we chose query performance or freshness of data.
+ - The semantics around when data from a commit is available to a query changes in a subtle way for the RO table. Note, that such a query
+ running at 10:10, wont see data after 10:05 above, while a query on the RT table always sees the freshest data.
+ - When we trigger compaction & what it decides to compact hold all the key to solving these hard problems. By implementing a compacting
+ strategy, where we aggressively compact the latest partitions compared to older partitions, we could ensure the RO Table sees data
+ published within X minutes in a consistent fashion.
+
+{% include callout.html content="Hudi is a young project. merge-on-read is currently underway. Get involved [here](https://github.com/uber/hoodie/projects/1)" type="info" %}
+
+The intention of merge on read storage, is to enable near real-time processing directly on top of Hadoop, as opposed to copying
+data out to specialized systems, which may not be able to handle the data volume.
+
+## Trade offs when choosing different storage types and views
+
+### Storage Types
+
+| Trade-off | CopyOnWrite | MergeOnRead |
+|-------------- |------------------| ------------------|
+| Data Latency | Higher | Lower |
+| Update cost (I/O) | Higher (rewrite entire parquet) | Lower (append to delta file) |
+| Parquet File Size | Smaller (high update(I/0) cost) | Larger (low update cost) |
+| Write Amplification | Higher | Lower (depending on compaction strategy) |
+
+### Hudi Views
+
+| Trade-off | ReadOptimized | RealTime |
+|-------------- |------------------| ------------------|
+| Data Latency | Higher | Lower |
+| Query Latency | Lower (raw columnar performance) | Higher (merge columnar + row based delta) |
\ No newline at end of file
diff --git a/docs/configurations.md b/docs/configurations.md
new file mode 100644
index 0000000..50a7e5f
--- /dev/null
+++ b/docs/configurations.md
@@ -0,0 +1,203 @@
+---
+title: Configurations
+keywords: configurations
+sidebar: mydoc_sidebar
+permalink: configurations.html
+toc: false
+summary: "Here we list all possible configurations and what they mean"
+---
+
+### Configuration
+
+* [HoodieWriteConfig](#HoodieWriteConfig) <br/>
+<span style="color:grey">Top Level Config which is passed in when HoodieWriteClent is created.</span>
+ - [withPath](#withPath) (hoodie_base_path) <br/>
+ <span style="color:grey">Base HDFS path under which all the data partitions are created. Hoodie stores all the main meta-data about commits, savepoints, cleaning audit logs etc in .hoodie directory under the base directory. </span>
+ - [withSchema](#withSchema) (schema_str) <br/>
+ <span style="color:grey">This is the current reader avro schema for the Hoodie Dataset. This is a string of the entire schema. HoodieWriteClient uses this schema to pass on to implementations of HoodieRecordPayload to convert from the source format to avro record. This is also used when re-writing records during an update. </span>
+ - [withParallelism](#withParallelism) (insert_shuffle_parallelism = 200, upsert_shuffle_parallelism = 200) <br/>
+ <span style="color:grey">Insert DAG uses the insert_parallelism in every shuffle. Upsert DAG uses the upsert_parallelism in every shuffle. Typical workload is profiled and once a min parallelism is established, trade off between latency and cluster usage optimizations this is tuned and have a conservatively high number to optimize for latency and </span>
+ - [combineInput](#combineInput) (on_insert = false, on_update=true) <br/>
+ <span style="color:grey">Flag which first combines the input RDD and merges multiple partial records into a single record before inserting or updating in HDFS</span>
+ - [withWriteStatusStorageLevel](#withWriteStatusStorageLevel) (level = MEMORY_AND_DISK_SER) <br/>
+ <span style="color:grey">HoodieWriteClient.insert and HoodieWriteClient.upsert returns a persisted RDD[WriteStatus], this is because the Client can choose to inspect the WriteStatus and choose and commit or not based on the failures. This is a configuration for the storage level for this RDD </span>
+ - [withAutoCommit](#withAutoCommit) (autoCommit = true) <br/>
+ <span style="color:grey">Should HoodieWriteClient autoCommit after insert and upsert. The client can choose to turn off auto-commit and commit on a "defined success condition"</span>
+ - [withAssumeDatePartitioning](#withAssumeDatePartitioning) (assumeDatePartitioning = false) <br/>
+ <span style="color:grey">Should HoodieWriteClient assume the data is partitioned by dates, i.e three levels from base path. This is a stop-gap to support tables created by versions < 0.3.1. Will be removed eventually </span>
+ - [withConsistencyCheckEnabled](#withConsistencyCheckEnabled) (enabled = false) <br/>
+ <span style="color:grey">Should HoodieWriteClient perform additional checks to ensure written files' are listable on the underlying filesystem/storage. Set this to true, to workaround S3's eventual consistency model and ensure all data written as a part of a commit is faithfully available for queries. </span>
+
+ - [withIndexConfig](#withIndexConfig) (HoodieIndexConfig) <br/>
+ <span style="color:grey">Hoodie uses a index to help find the FileID which contains an incoming record key. This is pluggable to have a external index (HBase) or use the default bloom filter stored in the Parquet files</span>
+ - [withIndexType](#withIndexType) (indexType = BLOOM) <br/>
+ <span style="color:grey">Type of index to use. Default is Bloom filter. Possible options are [BLOOM | HBASE | INMEMORY]. Bloom filters removes the dependency on a external system and is stored in the footer of the Parquet Data Files</span>
+ - [bloomFilterNumEntries](#bloomFilterNumEntries) (60000) <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/>This is the number of entries to be stored in the bloom filter. We assume the maxParquetFileSize is 128MB and averageRecordSize is 1024B and hence we approx a total of 130K records in a file. The default (60000) is roughly half of this approximation. [#70](https://github.com/uber/hoodie/issues/70) tracks computing this dynamically. Warning: Setting this very low, will generate a lot of false positives and index lo [...]
+ - [bloomFilterFPP](#bloomFilterFPP) (0.000000001) <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> Error rate allowed given the number of entries. This is used to calculate how many bits should be assigned for the bloom filter and the number of hash functions. This is usually set very low (default: 0.000000001), we like to tradeoff disk space for lower false positives</span>
+ - [bloomIndexPruneByRanges](#bloomIndexPruneByRanges) (true) <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, range information from files to leveraged speed up index lookups. Particularly helpful, if the key has a monotonously increasing prefix, such as timestamp.</span>
+ - [bloomIndexUseCaching](#bloomIndexUseCaching) (true) <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> When true, the input RDD will cached to speed up index lookup by reducing IO for computing parallelism or affected partitions</span>
+ - [bloomIndexParallelism](#bloomIndexParallelism) (0) <br/>
+ <span style="color:grey">Only applies if index type is BLOOM. <br/> This is the amount of parallelism for index lookup, which involves a Spark Shuffle. By default, this is auto computed based on input workload characteristics</span>
+ - [hbaseZkQuorum](#hbaseZkQuorum) (zkString) <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum url to connect to.</span>
+ - [hbaseZkPort](#hbaseZkPort) (port) <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase ZK Quorum port to connect to.</span>
+ - [hbaseTableName](#hbaseTableName) (tableName) <br/>
+ <span style="color:grey">Only application if index type is HBASE. HBase Table name to use as the index. Hoodie stores the row_key and [partition_path, fileID, commitTime] mapping in the table.</span>
+
+ - [withStorageConfig](#withStorageConfig) (HoodieStorageConfig) <br/>
+ <span style="color:grey">Storage related configs</span>
+ - [limitFileSize](#limitFileSize) (size = 120MB) <br/>
+ <span style="color:grey">Hoodie re-writes a single file during update (copy_on_write) or a compaction (merge_on_read). This is fundamental unit of parallelism. It is important that this is aligned with the underlying filesystem block size. </span>
+ - [parquetBlockSize](#parquetBlockSize) (rowgroupsize = 120MB) <br/>
+ <span style="color:grey">Parquet RowGroup size. Its better than this is aligned with the file size, so that a single column within a file is stored continuously on disk</span>
+ - [parquetPageSize](#parquetPageSize) (pagesize = 1MB) <br/>
+ <span style="color:grey">Parquet page size. Page is the unit of read within a parquet file. Within a block, pages are compressed seperately. </span>
+ - [logFileMaxSize](#logFileMaxSize) (logFileSize = 1GB) <br/>
+ <span style="color:grey">LogFile max size. This is the maximum size allowed for a log file before it is rolled over to the next version. </span>
+ - [logFileDataBlockMaxSize](#logFileDataBlockMaxSize) (dataBlockSize = 256MB) <br/>
+ <span style="color:grey">LogFile Data block max size. This is the maximum size allowed for a single data block to be appended to a log file. This helps to make sure the data appended to the log file is broken up into sizable blocks to prevent from OOM errors. This size should be greater than the JVM memory. </span>
+
+ - [withCompactionConfig](#withCompactionConfig) (HoodieCompactionConfig) <br/>
+ <span style="color:grey">Cleaning and configurations related to compaction techniques</span>
+ - [withCleanerPolicy](#withCleanerPolicy) (policy = KEEP_LATEST_COMMITS) <br/>
+ <span style="color:grey">Hoodie Cleaning policy. Hoodie will delete older versions of parquet files to re-claim space. Any Query/Computation referring to this version of the file will fail. It is good to make sure that the data is retained for more than the maximum query execution time.</span>
+ - [retainCommits](#retainCommits) (no_of_commits_to_retain = 24) <br/>
+ <span style="color:grey">Number of commits to retain. So data will be retained for num_of_commits * time_between_commits (scheduled). This also directly translates into how much you can incrementally pull on this dataset</span>
+ - [archiveCommitsWith](#archiveCommitsWith) (minCommits = 96, maxCommits = 128) <br/>
+ <span style="color:grey">Each commit is a small file in the .hoodie directory. Since HDFS is not designed to handle multiple small files, hoodie archives older commits into a sequential log. A commit is published atomically by a rename of the commit file.</span>
+ - [compactionSmallFileSize](#compactionSmallFileSize) (size = 0) <br/>
+ <span style="color:grey">Small files can always happen because of the number of insert records in a paritition in a batch. Hoodie has an option to auto-resolve small files by masking inserts into this partition as updates to existing small files. The size here is the minimum file size considered as a "small file size". This should be less < maxFileSize and setting it to 0, turns off this feature. </span>
+ - [insertSplitSize](#insertSplitSize) (size = 500000) <br/>
+ <span style="color:grey">Insert Write Parallelism. Number of inserts grouped for a single partition. Writing out 100MB files, with atleast 1kb records, means 100K records per file. Default is to overprovision to 500K. To improve insert latency, tune this to match the number of records in a single file. Setting this to a low number, will result in small files (particularly when compactionSmallFileSize is 0)</span>
+ - [autoTuneInsertSplits](#autoTuneInsertSplits) (true) <br/>
+ <span style="color:grey">Should hoodie dynamically compute the insertSplitSize based on the last 24 commit's metadata. Turned off by default. </span>
+ - [approxRecordSize](#approxRecordSize) () <br/>
+ <span style="color:grey">The average record size. If specified, hoodie will use this and not compute dynamically based on the last 24 commit's metadata. No value set as default. This is critical in computing the insert parallelism and bin-packing inserts into small files. See above.</span>
+ - [withCompactionLazyBlockReadEnabled](#withCompactionLazyBlockReadEnabled) (true) <br/>
+ <span style="color:grey">When a CompactedLogScanner merges all log files, this config helps to choose whether the logblocks should be read lazily or not. Choose true to use I/O intensive lazy block reading (low memory usage) or false for Memory intensive immediate block read (high memory usage)</span>
+ - [withMaxNumDeltaCommitsBeforeCompaction](#withMaxNumDeltaCommitsBeforeCompaction) (maxNumDeltaCommitsBeforeCompaction = 10) <br/>
+ <span style="color:grey">Number of max delta commits to keep before triggering an inline compaction</span>
+ - [withCompactionReverseLogReadEnabled](#withCompactionReverseLogReadEnabled) (false) <br/>
+ <span style="color:grey">HoodieLogFormatReader reads a logfile in the forward direction starting from pos=0 to pos=file_length. If this config is set to true, the Reader reads the logfile in reverse direction, from pos=file_length to pos=0</span>
+
+ - [withMetricsConfig](#withMetricsConfig) (HoodieMetricsConfig) <br/>
+ <span style="color:grey">Hoodie publishes metrics on every commit, clean, rollback etc.</span>
+ - [on](#on) (true) <br/>
+ <span style="color:grey">Turn sending metrics on/off. on by default.</span>
+ - [withReporterType](#withReporterType) (GRAPHITE) <br/>
+ <span style="color:grey">Type of metrics reporter. Graphite is the default and the only value suppported.</span>
+ - [toGraphiteHost](#toGraphiteHost) () <br/>
+ <span style="color:grey">Graphite host to connect to</span>
+ - [onGraphitePort](#onGraphitePort) () <br/>
+ <span style="color:grey">Graphite port to connect to</span>
+ - [usePrefix](#usePrefix) () <br/>
+ <span style="color:grey">Standard prefix for all metrics</span>
+
+ - [withMemoryConfig](#withMemoryConfig) (HoodieMemoryConfig) <br/>
+ <span style="color:grey">Memory related configs</span>
+ - [withMaxMemoryFractionPerPartitionMerge](#withMaxMemoryFractionPerPartitionMerge) (maxMemoryFractionPerPartitionMerge = 0.6) <br/>
+ <span style="color:grey">This fraction is multiplied with the user memory fraction (1 - spark.memory.fraction) to get a final fraction of heap space to use during merge </span>
+ - [withMaxMemorySizePerCompactionInBytes](#withMaxMemorySizePerCompactionInBytes) (maxMemorySizePerCompactionInBytes = 1GB) <br/>
+ <span style="color:grey">HoodieCompactedLogScanner reads logblocks, converts records to HoodieRecords and then merges these log blocks and records. At any point, the number of entries in a log block can be less than or equal to the number of entries in the corresponding parquet file. This can lead to OOM in the Scanner. Hence, a spillable map helps alleviate the memory pressure. Use this config to set the max allowable inMemory footprint of the spillable map.</span>
+
+ - [S3Configs](s3_hoodie.html) (Hoodie S3 Configs) <br/>
+ <span style="color:grey">Configurations required for S3 and Hoodie co-operability.</span>
+
+ - [GCSConfigs](gcs_hoodie.html) (Hoodie GCS Configs) <br/>
+ <span style="color:grey">Configurations required for GCS and Hoodie co-operability.</span>
+
+* [Hoodie Datasource](#datasource) <br/>
+<span style="color:grey">Configs for datasource</span>
+ - [write options](#writeoptions) (write.format.option(...)) <br/>
+ <span style="color:grey"> Options useful for writing datasets </span>
+ - [OPERATION_OPT_KEY](#OPERATION_OPT_KEY) (Default: upsert) <br/>
+ <span style="color:grey">whether to do upsert, insert or bulkinsert for the write operation</span>
+ - [STORAGE_TYPE_OPT_KEY](#STORAGE_TYPE_OPT_KEY) (Default: COPY_ON_WRITE) <br/>
+ <span style="color:grey">The storage type for the underlying data, for this write. This can't change between writes.</span>
+ - [TABLE_NAME_OPT_KEY](#TABLE_NAME_OPT_KEY) (Default: None (mandatory)) <br/>
+ <span style="color:grey">Hive table name, to register the dataset into.</span>
+ - [PRECOMBINE_FIELD_OPT_KEY](#PRECOMBINE_FIELD_OPT_KEY) (Default: ts) <br/>
+ <span style="color:grey">Field used in preCombining before actual write. When two records have the same key value,
+ we will pick the one with the largest value for the precombine field, determined by Object.compareTo(..)</span>
+ - [PAYLOAD_CLASS_OPT_KEY](#PAYLOAD_CLASS_OPT_KEY) (Default: com.uber.hoodie.OverwriteWithLatestAvroPayload) <br/>
+ <span style="color:grey">Payload class used. Override this, if you like to roll your own merge logic, when upserting/inserting.
+ This will render any value set for `PRECOMBINE_FIELD_OPT_VAL` in-effective</span>
+ - [RECORDKEY_FIELD_OPT_KEY](#RECORDKEY_FIELD_OPT_KEY) (Default: uuid) <br/>
+ <span style="color:grey">Record key field. Value to be used as the `recordKey` component of `HoodieKey`. Actual value
+ will be obtained by invoking .toString() on the field value. Nested fields can be specified using
+ the dot notation eg: `a.b.c`</span>
+ - [PARTITIONPATH_FIELD_OPT_KEY](#PARTITIONPATH_FIELD_OPT_KEY) (Default: partitionpath) <br/>
+ <span style="color:grey">Partition path field. Value to be used at the `partitionPath` component of `HoodieKey`.
+ Actual value ontained by invoking .toString()</span>
+ - [KEYGENERATOR_CLASS_OPT_KEY](#KEYGENERATOR_CLASS_OPT_KEY) (Default: com.uber.hoodie.SimpleKeyGenerator) <br/>
+ <span style="color:grey">Key generator class, that implements will extract the key out of incoming `Row` object</span>
+ - [COMMIT_METADATA_KEYPREFIX_OPT_KEY](#COMMIT_METADATA_KEYPREFIX_OPT_KEY) (Default: _) <br/>
+ <span style="color:grey">Option keys beginning with this prefix, are automatically added to the commit/deltacommit metadata.
+ This is useful to store checkpointing information, in a consistent way with the hoodie timeline</span>
+
+ - [read options](#readoptions) (read.format.option(...)) <br/>
+ <span style="color:grey">Options useful for reading datasets</span>
+ - [VIEW_TYPE_OPT_KEY](#VIEW_TYPE_OPT_KEY) (Default: = read_optimized) <br/>
+ <span style="color:grey">Whether data needs to be read, in incremental mode (new data since an instantTime)
+ (or) Read Optimized mode (obtain latest view, based on columnar data)
+ (or) Real time mode (obtain latest view, based on row & columnar data)</span>
+ - [BEGIN_INSTANTTIME_OPT_KEY](#BEGIN_INSTANTTIME_OPT_KEY) (Default: None (Mandatory in incremental mode)) <br/>
+ <span style="color:grey">Instant time to start incrementally pulling data from. The instanttime here need not
+ necessarily correspond to an instant on the timeline. New data written with an
+ `instant_time > BEGIN_INSTANTTIME` are fetched out. For e.g: '20170901080000' will get
+ all new data written after Sep 1, 2017 08:00AM.</span>
+ - [END_INSTANTTIME_OPT_KEY](#END_INSTANTTIME_OPT_KEY) (Default: latest instant (i.e fetches all new data since begin instant time)) <br/>
+ <span style="color:grey"> Instant time to limit incrementally fetched data to. New data written with an
+ `instant_time <= END_INSTANTTIME` are fetched out.</span>
+
+
+### Tuning
+
+Writing data via Hudi happens as a Spark job and thus general rules of spark debugging applies here too. Below is a list of things to keep in mind, if you are looking to improving performance or reliability.
+
+ - **Write operations** : Use `bulkinsert` to load new data into a table, and there on use `upsert`/`insert`.
+ Difference between them is that bulk insert uses a disk based write path to scale to load large inputs without need to cache it.
+ - **Input Parallelism** : By default, Hoodie tends to over-partition input (i.e `withParallelism(1500)`), to ensure each Spark partition stays within the 2GB limit for inputs upto 500GB. Bump this up accordingly if you have larger inputs. We recommend having shuffle parallelism `hoodie.[insert|upsert|bulkinsert].shuffle.parallelism` such that its atleast input_data_size/500MB
+ - **Off-heap memory** : Hoodie writes parquet files and that needs good amount of off-heap memory proportional to schema width. Consider setting something like `spark.yarn.executor.memoryOverhead` or `spark.yarn.driver.memoryOverhead`, if you are running into such failures.
+ - **Spark Memory** : Typically, hoodie needs to be able to read a single file into memory to perform merges or compactions and thus the executor memory should be sufficient to accomodate this. In addition, Hoodie caches the input to be able to intelligently place data and thus leaving some `spark.storage.memoryFraction` will generally help boost performance.
+ - **Sizing files** : Set `limitFileSize` above judiciously, to balance ingest/write latency vs number of files & consequently metadata overhead associated with it.
+ - **Timeseries/Log data** : Default configs are tuned for database/nosql changelogs where individual record sizes are large. Another very popular class of data is timeseries/event/log data that tends to be more volumnious with lot more records per partition. In such cases
+ - Consider tuning the bloom filter accuracy via `.bloomFilterFPP()/bloomFilterNumEntries()` to achieve your target index look up time
+ - Consider making a key that is prefixed with time of the event, which will enable range pruning & significantly speeding up index lookup.
+ - **GC Tuning** : Please be sure to follow garbage collection tuning tips from Spark tuning guide to avoid OutOfMemory errors
+ - [Must] Use G1/CMS Collector. Sample CMS Flags to add to spark.executor.extraJavaOptions : ``-XX:NewSize=1g -XX:SurvivorRatio=2 -XX:+UseCompressedOops -XX:+UseConcMarkSweepGC -XX:+UseParNewGC -XX:CMSInitiatingOccupancyFraction=70 -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintTenuringDistribution -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/ho [...]
+ - If it keeps OOMing still, reduce spark memory conservatively: `spark.memory.fraction=0.2, spark.memory.storageFraction=0.2` allowing it to spill rather than OOM. (reliably slow vs crashing intermittently)
+
+ Below is a full working production config
+
+ ```
+ spark.driver.extraClassPath /etc/hive/conf
+ spark.driver.extraJavaOptions -XX:+PrintTenuringDistribution -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCApplicationStoppedTime -XX:+PrintGCApplicationConcurrentTime -XX:+PrintGCTimeStamps -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.driver.maxResultSize 2g
+ spark.driver.memory 4g
+ spark.executor.cores 1
+ spark.executor.extraJavaOptions -XX:+PrintFlagsFinal -XX:+PrintReferenceGC -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps -XX:+PrintAdaptiveSizePolicy -XX:+UnlockDiagnosticVMOptions -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/tmp/hoodie-heapdump.hprof
+ spark.executor.id driver
+ spark.executor.instances 300
+ spark.executor.memory 6g
+ spark.rdd.compress true
+
+ spark.kryoserializer.buffer.max 512m
+ spark.serializer org.apache.spark.serializer.KryoSerializer
+ spark.shuffle.memoryFraction 0.2
+ spark.shuffle.service.enabled true
+ spark.sql.hive.convertMetastoreParquet false
+ spark.storage.memoryFraction 0.6
+ spark.submit.deployMode cluster
+ spark.task.cpus 1
+ spark.task.maxFailures 4
+
+ spark.yarn.driver.memoryOverhead 1024
+ spark.yarn.executor.memoryOverhead 3072
+ spark.yarn.max.executor.failures 100
+ ```
diff --git a/docs/css/bootstrap.min.css b/docs/css/bootstrap.min.css
new file mode 100755
index 0000000..7b4112f
--- /dev/null
+++ b/docs/css/bootstrap.min.css
@@ -0,0 +1,5 @@
+/*!
+ * Bootstrap v3.3.2 (http://getbootstrap.com)
+ * Copyright 2011-2016 Twitter, Inc.
+ * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
+ *//*! normalize.css v3.0.2 | MIT License | git.io/normalize */html{font-family:sans-serif;-webkit-text-size-adjust:100%;-ms-text-size-adjust:100%}body{margin:0}article,aside,details,figcaption,figure,footer,header,hgroup,main,menu,nav,section,summary{display:block}audio,canvas,progress,video{display:inline-block;vertical-align:baseline}audio:not([controls]){display:none;height:0}[hidden],template{display:none}a{background-color:transparent}a:active,a:hover{outline:0}abbr[title]{border-b [...]
\ No newline at end of file
diff --git a/docs/css/customstyles.css b/docs/css/customstyles.css
new file mode 100644
index 0000000..676c804
--- /dev/null
+++ b/docs/css/customstyles.css
@@ -0,0 +1,1181 @@
+body {
+ font-size:15px;
+}
+
+.bs-callout {
+ padding: 20px;
+ margin: 20px 0;
+ border: 1px solid #eee;
+ border-left-width: 5px;
+ border-radius: 3px;
+}
+.bs-callout h4 {
+ margin-top: 0;
+ margin-bottom: 5px;
+}
+.bs-callout p:last-child {
+ margin-bottom: 0;
+}
+.bs-callout code {
+ border-radius: 3px;
+}
+.bs-callout+.bs-callout {
+ margin-top: -5px;
+}
+.bs-callout-default {
+ border-left-color: #777;
+}
+.bs-callout-default h4 {
+ color: #777;
+}
+.bs-callout-primary {
+ border-left-color: #428bca;
+}
+.bs-callout-primary h4 {
+ color: #428bca;
+}
+.bs-callout-success {
+ border-left-color: #5cb85c;
+}
+.bs-callout-success h4 {
+ color: #5cb85c;
+}
+.bs-callout-danger {
+ border-left-color: #d9534f;
+}
+.bs-callout-danger h4 {
+ color: #d9534f;
+}
+.bs-callout-warning {
+ border-left-color: #f0ad4e;
+}
+.bs-callout-warning h4 {
+ color: #f0ad4e;
+}
+.bs-callout-info {
+ border-left-color: #5bc0de;
+}
+.bs-callout-info h4 {
+ color: #5bc0de;
+}
+
+
+.gi-2x{font-size: 2em;}
+.gi-3x{font-size: 3em;}
+.gi-4x{font-size: 4em;}
+.gi-5x{font-size: 5em;}
+
+
+
+
+
+.breadcrumb > .active {color: #777 !important;}
+
+/* make room for the nav bar */
+h1[id],
+h2[id],
+h3[id],
+h4[id],
+h5[id],
+h6[id],
+dt[id]{
+padding-top: 60px;
+margin-top: -40px
+}
+
+body h1 {margin-top:40px;}
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+
+.post-content ol li, .post-content ul li {
+ margin: 10px 0px;
+}
+
+.pageSummary {
+ font-size:13px;
+ display:block;
+ margin-bottom:15px;
+ padding-left:20px;
+}
+
+.post-summary {
+ margin-bottom:12px;
+}
+
+.bs-example{
+ margin: 20px;
+}
+
+.breadcrumb li {
+ color: gray;
+}
+
+table {
+ background-color: transparent;
+}
+caption {
+ padding-top: 8px;
+ padding-bottom: 8px;
+ color: #777;
+ text-align: left;
+}
+th {
+ text-align: left;
+}
+table {
+ max-width: 90%;
+ margin-bottom: 20px;
+ border: 1px solid #dedede;
+}
+
+table > thead > tr > th,
+table > tbody > tr > th,
+table > tfoot > tr > th,
+table > thead > tr > td,
+table > tbody > tr > td,
+table > tfoot > tr > td {
+ padding: 8px;
+ line-height: 1.42857143;
+ vertical-align: top;
+ border-top: 1px solid #ddd;
+}
+table > thead > tr > th {
+ vertical-align: bottom;
+ border-bottom: 2px solid #ddd;
+ text-transform: none;
+ background-color: #777;
+ color: white;
+ text-align: left;
+}
+table > caption + thead > tr:first-child > th,
+table > colgroup + thead > tr:first-child > th,
+table > thead:first-child > tr:first-child > th,
+table > caption + thead > tr:first-child > td,
+table > colgroup + thead > tr:first-child > td,
+table > thead:first-child > tr:first-child > td {
+ border-top: 0;
+}
+table > tbody + tbody {
+ b
+}
+table > tbody > tr:nth-of-type(odd) {
+ background-color: #f9f9f9;
+}
+
+table col[class*="col-"] {
+ position: static;
+ display: table-column;
+ float: none;
+}
+table td[class*="col-"],
+table th[class*="col-"] {
+ position: static;
+ display: table-cell;
+ float: none;
+}
+
+
+table td:first-child {
+ width: 150px;
+ /*font-weight:bold;*/
+}
+
+table.boldFirstColumn td:first-child {
+ font-weight: bold;
+}
+
+table tr td {
+ hyphens: auto;
+}
+
+
+p.external a {
+ text-align:right;
+ font-size:12px;
+ font-color: #0088cc;
+ display:inline;
+}
+
+#definition-box-container div a.active {
+ font-weight: bold;
+}
+p.post-meta {font-size: 80%; color: #777;}
+
+.entry-date{font-size:14px;font-size:0.875rem;line-height:1.71429;margin-bottom:0;text-transform:uppercase;}
+
+/* search area */
+#search-demo-container ul#results-container {
+ list-style: none;
+ font-size: 12px;
+ background-color: white;
+ position: absolute;
+ top: 40px; /* if you change anything about the nav, you'll prob. need to reset the top and left values here.*/
+ left: 20px;
+ z-index: -1;
+ width:223px;
+ border-left: 1px solid #dedede;
+ box-shadow: 2px 3px 2px #dedede;
+}
+
+
+ul#results-container a {
+ background-color: transparent;
+}
+
+ul#results-container a: hover {
+ color: black;
+}
+
+
+#search-demo-container a:hover {
+ color: black;
+}
+#search-input {
+ padding: .5em;
+ margin-left:20px;
+ width:20em;
+ font-size: 0.8em;
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
+ float: right;
+ margin-top:10px;
+}
+/* end search */
+
+.filter-options {
+ margin-bottom: 20px;
+}
+.filter-options button {
+ margin: 3px;
+}
+
+div#toc ul li {
+ margin: 8px 0px 8px 22px;
+ font-size: 90%;
+ list-style: square;
+}
+div#toc ul {
+ background-color: whitesmoke;
+ padding: 5px;
+ border-radius: 5px;
+ max-width: 300px;
+ color: gray;
+}
+
+div#toc ul li ul {
+ padding-left:8px;
+
+}
+
+div#toc ul li ul li::before {
+ content: "– ";
+}
+
+div#toc >ul::before {
+ content: "Table of Contents";
+ font-weight: 500;
+ color: #555;
+ text-align:center;
+ margin-left:auto;
+ margin-right:auto;
+ width:70px;
+ padding-top:20px;
+ padding-bottom:20px;
+ padding-left:10px;
+}
+
+li.dropdownActive a {
+ font-weight: bold;
+}
+
+
+.post-content a.fa-rss {
+ color: orange;
+}
+
+
+.navbar-inverse .navbar-nav > li > a {
+ background-color: transparent;
+ margin-top:10px;
+}
+
+.post-content .rssfeedLink {
+ color: #248EC2;
+}
+
+footer {
+ font-size: smaller;
+}
+
+/* FAQ page */
+#accordion .panel-heading {
+ font-size: 12px;
+}
+
+a.accordion-toggle, a.accordion-collapsed {
+ font-size: 14px;
+ text-decoration: none;
+}
+
+/* navgoco sidebar styles (customized) */
+.nav, .nav ul, .nav li {
+ list-style: none;
+}
+
+.nav ul {
+ padding: 0;
+ /*margin: 0 0 0 18px;*/
+ margin:0px;
+}
+
+.nav {
+ /* padding: 4px;*/
+ padding:0px;
+ margin: 0px;
+}
+
+.nav > li {
+ margin: 1px 0;
+}
+
+.nav > li li {
+ margin: 2px 0;
+}
+
+.nav a {
+ color: #333;
+ display: block;
+ outline: none;
+ /*-webkit-border-radius: 4px;
+ -moz-border-radius: 4px;
+ border-radius: 4px;*/
+ text-decoration: none;
+}
+
+.nav li > a > span {
+ float: right;
+ font-size: 19px;
+ font-weight: bolder;
+}
+
+
+.nav li > a > span:after {
+ content: '\25be';
+}
+.nav li.open > a > span:after {
+ content: '\25b4';
+}
+
+.nav a:hover, .nav li.active > a {
+ background-color: #8D8D8D;
+ color: #f5f5f5;
+}
+
+.nav > li.active > a {
+background-color: #347DBE;
+}
+
+.nav li a {
+ font-size: 12px;
+ line-height: 18px;
+ padding: 2px 10px;
+ background-color: #f1f1f1;
+}
+
+.nav > li > a {
+ font-size: 14px;
+ line-height: 20px;
+ padding: 4px 10px;
+}
+
+ul#mysidebar {
+ border-radius:0px;
+}
+
+.nav ul li ul li a {
+ padding-left:40px;
+}
+
+.nav li.thirdlevel > a {
+ color: #248EC2;
+ font-weight:bold;
+ padding-left:20px;
+ background-color: whitesmoke !important;
+}
+
+
+.nav ul li a {
+ background-color: #FAFAFA;
+}
+
+.nav li a {
+ padding-right:10px;
+}
+
+.nav li a:hover {
+ background-color: #8D8D8D;
+}
+
+.nav ul li a {
+ border-top:1px solid whitesmoke;
+ padding-left:10px;
+}
+/* end sidebar */
+
+.navbar-inverse .navbar-nav > .active > a, .navbar-inverse .navbar-nav > .active > a:hover, .navbar-inverse .navbar-nav > .active > a:focus {
+ border-radius:5px;
+}
+
+.navbar-inverse .navbar-nav>.open>a, .navbar-inverse .navbar-nav>.open>a:focus, .navbar-inverse .navbar-nav>.open>a:hover {
+ border-radius: 5px;
+}
+
+span.projectTitle {
+ font-family: Helvetica;
+ font-weight: bold;
+}
+
+.footer {
+ text-align: right;
+}
+
+.footerMeta {
+ background-color: whitesmoke;
+ padding: 10px;
+ max-width: 250px;
+ border-radius: 5px;
+ margin-top: 50px;
+ font-style:italic;
+ font-size:12px;
+}
+
+img.screenshotSmall {
+ max-width: 300px;
+}
+
+
+dl dt p {
+ margin-left:20px;
+}
+
+
+dl dd {
+ margin-top:10px;
+ margin-bottom:10px;
+}
+
+dl.dl-horizontal dd {
+ padding-top: 20px;
+}
+
+figcaption {
+
+ padding-bottom:12px;
+ padding-top:6px;
+ max-width: 90%;
+ margin-bottom:20px;
+ font-style: italic;
+ color: gray;
+
+}
+
+.testing {
+ color: orange;
+}
+
+.preference {
+ color: red;
+}
+
+
+table.dataTable thead {
+ background-color: #444;
+}
+table td {
+ hyphens: auto;
+}
+
+section table tr.success {
+ background-color: #dff0d8 !important;
+}
+
+table tr.info {
+ background-color: #d9edf7 !important;
+}
+
+section table tr.warning, table tr.testing, table tr.testing > td.sorting_1 {
+ background-color: #fcf8e3 !important;
+}
+section table tr.danger, table tr.preference, table tr.preference > td.sorting_1 {
+ background-color: #f2dede !important;
+}
+
+.orange {
+ color: orange;
+}
+
+table.profile thead tr th {
+ background-color: #248ec2;
+}
+
+table.request thead tr th {
+ background-color: #ED1951;
+}
+
+.audienceLabel {
+ margin: 10px;
+ float: right;
+ border:1px solid #dedede;
+ padding:7px;
+}
+
+.prefaceAudienceLabel {
+ color: gray;
+ text-align: center;
+ margin:5px;
+}
+span.myLabel {
+ padding-left:10px;
+ padding-right:10px;
+}
+
+button.cursorNorm {
+ cursor: default;
+}
+
+a.dropdown-toggle, .navbar-inverse .navbar-nav > li > a {
+ margin-left: 10px;
+}
+
+hr.faded {
+ border: 0;
+ height: 1px;
+ background-image: -webkit-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -moz-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -ms-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+ background-image: -o-linear-gradient(left, rgba(0,0,0,0), rgba(0,0,0,0.75), rgba(0,0,0,0));
+}
+
+hr.shaded {
+ height: 12px;
+ border: 0;
+ box-shadow: inset 0 6px 6px -6px rgba(0,0,0,0.5);
+ margin-top: 70px;
+ background: white;
+ width: 100%;
+ margin-bottom: 10px;
+}
+
+.fa-6x{font-size:900%;}
+.fa-7x{font-size:1100%;}
+.fa-8x{font-size:1300%;}
+.fa-9x{font-size:1500%;}
+.fa-10x{font-size:1700%;}
+
+i.border {
+ padding: 10px 20px;
+ background-color: whitesmoke;
+}
+
+a[data-toggle] {
+ color: #248EC2;
+}
+
+.summary {
+ font-size:120%;
+ color: #808080;
+ margin:20px 0px 20px 0px;
+ border-left: 5px solid #ED1951;
+ padding-left: 10px;
+
+}
+
+.summary:before {
+ content: "Summary: ";
+ font-weight: bold;
+}
+
+
+a.fa.fa-envelope-o.mailto {
+ font-weight: 600;
+}
+
+h3 {color: #ED1951; font-weight:normal; font-size:130%;}
+h4 {color: #808080; font-weight:normal; font-size:120%; font-style:italic;}
+
+.alert, .callout {
+ overflow: hidden;
+}
+
+.nav-tabs > li.active > a, .nav-tabs > li.active > a:hover, .nav-tabs > li.active > a:focus {
+ background-color: #248ec2;
+ color: white;
+}
+
+ol li ol li {list-style-type: lower-alpha;}
+ol li ul li {list-style-type: disc;}
+
+li img {clear:both; }
+
+div#toc ul li ul li {
+ list-style-type: none;
+ margin: 5px 0px 0px 0px;
+}
+
+.tab-content {
+ padding: 15px;
+ background-color: #FAFAFA;
+}
+
+span.tagTitle {font-weight: 500;}
+
+li.activeSeries {
+ font-weight: bold;
+}
+
+.seriesContext .dropdown-menu li.active {
+ font-weight: bold;
+ margin-left: 43px;
+ font-size:18px;
+}
+
+.alert-warning {
+ color: #444;
+}
+
+div.alert code, h2 code {
+ background-color: transparent !important;
+}
+/* without this, the links in these notes aren't visible.*/
+.alert a {
+ text-decoration: underline;
+}
+
+div.tags {padding: 10px 5px;}
+
+.tabLabel {
+ font-weight: normal;
+}
+
+hr {
+ background: #999;
+ margin: 30px 0px;
+ width: 90%;
+ margin-left: auto;
+ margin-right: auto;
+}
+
+button.cursorNorm {
+ cursor: pointer;
+}
+
+h2 {
+ font-size:24px;
+ line-height:29px;
+}
+span.otherProgrammingLanguages {
+ font-style: normal;
+}
+
+a[data-toggle="tooltip"] {
+ color: #649345;
+ font-style: italic;
+ cursor: default;
+}
+
+.seriesNext, .seriesContext {
+ margin-top: 15px;
+ margin-bottom: 15px;
+}
+
+.seriescontext ol li {
+ list-style-type: upper-roman;
+}
+
+ol.series li {
+ list-style-type: decimal;
+ margin-left: 40px;
+ padding-left: 0px;
+}
+
+.siteTagline {
+ font-size: 200%;
+ font-weight: bold;
+ color: silver;
+ font-family: monospace;
+ text-align: center;
+ line-height: 10px;
+ margin: 20px 0px;
+ display: block;
+}
+
+.versionTagline {
+ text-align: center;
+ margin-bottom: 20px;
+ font-family: courier;
+ font-color: silver;
+ color: #444;
+ display:block;
+}
+
+/* not sure if using this ...*/
+.navbar-inverse .navbar-collapse, .navbar-inverse .navbar-form {
+ border-color: #248ec2 !important;
+}
+
+#mysidebar .nav ul {
+ background-color: #FAFAFA;
+}
+.nav ul.series li {
+ list-style: decimal;
+ font-size:12px;
+}
+
+.nav ul.series li a:hover {
+ background-color: gray;
+}
+.nav ul.series {
+ padding-left: 30px;
+}
+
+.nav ul.series {
+ background-color: #FAFAFA;
+}
+
+/*
+a.dropdown-toggle.otherProgLangs {
+ color: #f7e68f !important;
+}
+*/
+
+span.muted {color: #666;}
+
+table code {background-color: transparent;}
+
+.highlight .err {
+ color: #a61717;
+ background-color: transparent !important;
+}
+
+table p {
+ margin-top: 12px;
+ margin-bottom: 12px;
+}
+
+pre, table code {
+ white-space: pre-wrap; /* css-3 */
+ white-space: -moz-pre-wrap; /* Mozilla, since 1999 */
+ white-space: -pre-wrap; /* Opera 4-6 */
+ white-space: -o-pre-wrap; /* Opera 7 */
+ word-wrap: break-word; /* Internet Explorer 5.5+ */
+}
+
+pre {
+ margin: 25px 0px;
+}
+
+#json-box-container pre {
+ margin: 0px;
+}
+
+.video-js {
+ margin: 30px 0px;
+}
+
+video {
+ display: block;
+ margin: 30px 0px;
+ border: 1px solid #c0c0c0;
+}
+
+
+p.required, p.dataType {display: block; color: #c0c0c0; font-size: 80%; margin-left:4px;}
+
+dd {margin-left:20px;}
+
+.post-content img.inline {
+ margin:0px;
+ margin-bottom:6px;
+}
+.panel-heading {
+ font-weight: bold;
+}
+
+.note code, .alert code, .warning code, div#toc code, h2 code, h3 code, h4 code {
+ color: inherit;
+ padding: 0px;
+}
+
+.alert {
+ margin-bottom:10px;
+ margin-top:10px;
+}
+
+a.accordion-toggle {
+ font-style: normal;
+}
+
+span.red {
+ color: red;
+ font-family: Monaco, Menlo, Consolas, "Courier New", monospace;
+}
+
+h3.codeExplanation {
+ font-size:18px;
+ font-style:normal;
+ color: black;
+ line-height: 24px;
+}
+
+span.soft {
+ color: #c0c0c0;
+}
+
+.githubEditButton {
+ margin-bottom:7px;
+}
+
+.endpoint {
+ padding: 15px;
+ background-color: #f0f0f0;
+ font-family: courier;
+ font-size: 110%;
+ margin: 20px 0px;
+ color: #444;
+}
+
+.parameter {
+ font-family: courier;
+ color: red !important;
+}
+
+.formBoundary {
+ border: 1px solid gray;
+ padding: 15px;
+ margin: 15px 0px;
+ background-color: whitesmoke;
+}
+
+@media (max-width: 767px) {
+ .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
+ color: #444;
+ }
+}
+
+@media (max-width: 990px) {
+ #mysidebar {
+ position: relative;
+ }
+}
+
+@media (min-width: 1000px) {
+
+ ul#mysidebar {
+ width: 225px;
+ }
+}
+
+@media (max-width: 900px) {
+
+ ul#mysidebar {
+ max-width: 100%;
+ }
+}
+
+.col-md-9 img {
+ max-width: 100%;
+ max-height: 100%;
+}
+
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+.col-md-9 img {
+ max-width: 100%;
+ max-height: 100%;
+}
+
+
+.post-content img {
+ margin: 12px 0px 3px 0px;
+ width: auto;
+ height: auto;
+ max-width: 100%;
+ max-height: 100%;
+}
+
+.videoThumbs img {
+ float: left;
+ margin:15px 15px 15px 0px;
+ box-shadow: 2px 2px 1px #f0f0f0;
+ border: 1px solid #dedede;
+}
+
+
+@media only screen and (min-width: 900px), @media only screen and (min-device-width: 900px) {
+ .col-md-9 img {
+ max-width: 700px;
+ max-height: 700px;
+ }
+}
+
+*:hover > .anchorjs-link {
+ transition: color .25s linear;
+ text-decoration: none;
+}
+
+.kbCaption {
+ color: white;
+ background-color: #444;
+ padding:10px;
+}
+
+/* this part adds an icon after external links, using FontAwesome*/
+a[href^="http://"]:after, a[href^="https://"]:after {
+ content: "\f08e";
+ font-family: FontAwesome;
+ font-weight: normal;
+ font-style: normal;
+ display: inline-block;
+ text-decoration: none;
+ padding-left: 3px;
+}
+
+/* Strip the outbound icon when this class is present */
+a[href].noCrossRef::after,
+a.no_icon:after
+ {
+ content:"" !important;
+ padding-left: 0;
+}
+
+.btn-default {
+ margin-bottom: 10px;
+}
+
+/* algolia search */
+
+.search {
+ text-align: left;
+}
+.search input {
+ font-size: 20px;
+ width: 300px;
+}
+.results {
+ margin: auto;
+ text-align: left;
+}
+.results ul {
+ list-style-type: none;
+ padding: 0;
+}
+
+/* algolia */
+
+div.results {
+ position: absolute;
+ background-color: white;
+ width: 100%;
+}
+
+.post-meta {
+ font-size: 14px;
+ color: #828282;
+}
+
+.post-link {
+ font-size: 22px;
+}
+
+.post-list p {
+ margin: 10px 0px;
+}
+
+time {
+ margin-right: 10px;
+}
+
+p.post-meta time {
+ margin-right: 0px;
+}
+
+span.label.label-default {
+ background-color: gray;
+}
+
+span.label.label-primary {
+ background-color: #f0ad4e;
+}
+.col-lg-12 .nav li a {background-color: white}
+
+
+.nav li.active > a.subfoldersTitle {
+ background-color: whitesmoke;
+ font-weight: bold;
+ color: black;
+ }
+
+a code {
+ color: #248EC2;
+}
+
+code + a > code {
+ margin-left: -7px;
+}
+
+table th code {
+ color: white;
+}
+
+ol li ul li ol li {
+ list-style: decimal;
+}
+
+ol li ul li ol li ul li{
+ list-style: disc;
+}
+
+.post-content table th {
+ vertical-align: top;
+}
+
+table thead th code.highlighter-rouge {
+ background-color: transparent;
+}
+
+
+.box {
+ padding: 10px;
+ border: 1px solid #888;
+ box-shadow: 2px 2px 4px #dedede;
+ width: 100px;
+ height: 80px;
+ background-color: #f5f5f5;
+ font-family: Arial;
+ font-size: 12px;
+ hyphens: auto;
+ float: left;
+ font-size: 12px;
+}
+
+.box:hover {
+ background-color: #f0f0f0;
+}
+
+#userMap {
+ overflow-x: auto;
+ overflow-y: auto;
+ padding: 20px;
+ min-width: 770px;
+}
+
+#userMap .active {
+ background-color: #d6f5d6;
+ border:1px solid #555;
+ font-weight: bold;
+}
+
+h2.userMapTitle {
+ font-family: Arial;
+}
+
+#userMap a:hover {
+ text-decoration: none;
+ }
+
+div.arrow {
+ max-width: 50px;
+ margin-left: 15px;
+ margin-right: 15px;
+ font-size: 20px;
+}
+
+div.content {
+ max-width: 110px
+}
+
+#userMap div.arrow, #userMap div.content {
+ float: left;
+}
+
+.clearfix {
+ clear: both;
+}
+
+
+#userMap div.arrow {
+ position: relative;
+ top: 30px;
+}
+
+.box1 {
+ margin-left:0px;
+}
+
+button.btn.btn-default.btn-lg.modalButton1 {
+ margin-left: -20px;
+}
+
+div.box.box1 {
+ margin-left: -20px;
+}
+
+#userMap .btn-lg {
+ width: 100px;
+ height: 80px;
+
+}
+
+#userMap .complexArrow {
+ font-size: 22px;
+ margin: 0px 10px;
+}
+
+
+#userMap .btn-lg .active {
+ background-color: #d6f5d6;
+}
+
+#userMap .btn-lg {
+ white-space: pre-wrap; /* css-3 */
+ white-space: -moz-pre-wrap; /* Mozilla, since 1999 */
+ white-space: -pre-wrap; /* Opera 4-6 */
+ white-space: -o-pre-wrap; /* Opera 7 */
+ word-wrap: break-word; /* Internet Explorer 5.5+ */
+ font-size: 14px;
+ }
+
+/*
+ * Let's target IE to respect aspect ratios and sizes for img tags containing SVG files
+ *
+ * [1] IE9
+ * [2] IE10+
+ */
+/* 1 */
+.ie9 img[src$=".svg"] {
+ width: 100%;
+}
+/* 2 */
+@media screen and (-ms-high-contrast: active), (-ms-high-contrast: none) {
+ img[src$=".svg"] {
+ width: 100%;
+ }
+}
+
+h4.panel-title {
+ padding-top: 0px;
+ margin-top: 0px;
+}
\ No newline at end of file
diff --git a/docs/css/font-awesome.min.css b/docs/css/font-awesome.min.css
new file mode 100644
index 0000000..08e68ec
--- /dev/null
+++ b/docs/css/font-awesome.min.css
@@ -0,0 +1,4 @@
+/*!
+ * Font Awesome 4.2.0 by @davegandy - http://fontawesome.io - @fontawesome
+ * License - http://fontawesome.io/license (Font: SIL OFL 1.1, CSS: MIT License)
+ */@font-face{font-family:'FontAwesome';src:url('fonts/fontawesome-webfont.eot?v=4.2.0');src:url('fonts/fontawesome-webfont.eot?#iefix&v=4.2.0') format('embedded-opentype'),url('fonts/fontawesome-webfont.woff?v=4.2.0') format('woff'),url('fonts/fontawesome-webfont.ttf?v=4.2.0') format('truetype'),url('fonts/fontawesome-webfont.svg?v=4.2.0#fontawesomeregular') format('svg');font-weight:normal;font-style:normal}.fa{display:inline-block;font:normal normal normal 14px/1 FontAwesome;font-size [...]
\ No newline at end of file
diff --git a/docs/css/fonts/FontAwesome.otf b/docs/css/fonts/FontAwesome.otf
new file mode 100644
index 0000000..f7936cc
Binary files /dev/null and b/docs/css/fonts/FontAwesome.otf differ
diff --git a/docs/css/fonts/fontawesome-webfont.eot b/docs/css/fonts/fontawesome-webfont.eot
new file mode 100644
index 0000000..33b2bb8
Binary files /dev/null and b/docs/css/fonts/fontawesome-webfont.eot differ
diff --git a/docs/css/fonts/fontawesome-webfont.svg b/docs/css/fonts/fontawesome-webfont.svg
new file mode 100644
index 0000000..1ee89d4
--- /dev/null
+++ b/docs/css/fonts/fontawesome-webfont.svg
@@ -0,0 +1,565 @@
+<?xml version="1.0" standalone="no"?>
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd" >
+<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" version="1.1">
+<metadata></metadata>
+<defs>
+<font id="fontawesomeregular" horiz-adv-x="1536" >
+<font-face units-per-em="1792" ascent="1536" descent="-256" />
+<missing-glyph horiz-adv-x="448" />
+<glyph unicode=" " horiz-adv-x="448" />
+<glyph unicode="	" horiz-adv-x="448" />
+<glyph unicode=" " horiz-adv-x="448" />
+<glyph unicode="¨" horiz-adv-x="1792" />
+<glyph unicode="©" horiz-adv-x="1792" />
+<glyph unicode="®" horiz-adv-x="1792" />
+<glyph unicode="´" horiz-adv-x="1792" />
+<glyph unicode="Æ" horiz-adv-x="1792" />
+<glyph unicode="Ø" horiz-adv-x="1792" />
+<glyph unicode=" " horiz-adv-x="768" />
+<glyph unicode=" " horiz-adv-x="1537" />
+<glyph unicode=" " horiz-adv-x="768" />
+<glyph unicode=" " horiz-adv-x="1537" />
+<glyph unicode=" " horiz-adv-x="512" />
+<glyph unicode=" " horiz-adv-x="384" />
+<glyph unicode=" " horiz-adv-x="256" />
+<glyph unicode=" " horiz-adv-x="256" />
+<glyph unicode=" " horiz-adv-x="192" />
+<glyph unicode=" " horiz-adv-x="307" />
+<glyph unicode=" " horiz-adv-x="85" />
+<glyph unicode=" " horiz-adv-x="307" />
+<glyph unicode=" " horiz-adv-x="384" />
+<glyph unicode="™" horiz-adv-x="1792" />
+<glyph unicode="∞" horiz-adv-x="1792" />
+<glyph unicode="≠" horiz-adv-x="1792" />
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+<glyph unicode="" horiz-adv-x="1792" />
+</font>
+</defs></svg>
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diff --git a/docs/css/fonts/fontawesome-webfont.woff b/docs/css/fonts/fontawesome-webfont.woff
new file mode 100644
index 0000000..8b280b9
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diff --git a/docs/css/fonts/fontawesome-webfont.woff2 b/docs/css/fonts/fontawesome-webfont.woff2
new file mode 100644
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diff --git a/docs/css/lavish-bootstrap.css b/docs/css/lavish-bootstrap.css
new file mode 100644
index 0000000..c2af93e
--- /dev/null
+++ b/docs/css/lavish-bootstrap.css
@@ -0,0 +1,5898 @@
+/* CSS generated by http://lavishbootstrap.com */
+/*! normalize.css v2.1.0 | MIT License | git.io/normalize */
+article,
+aside,
+details,
+figcaption,
+figure,
+footer,
+header,
+hgroup,
+main,
+nav,
+section,
+summary {
+ display: block;
+}
+audio,
+canvas,
+video {
+ display: inline-block;
+}
+audio:not([controls]) {
+ display: none;
+ height: 0;
+}
+[hidden] {
+ display: none;
+}
+html {
+ font-family: sans-serif;
+ -webkit-text-size-adjust: 100%;
+ -ms-text-size-adjust: 100%;
+}
+body {
+ margin: 0;
+}
+a:focus {
+ outline: thin dotted;
+}
+a:active,
+a:hover {
+ outline: 0;
+}
+h1 {
+ font-size: 2em;
+ margin: 0.67em 0;
+}
+abbr[title] {
+ border-bottom: 1px dotted;
+}
+b,
+strong {
+ font-weight: bold;
+}
+dfn {
+ font-style: italic;
+}
+hr {
+ -moz-box-sizing: content-box;
+ box-sizing: content-box;
+ height: 0;
+}
+mark {
+ background: #ff0;
+ color: #000;
+}
+code,
+kbd,
+pre,
+samp {
+ font-family: monospace, serif;
+ font-size: 1em;
+}
+pre {
+ white-space: pre-wrap;
+}
+q {
+ quotes: "\201C" "\201D" "\2018" "\2019";
+}
+small {
+ font-size: 80%;
+}
+sub,
+sup {
+ font-size: 75%;
+ line-height: 0;
+ position: relative;
+ vertical-align: baseline;
+}
+sup {
+ top: -0.5em;
+}
+sub {
+ bottom: -0.25em;
+}
+img {
+ border: 0;
+}
+svg:not(:root) {
+ overflow: hidden;
+}
+figure {
+ margin: 0;
+}
+fieldset {
+ border: 1px solid #c0c0c0;
+ margin: 0 2px;
+ padding: 0.35em 0.625em 0.75em;
+}
+legend {
+ border: 0;
+ padding: 0;
+}
+button,
+input,
+select,
+textarea {
+ font-family: inherit;
+ font-size: 100%;
+ margin: 0;
+}
+button,
+input {
+ line-height: normal;
+}
+button,
+select {
+ text-transform: none;
+}
+button,
+html input[type="button"],
+input[type="reset"],
+input[type="submit"] {
+ -webkit-appearance: button;
+ cursor: pointer;
+}
+button[disabled],
+html input[disabled] {
+ cursor: default;
+}
+input[type="checkbox"],
+input[type="radio"] {
+ box-sizing: border-box;
+ padding: 0;
+}
+input[type="search"] {
+ -webkit-appearance: textfield;
+ -moz-box-sizing: content-box;
+ -webkit-box-sizing: content-box;
+ box-sizing: content-box;
+}
+input[type="search"]::-webkit-search-cancel-button,
+input[type="search"]::-webkit-search-decoration {
+ -webkit-appearance: none;
+}
+button::-moz-focus-inner,
+input::-moz-focus-inner {
+ border: 0;
+ padding: 0;
+}
+textarea {
+ overflow: auto;
+ vertical-align: top;
+}
+table {
+ border-collapse: collapse;
+ border-spacing: 0;
+}
+@media print {
+ * {
+ text-shadow: none !important;
+ color: #000 !important;
+ background: transparent !important;
+ box-shadow: none !important;
+ }
+ a,
+ a:visited {
+ text-decoration: underline;
+ }
+ a[href]:after {
+ content: " (" attr(href) ")";
+ }
+ abbr[title]:after {
+ content: " (" attr(title) ")";
+ }
+ .ir a:after,
+ a[href^="javascript:"]:after,
+ a[href^="#"]:after {
+ content: "";
+ }
+ pre,
+ blockquote {
+ border: 1px solid #999;
+ page-break-inside: avoid;
+ }
+ thead {
+ display: table-header-group;
+ }
+ tr,
+ img {
+ page-break-inside: avoid;
+ }
+ img {
+ max-width: 100% !important;
+ }
+ @page {
+ margin: 2cm .5cm;
+ }
+ p,
+ h2,
+ h3 {
+ orphans: 3;
+ widows: 3;
+ }
+ h2,
+ h3 {
+ page-break-after: avoid;
+ }
+ .navbar {
+ display: none;
+ }
+ .table td,
+ .table th {
+ background-color: #fff !important;
+ }
+ .btn > .caret,
+ .dropup > .btn > .caret {
+ border-top-color: #000 !important;
+ }
+ .label {
+ border: 1px solid #000;
+ }
+ .table {
+ border-collapse: collapse !important;
+ }
+ .table-bordered th,
+ .table-bordered td {
+ border: 1px solid #ddd !important;
+ }
+}
+*,
+*:before,
+*:after {
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
+}
+html {
+ font-size: 62.5%;
+ -webkit-tap-highlight-color: rgba(0, 0, 0, 0);
+}
+body {
+ font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+ font-size: 14px;
+ line-height: 1.428571429;
+ /*color: #77777a; */
+ background-color: #ffffff;
+}
+input,
+button,
+select,
+textarea {
+ font-family: inherit;
+ font-size: inherit;
+ line-height: inherit;
+}
+button,
+input,
+select[multiple],
+textarea {
+ background-image: none;
+}
+a {
+ color: #248EC2;
+ text-decoration: none;
+}
+a:hover,
+a:focus {
+ text-decoration: underline;
+}
+a:focus {
+ outline: thin dotted #333;
+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
+img {
+ vertical-align: middle;
+}
+.img-responsive {
+ display: block;
+ max-width: 100%;
+ height: auto;
+}
+.img-rounded {
+ border-radius: 6px;
+}
+.img-thumbnail {
+ padding: 4px;
+ line-height: 1.428571429;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-radius: 4px;
+ -webkit-transition: all 0.2s ease-in-out;
+ transition: all 0.2s ease-in-out;
+ display: inline-block;
+ max-width: 100%;
+ height: auto;
+}
+.img-circle {
+ border-radius: 50%;
+}
+hr {
+ margin-top: 20px;
+ margin-bottom: 20px;
+ border: 0;
+ border-top: 1px solid #bac9c2;
+}
+.sr-only {
+ position: absolute;
+ width: 1px;
+ height: 1px;
+ margin: -1px;
+ padding: 0;
+ overflow: hidden;
+ clip: rect(0 0 0 0);
+ border: 0;
+}
+p {
+ margin: 0 0 10px;
+}
+.lead {
+ margin-bottom: 20px;
+ font-size: 16.099999999999998px;
+ font-weight: 200;
+ line-height: 1.4;
+}
+@media (min-width: 768px) {
+ .lead {
+ font-size: 21px;
+ }
+}
+small {
+ font-size: 85%;
+}
+cite {
+ font-style: normal;
+}
+.text-muted {
+ color: #f9faf9;
+}
+.text-primary {
+ color: #74ab50;
+}
+.text-warning {
+ color: #c09853;
+}
+.text-danger {
+ color: #b94a48;
+}
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+ color: #468847;
+}
+.text-info {
+ color: #3a87ad;
+}
+.text-left {
+ text-align: left;
+}
+.text-right {
+ text-align: right;
+}
+.text-center {
+ text-align: center;
+}
+h1,
+h2,
+h3,
+h4,
+h5,
+h6,
+.h1,
+.h2,
+.h3,
+.h4,
+.h5,
+.h6 {
+ font-family: "Helvetica Neue", Helvetica, Arial, sans-serif;
+ font-weight: 500;
+ line-height: 1.1;
+}
+h1 small,
+h2 small,
+h3 small,
+h4 small,
+h5 small,
+h6 small,
+.h1 small,
+.h2 small,
+.h3 small,
+.h4 small,
+.h5 small,
+.h6 small {
+ font-weight: normal;
+ line-height: 1;
+ color: #f9faf9;
+}
+h1,
+h2,
+h3 {
+ margin-top: 20px;
+ margin-bottom: 10px;
+}
+h4,
+h5,
+h6 {
+ margin-top: 10px;
+ margin-bottom: 10px;
+}
+h1,
+.h1 {
+ font-size: 36px;
+}
+h2,
+.h2 {
+ font-size: 30px;
+}
+h3,
+.h3 {
+ font-size: 24px;
+}
+h4,
+.h4 {
+ font-size: 18px;
+}
+h5,
+.h5 {
+ font-size: 14px;
+}
+h6,
+.h6 {
+ font-size: 12px;
+}
+h1 small,
+.h1 small {
+ font-size: 24px;
+}
+h2 small,
+.h2 small {
+ font-size: 18px;
+}
+h3 small,
+.h3 small,
+h4 small,
+.h4 small {
+ font-size: 14px;
+}
+.page-header {
+ padding-bottom: 9px;
+ margin: 40px 0 20px;
+ border-bottom: 1px solid #bac9c2;
+}
+ul,
+ol {
+ margin-top: 0;
+ margin-bottom: 10px;
+}
+ul ul,
+ol ul,
+ul ol,
+ol ol {
+ margin-bottom: 0;
+}
+.list-unstyled {
+ padding-left: 0;
+ list-style: none;
+}
+.list-inline {
+ padding-left: 0;
+ list-style: none;
+}
+.list-inline > li {
+ display: inline-block;
+ padding-left: 5px;
+ padding-right: 5px;
+}
+dl {
+ margin-bottom: 20px;
+}
+dt,
+dd {
+ line-height: 1.428571429;
+}
+dt {
+ font-weight: bold;
+}
+dd {
+ margin-left: 0;
+}
+@media (min-width: 768px) {
+ .dl-horizontal dt {
+ float: left;
+ width: 160px;
+ clear: left;
+ text-align: right;
+ overflow: hidden;
+ text-overflow: ellipsis;
+ white-space: nowrap;
+ }
+ .dl-horizontal dd {
+ margin-left: 180px;
+ }
+ .dl-horizontal dd:before,
+ .dl-horizontal dd:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+ }
+ .dl-horizontal dd:after {
+ clear: both;
+ }
+ .dl-horizontal dd:before,
+ .dl-horizontal dd:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+ }
+ .dl-horizontal dd:after {
+ clear: both;
+ }
+}
+abbr[title],
+abbr[data-original-title] {
+ cursor: help;
+ border-bottom: 1px dotted #f9faf9;
+}
+abbr.initialism {
+ font-size: 90%;
+ text-transform: uppercase;
+}
+blockquote {
+ padding: 10px 20px;
+ margin: 0 0 20px;
+ border-left: 5px solid #bac9c2;
+}
+blockquote p {
+ font-size: 17.5px;
+ font-weight: 300;
+ line-height: 1.25;
+}
+blockquote p:last-child {
+ margin-bottom: 0;
+}
+blockquote small {
+ display: block;
+ line-height: 1.428571429;
+ color: #f9faf9;
+}
+blockquote small:before {
+ content: '\2014 \00A0';
+}
+blockquote.pull-right {
+ padding-right: 15px;
+ padding-left: 0;
+ border-right: 5px solid #bac9c2;
+ border-left: 0;
+}
+blockquote.pull-right p,
+blockquote.pull-right small {
+ text-align: right;
+}
+blockquote.pull-right small:before {
+ content: '';
+}
+blockquote.pull-right small:after {
+ content: '\00A0 \2014';
+}
+q:before,
+q:after,
+blockquote:before,
+blockquote:after {
+ content: "";
+}
+address {
+ display: block;
+ margin-bottom: 20px;
+ font-style: normal;
+ line-height: 1.428571429;
+}
+code,
+pre {
+ font-family: Monaco, Menlo, Consolas, "Courier New", monospace;
+}
+code {
+ padding: 2px 4px;
+ font-size: 90%;
+ color: #444;
+ background-color: #f0f0f0;
+ white-space: nowrap;
+ border-radius: 4px;
+}
+
+pre {
+ display: block;
+ padding: 9.5px;
+ margin: 0 0 10px;
+ font-size: 13px;
+ line-height: 1.428571429;
+ word-break: break-all;
+ word-wrap: break-word;
+ color: #77777a;
+ background-color: #f5f5f5;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+}
+pre.prettyprint {
+ margin-bottom: 20px;
+}
+pre code {
+ padding: 0;
+ font-size: inherit;
+ color: inherit;
+ white-space: pre-wrap;
+ background-color: transparent;
+ border: 0;
+}
+.pre-scrollable {
+ max-height: 340px;
+ overflow-y: scroll;
+}
+.container {
+ margin-right: auto;
+ margin-left: auto;
+ padding-left: 15px;
+ padding-right: 15px;
+}
+.container:before,
+.container:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.container:after {
+ clear: both;
+}
+.container:before,
+.container:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.container:after {
+ clear: both;
+}
+.row {
+ margin-left: -15px;
+ margin-right: -15px;
+}
+.row:before,
+.row:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.row:after {
+ clear: both;
+}
+.row:before,
+.row:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.row:after {
+ clear: both;
+}
+.col-xs-1,
+.col-xs-2,
+.col-xs-3,
+.col-xs-4,
+.col-xs-5,
+.col-xs-6,
+.col-xs-7,
+.col-xs-8,
+.col-xs-9,
+.col-xs-10,
+.col-xs-11,
+.col-xs-12,
+.col-sm-1,
+.col-sm-2,
+.col-sm-3,
+.col-sm-4,
+.col-sm-5,
+.col-sm-6,
+.col-sm-7,
+.col-sm-8,
+.col-sm-9,
+.col-sm-10,
+.col-sm-11,
+.col-sm-12,
+.col-md-1,
+.col-md-2,
+.col-md-3,
+.col-md-4,
+.col-md-5,
+.col-md-6,
+.col-md-7,
+.col-md-8,
+.col-md-9,
+.col-md-10,
+.col-md-11,
+.col-md-12,
+.col-lg-1,
+.col-lg-2,
+.col-lg-3,
+.col-lg-4,
+.col-lg-5,
+.col-lg-6,
+.col-lg-7,
+.col-lg-8,
+.col-lg-9,
+.col-lg-10,
+.col-lg-11,
+.col-lg-12 {
+ position: relative;
+ min-height: 1px;
+ padding-left: 15px;
+ padding-right: 15px;
+}
+.col-xs-1,
+.col-xs-2,
+.col-xs-3,
+.col-xs-4,
+.col-xs-5,
+.col-xs-6,
+.col-xs-7,
+.col-xs-8,
+.col-xs-9,
+.col-xs-10,
+.col-xs-11 {
+ float: left;
+}
+.col-xs-1 {
+ width: 8.333333333333332%;
+}
+.col-xs-2 {
+ width: 16.666666666666664%;
+}
+.col-xs-3 {
+ width: 25%;
+}
+.col-xs-4 {
+ width: 33.33333333333333%;
+}
+.col-xs-5 {
+ width: 41.66666666666667%;
+}
+.col-xs-6 {
+ width: 50%;
+}
+.col-xs-7 {
+ width: 58.333333333333336%;
+}
+.col-xs-8 {
+ width: 66.66666666666666%;
+}
+.col-xs-9 {
+ width: 75%;
+}
+.col-xs-10 {
+ width: 83.33333333333334%;
+}
+.col-xs-11 {
+ width: 91.66666666666666%;
+}
+.col-xs-12 {
+ width: 100%;
+}
+@media (min-width: 768px) {
+ .container {
+ max-width: 750px;
+ }
+ .col-sm-1,
+ .col-sm-2,
+ .col-sm-3,
+ .col-sm-4,
+ .col-sm-5,
+ .col-sm-6,
+ .col-sm-7,
+ .col-sm-8,
+ .col-sm-9,
+ .col-sm-10,
+ .col-sm-11 {
+ float: left;
+ }
+ .col-sm-1 {
+ width: 8.333333333333332%;
+ }
+ .col-sm-2 {
+ width: 16.666666666666664%;
+ }
+ .col-sm-3 {
+ width: 25%;
+ }
+ .col-sm-4 {
+ width: 33.33333333333333%;
+ }
+ .col-sm-5 {
+ width: 41.66666666666667%;
+ }
+ .col-sm-6 {
+ width: 50%;
+ }
+ .col-sm-7 {
+ width: 58.333333333333336%;
+ }
+ .col-sm-8 {
+ width: 66.66666666666666%;
+ }
+ .col-sm-9 {
+ width: 75%;
+ }
+ .col-sm-10 {
+ width: 83.33333333333334%;
+ }
+ .col-sm-11 {
+ width: 91.66666666666666%;
+ }
+ .col-sm-12 {
+ width: 100%;
+ }
+ .col-sm-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-sm-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-sm-push-3 {
+ left: 25%;
+ }
+ .col-sm-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-sm-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-sm-push-6 {
+ left: 50%;
+ }
+ .col-sm-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-sm-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-sm-push-9 {
+ left: 75%;
+ }
+ .col-sm-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-sm-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-sm-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-sm-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-sm-pull-3 {
+ right: 25%;
+ }
+ .col-sm-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-sm-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-sm-pull-6 {
+ right: 50%;
+ }
+ .col-sm-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-sm-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-sm-pull-9 {
+ right: 75%;
+ }
+ .col-sm-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-sm-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-sm-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-sm-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-sm-offset-3 {
+ margin-left: 25%;
+ }
+ .col-sm-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-sm-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-sm-offset-6 {
+ margin-left: 50%;
+ }
+ .col-sm-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-sm-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-sm-offset-9 {
+ margin-left: 75%;
+ }
+ .col-sm-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-sm-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+@media (min-width: 992px) {
+ .container {
+ max-width: 970px;
+ }
+ .col-md-1,
+ .col-md-2,
+ .col-md-3,
+ .col-md-4,
+ .col-md-5,
+ .col-md-6,
+ .col-md-7,
+ .col-md-8,
+ .col-md-9,
+ .col-md-10,
+ .col-md-11 {
+ float: left;
+ }
+ .col-md-1 {
+ width: 8.333333333333332%;
+ }
+ .col-md-2 {
+ width: 16.666666666666664%;
+ }
+ .col-md-3 {
+ width: 25%;
+ }
+ .col-md-4 {
+ width: 33.33333333333333%;
+ }
+ .col-md-5 {
+ width: 41.66666666666667%;
+ }
+ .col-md-6 {
+ width: 50%;
+ }
+ .col-md-7 {
+ width: 58.333333333333336%;
+ }
+ .col-md-8 {
+ width: 66.66666666666666%;
+ }
+ .col-md-9 {
+ width: 75%;
+ }
+ .col-md-10 {
+ width: 83.33333333333334%;
+ }
+ .col-md-11 {
+ width: 91.66666666666666%;
+ }
+ .col-md-12 {
+ width: 100%;
+ }
+ .col-md-push-0 {
+ left: auto;
+ }
+ .col-md-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-md-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-md-push-3 {
+ left: 25%;
+ }
+ .col-md-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-md-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-md-push-6 {
+ left: 50%;
+ }
+ .col-md-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-md-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-md-push-9 {
+ left: 75%;
+ }
+ .col-md-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-md-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-md-pull-0 {
+ right: auto;
+ }
+ .col-md-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-md-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-md-pull-3 {
+ right: 25%;
+ }
+ .col-md-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-md-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-md-pull-6 {
+ right: 50%;
+ }
+ .col-md-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-md-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-md-pull-9 {
+ right: 75%;
+ }
+ .col-md-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-md-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-md-offset-0 {
+ margin-left: 0;
+ }
+ .col-md-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-md-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-md-offset-3 {
+ margin-left: 25%;
+ }
+ .col-md-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-md-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-md-offset-6 {
+ margin-left: 50%;
+ }
+ .col-md-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-md-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-md-offset-9 {
+ margin-left: 75%;
+ }
+ .col-md-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-md-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+@media (min-width: 1200px) {
+ .container {
+ max-width: 1170px;
+ }
+ .col-lg-1,
+ .col-lg-2,
+ .col-lg-3,
+ .col-lg-4,
+ .col-lg-5,
+ .col-lg-6,
+ .col-lg-7,
+ .col-lg-8,
+ .col-lg-9,
+ .col-lg-10,
+ .col-lg-11 {
+ float: left;
+ }
+ .col-lg-1 {
+ width: 8.333333333333332%;
+ }
+ .col-lg-2 {
+ width: 16.666666666666664%;
+ }
+ .col-lg-3 {
+ width: 25%;
+ }
+ .col-lg-4 {
+ width: 33.33333333333333%;
+ }
+ .col-lg-5 {
+ width: 41.66666666666667%;
+ }
+ .col-lg-6 {
+ width: 50%;
+ }
+ .col-lg-7 {
+ width: 58.333333333333336%;
+ }
+ .col-lg-8 {
+ width: 66.66666666666666%;
+ }
+ .col-lg-9 {
+ width: 75%;
+ }
+ .col-lg-10 {
+ width: 83.33333333333334%;
+ }
+ .col-lg-11 {
+ width: 91.66666666666666%;
+ }
+ .col-lg-12 {
+ width: 100%;
+ }
+ .col-lg-push-0 {
+ left: auto;
+ }
+ .col-lg-push-1 {
+ left: 8.333333333333332%;
+ }
+ .col-lg-push-2 {
+ left: 16.666666666666664%;
+ }
+ .col-lg-push-3 {
+ left: 25%;
+ }
+ .col-lg-push-4 {
+ left: 33.33333333333333%;
+ }
+ .col-lg-push-5 {
+ left: 41.66666666666667%;
+ }
+ .col-lg-push-6 {
+ left: 50%;
+ }
+ .col-lg-push-7 {
+ left: 58.333333333333336%;
+ }
+ .col-lg-push-8 {
+ left: 66.66666666666666%;
+ }
+ .col-lg-push-9 {
+ left: 75%;
+ }
+ .col-lg-push-10 {
+ left: 83.33333333333334%;
+ }
+ .col-lg-push-11 {
+ left: 91.66666666666666%;
+ }
+ .col-lg-pull-0 {
+ right: auto;
+ }
+ .col-lg-pull-1 {
+ right: 8.333333333333332%;
+ }
+ .col-lg-pull-2 {
+ right: 16.666666666666664%;
+ }
+ .col-lg-pull-3 {
+ right: 25%;
+ }
+ .col-lg-pull-4 {
+ right: 33.33333333333333%;
+ }
+ .col-lg-pull-5 {
+ right: 41.66666666666667%;
+ }
+ .col-lg-pull-6 {
+ right: 50%;
+ }
+ .col-lg-pull-7 {
+ right: 58.333333333333336%;
+ }
+ .col-lg-pull-8 {
+ right: 66.66666666666666%;
+ }
+ .col-lg-pull-9 {
+ right: 75%;
+ }
+ .col-lg-pull-10 {
+ right: 83.33333333333334%;
+ }
+ .col-lg-pull-11 {
+ right: 91.66666666666666%;
+ }
+ .col-lg-offset-0 {
+ margin-left: 0;
+ }
+ .col-lg-offset-1 {
+ margin-left: 8.333333333333332%;
+ }
+ .col-lg-offset-2 {
+ margin-left: 16.666666666666664%;
+ }
+ .col-lg-offset-3 {
+ margin-left: 25%;
+ }
+ .col-lg-offset-4 {
+ margin-left: 33.33333333333333%;
+ }
+ .col-lg-offset-5 {
+ margin-left: 41.66666666666667%;
+ }
+ .col-lg-offset-6 {
+ margin-left: 50%;
+ }
+ .col-lg-offset-7 {
+ margin-left: 58.333333333333336%;
+ }
+ .col-lg-offset-8 {
+ margin-left: 66.66666666666666%;
+ }
+ .col-lg-offset-9 {
+ margin-left: 75%;
+ }
+ .col-lg-offset-10 {
+ margin-left: 83.33333333333334%;
+ }
+ .col-lg-offset-11 {
+ margin-left: 91.66666666666666%;
+ }
+}
+table {
+ max-width: 100%;
+ background-color: transparent;
+}
+th {
+ text-align: left;
+}
+.table {
+ width: 100%;
+ margin-bottom: 20px;
+}
+.table thead > tr > th,
+.table tbody > tr > th,
+.table tfoot > tr > th,
+.table thead > tr > td,
+.table tbody > tr > td,
+.table tfoot > tr > td {
+ padding: 8px;
+ line-height: 1.428571429;
+ vertical-align: top;
+ border-top: 1px solid #77777a;
+}
+.table thead > tr > th {
+ vertical-align: bottom;
+ border-bottom: 2px solid #77777a;
+}
+.table caption + thead tr:first-child th,
+.table colgroup + thead tr:first-child th,
+.table thead:first-child tr:first-child th,
+.table caption + thead tr:first-child td,
+.table colgroup + thead tr:first-child td,
+.table thead:first-child tr:first-child td {
+ border-top: 0;
+}
+.table tbody + tbody {
+ border-top: 2px solid #77777a;
+}
+.table .table {
+ background-color: #ffffff;
+}
+.table-condensed thead > tr > th,
+.table-condensed tbody > tr > th,
+.table-condensed tfoot > tr > th,
+.table-condensed thead > tr > td,
+.table-condensed tbody > tr > td,
+.table-condensed tfoot > tr > td {
+ padding: 5px;
+}
+.table-bordered {
+ border: 1px solid #77777a;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > tbody > tr > th,
+.table-bordered > tfoot > tr > th,
+.table-bordered > thead > tr > td,
+.table-bordered > tbody > tr > td,
+.table-bordered > tfoot > tr > td {
+ border: 1px solid #77777a;
+}
+.table-bordered > thead > tr > th,
+.table-bordered > thead > tr > td {
+ border-bottom-width: 2px;
+}
+.table-striped > tbody > tr:nth-child(odd) > td,
+.table-striped > tbody > tr:nth-child(odd) > th {
+ background-color: #f9f9f9;
+}
+.table-hover > tbody > tr:hover > td,
+.table-hover > tbody > tr:hover > th {
+ background-color: #f5f5f5;
+}
+table col[class*="col-"] {
+ float: none;
+ display: table-column;
+}
+table td[class*="col-"],
+table th[class*="col-"] {
+ float: none;
+ display: table-cell;
+}
+.table > thead > tr > td.active,
+.table > tbody > tr > td.active,
+.table > tfoot > tr > td.active,
+.table > thead > tr > th.active,
+.table > tbody > tr > th.active,
+.table > tfoot > tr > th.active,
+.table > thead > tr.active > td,
+.table > tbody > tr.active > td,
+.table > tfoot > tr.active > td,
+.table > thead > tr.active > th,
+.table > tbody > tr.active > th,
+.table > tfoot > tr.active > th {
+ background-color: #f5f5f5;
+}
+.table > thead > tr > td.success,
+.table > tbody > tr > td.success,
+.table > tfoot > tr > td.success,
+.table > thead > tr > th.success,
+.table > tbody > tr > th.success,
+.table > tfoot > tr > th.success,
+.table > thead > tr.success > td,
+.table > tbody > tr.success > td,
+.table > tfoot > tr.success > td,
+.table > thead > tr.success > th,
+.table > tbody > tr.success > th,
+.table > tfoot > tr.success > th {
+ background-color: #dff0d8;
+ border-color: #d6e9c6;
+}
+.table-hover > tbody > tr > td.success:hover,
+.table-hover > tbody > tr > th.success:hover,
+.table-hover > tbody > tr.success:hover > td {
+ background-color: #d0e9c6;
+ border-color: #c9e2b3;
+}
+.table > thead > tr > td.danger,
+.table > tbody > tr > td.danger,
+.table > tfoot > tr > td.danger,
+.table > thead > tr > th.danger,
+.table > tbody > tr > th.danger,
+.table > tfoot > tr > th.danger,
+.table > thead > tr.danger > td,
+.table > tbody > tr.danger > td,
+.table > tfoot > tr.danger > td,
+.table > thead > tr.danger > th,
+.table > tbody > tr.danger > th,
+.table > tfoot > tr.danger > th {
+ background-color: #f2dede;
+ border-color: #eed3d7;
+}
+.table-hover > tbody > tr > td.danger:hover,
+.table-hover > tbody > tr > th.danger:hover,
+.table-hover > tbody > tr.danger:hover > td {
+ background-color: #ebcccc;
+ border-color: #e6c1c7;
+}
+.table > thead > tr > td.warning,
+.table > tbody > tr > td.warning,
+.table > tfoot > tr > td.warning,
+.table > thead > tr > th.warning,
+.table > tbody > tr > th.warning,
+.table > tfoot > tr > th.warning,
+.table > thead > tr.warning > td,
+.table > tbody > tr.warning > td,
+.table > tfoot > tr.warning > td,
+.table > thead > tr.warning > th,
+.table > tbody > tr.warning > th,
+.table > tfoot > tr.warning > th {
+ background-color: #fcf8e3;
+ border-color: #fbeed5;
+}
+.table-hover > tbody > tr > td.warning:hover,
+.table-hover > tbody > tr > th.warning:hover,
+.table-hover > tbody > tr.warning:hover > td {
+ background-color: #faf2cc;
+ border-color: #f8e5be;
+}
+@media (max-width: 768px) {
+ .table-responsive {
+ width: 100%;
+ margin-bottom: 15px;
+ overflow-y: hidden;
+ overflow-x: scroll;
+ border: 1px solid #77777a;
+ }
+ .table-responsive > .table {
+ margin-bottom: 0;
+ background-color: #fff;
+ }
+ .table-responsive > .table > thead > tr > th,
+ .table-responsive > .table > tbody > tr > th,
+ .table-responsive > .table > tfoot > tr > th,
+ .table-responsive > .table > thead > tr > td,
+ .table-responsive > .table > tbody > tr > td,
+ .table-responsive > .table > tfoot > tr > td {
+ white-space: nowrap;
+ }
+ .table-responsive > .table-bordered {
+ border: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr > th:first-child,
+ .table-responsive > .table-bordered > tbody > tr > th:first-child,
+ .table-responsive > .table-bordered > tfoot > tr > th:first-child,
+ .table-responsive > .table-bordered > thead > tr > td:first-child,
+ .table-responsive > .table-bordered > tbody > tr > td:first-child,
+ .table-responsive > .table-bordered > tfoot > tr > td:first-child {
+ border-left: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr > th:last-child,
+ .table-responsive > .table-bordered > tbody > tr > th:last-child,
+ .table-responsive > .table-bordered > tfoot > tr > th:last-child,
+ .table-responsive > .table-bordered > thead > tr > td:last-child,
+ .table-responsive > .table-bordered > tbody > tr > td:last-child,
+ .table-responsive > .table-bordered > tfoot > tr > td:last-child {
+ border-right: 0;
+ }
+ .table-responsive > .table-bordered > thead > tr:last-child > th,
+ .table-responsive > .table-bordered > tbody > tr:last-child > th,
+ .table-responsive > .table-bordered > tfoot > tr:last-child > th,
+ .table-responsive > .table-bordered > thead > tr:last-child > td,
+ .table-responsive > .table-bordered > tbody > tr:last-child > td,
+ .table-responsive > .table-bordered > tfoot > tr:last-child > td {
+ border-bottom: 0;
+ }
+}
+fieldset {
+ padding: 0;
+ margin: 0;
+ border: 0;
+}
+legend {
+ display: block;
+ width: 100%;
+ padding: 0;
+ margin-bottom: 20px;
+ font-size: 21px;
+ line-height: inherit;
+ color: #77777a;
+ border: 0;
+ border-bottom: 1px solid #e5e5e5;
+}
+label {
+ display: inline-block;
+ margin-bottom: 5px;
+ font-weight: bold;
+}
+input[type="search"] {
+ -webkit-box-sizing: border-box;
+ -moz-box-sizing: border-box;
+ box-sizing: border-box;
+}
+input[type="radio"],
+input[type="checkbox"] {
+ margin: 4px 0 0;
+ margin-top: 1px \9;
+ /* IE8-9 */
+
+ line-height: normal;
+}
+input[type="file"] {
+ display: block;
+}
+select[multiple],
+select[size] {
+ height: auto;
+}
+select optgroup {
+ font-size: inherit;
+ font-style: inherit;
+ font-family: inherit;
+}
+input[type="file"]:focus,
+input[type="radio"]:focus,
+input[type="checkbox"]:focus {
+ outline: thin dotted #333;
+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
+input[type="number"]::-webkit-outer-spin-button,
+input[type="number"]::-webkit-inner-spin-button {
+ height: auto;
+}
+.form-control:-moz-placeholder {
+ color: #f9faf9;
+}
+.form-control::-moz-placeholder {
+ color: #f9faf9;
+}
+.form-control:-ms-input-placeholder {
+ color: #f9faf9;
+}
+.form-control::-webkit-input-placeholder {
+ color: #f9faf9;
+}
+.form-control {
+ display: block;
+ width: 100%;
+ height: 34px;
+ padding: 6px 12px;
+ font-size: 14px;
+ line-height: 1.428571429;
+ color: #4aadd6;
+ vertical-align: middle;
+ background-color: #ffffff;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ -webkit-transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+ transition: border-color ease-in-out .15s, box-shadow ease-in-out .15s;
+}
+.form-control:focus {
+ border-color: #66afe9;
+ outline: 0;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+ box-shadow: inset 0 1px 1px rgba(0,0,0,.075), 0 0 8px rgba(102, 175, 233, 0.6);
+}
+.form-control[disabled],
+.form-control[readonly],
+fieldset[disabled] .form-control {
+ cursor: not-allowed;
+ background-color: #bac9c2;
+}
+textarea.form-control {
+ height: auto;
+}
+.form-group {
+ margin-bottom: 15px;
+}
+.radio,
+.checkbox {
+ display: block;
+ min-height: 20px;
+ margin-top: 10px;
+ margin-bottom: 10px;
+ padding-left: 20px;
+ vertical-align: middle;
+}
+.radio label,
+.checkbox label {
+ display: inline;
+ margin-bottom: 0;
+ font-weight: normal;
+ cursor: pointer;
+}
+.radio input[type="radio"],
+.radio-inline input[type="radio"],
+.checkbox input[type="checkbox"],
+.checkbox-inline input[type="checkbox"] {
+ float: left;
+ margin-left: -20px;
+}
+.radio + .radio,
+.checkbox + .checkbox {
+ margin-top: -5px;
+}
+.radio-inline,
+.checkbox-inline {
+ display: inline-block;
+ padding-left: 20px;
+ margin-bottom: 0;
+ vertical-align: middle;
+ font-weight: normal;
+ cursor: pointer;
+}
+.radio-inline + .radio-inline,
+.checkbox-inline + .checkbox-inline {
+ margin-top: 0;
+ margin-left: 10px;
+}
+input[type="radio"][disabled],
+input[type="checkbox"][disabled],
+.radio[disabled],
+.radio-inline[disabled],
+.checkbox[disabled],
+.checkbox-inline[disabled],
+fieldset[disabled] input[type="radio"],
+fieldset[disabled] input[type="checkbox"],
+fieldset[disabled] .radio,
+fieldset[disabled] .radio-inline,
+fieldset[disabled] .checkbox,
+fieldset[disabled] .checkbox-inline {
+ cursor: not-allowed;
+}
+.input-sm {
+ height: 30px;
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+select.input-sm {
+ height: 30px;
+ line-height: 30px;
+}
+textarea.input-sm {
+ height: auto;
+}
+.input-lg {
+ height: 45px;
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+select.input-lg {
+ height: 45px;
+ line-height: 45px;
+}
+textarea.input-lg {
+ height: auto;
+}
+.has-warning .help-block,
+.has-warning .control-label {
+ color: #c09853;
+}
+.has-warning .form-control {
+ border-color: #c09853;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-warning .form-control:focus {
+ border-color: #a47e3c;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #dbc59e;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #dbc59e;
+}
+.has-warning .input-group-addon {
+ color: #c09853;
+ border-color: #c09853;
+ background-color: #fcf8e3;
+}
+.has-error .help-block,
+.has-error .control-label {
+ color: #b94a48;
+}
+.has-error .form-control {
+ border-color: #b94a48;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-error .form-control:focus {
+ border-color: #953b39;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #d59392;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #d59392;
+}
+.has-error .input-group-addon {
+ color: #b94a48;
+ border-color: #b94a48;
+ background-color: #f2dede;
+}
+.has-success .help-block,
+.has-success .control-label {
+ color: #468847;
+}
+.has-success .form-control {
+ border-color: #468847;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075);
+}
+.has-success .form-control:focus {
+ border-color: #356635;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #7aba7b;
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 6px #7aba7b;
+}
+.has-success .input-group-addon {
+ color: #468847;
+ border-color: #468847;
+ background-color: #dff0d8;
+}
+.form-control-static {
+ margin-bottom: 0;
+ padding-top: 7px;
+}
+.help-block {
+ display: block;
+ margin-top: 5px;
+ margin-bottom: 10px;
+ color: #b7b7b9;
+}
+@media (min-width: 768px) {
+ .form-inline .form-group {
+ display: inline-block;
+ margin-bottom: 0;
+ vertical-align: middle;
+ }
+ .form-inline .form-control {
+ display: inline-block;
+ }
+ .form-inline .radio,
+ .form-inline .checkbox {
+ display: inline-block;
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-left: 0;
+ }
+ .form-inline .radio input[type="radio"],
+ .form-inline .checkbox input[type="checkbox"] {
+ float: none;
+ margin-left: 0;
+ }
+}
+.form-horizontal .control-label,
+.form-horizontal .radio,
+.form-horizontal .checkbox,
+.form-horizontal .radio-inline,
+.form-horizontal .checkbox-inline {
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-top: 7px;
+}
+.form-horizontal .form-group {
+ margin-left: -15px;
+ margin-right: -15px;
+}
+.form-horizontal .form-group:before,
+.form-horizontal .form-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.form-horizontal .form-group:after {
+ clear: both;
+}
+.form-horizontal .form-group:before,
+.form-horizontal .form-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.form-horizontal .form-group:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .form-horizontal .control-label {
+ text-align: right;
+ }
+}
+.btn {
+ display: inline-block;
+ padding: 6px 12px;
+ margin-bottom: 0;
+ font-size: 14px;
+ font-weight: normal;
+ line-height: 1.428571429;
+ text-align: center;
+ vertical-align: middle;
+ cursor: pointer;
+ border: 1px solid transparent;
+ border-radius: 4px;
+ white-space: nowrap;
+ -webkit-user-select: none;
+ -moz-user-select: none;
+ -ms-user-select: none;
+ -o-user-select: none;
+ user-select: none;
+}
+.btn:focus {
+ outline: thin dotted #333;
+ outline: 5px auto -webkit-focus-ring-color;
+ outline-offset: -2px;
+}
+.btn:hover,
+.btn:focus {
+ color: #333333;
+ text-decoration: none;
+}
+.btn:active,
+.btn.active {
+ outline: 0;
+ background-image: none;
+ -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+ box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn.disabled,
+.btn[disabled],
+fieldset[disabled] .btn {
+ cursor: not-allowed;
+ pointer-events: none;
+ opacity: 0.65;
+ filter: alpha(opacity=65);
+ -webkit-box-shadow: none;
+ box-shadow: none;
+}
+.btn-default {
+ color: #333333;
+ background-color: #ffffff;
+ border-color: #cccccc;
+}
+.btn-default:hover,
+.btn-default:focus,
+.btn-default:active,
+.btn-default.active,
+.open .dropdown-toggle.btn-default {
+ color: #333333;
+ background-color: #ebebeb;
+ border-color: #adadad;
+}
+.btn-default:active,
+.btn-default.active,
+.open .dropdown-toggle.btn-default {
+ background-image: none;
+}
+.btn-default.disabled,
+.btn-default[disabled],
+fieldset[disabled] .btn-default,
+.btn-default.disabled:hover,
+.btn-default[disabled]:hover,
+fieldset[disabled] .btn-default:hover,
+.btn-default.disabled:focus,
+.btn-default[disabled]:focus,
+fieldset[disabled] .btn-default:focus,
+.btn-default.disabled:active,
+.btn-default[disabled]:active,
+fieldset[disabled] .btn-default:active,
+.btn-default.disabled.active,
+.btn-default[disabled].active,
+fieldset[disabled] .btn-default.active {
+ background-color: #ffffff;
+ border-color: #cccccc;
+}
+.btn-primary {
+ color: #ffffff;
+ background-color: #74ab50;
+ border-color: #689a48;
+}
+.btn-primary:hover,
+.btn-primary:focus,
+.btn-primary:active,
+.btn-primary.active,
+.open .dropdown-toggle.btn-primary {
+ color: #ffffff;
+ background-color: #618f43;
+ border-color: #4c7034;
+}
+.btn-primary:active,
+.btn-primary.active,
+.open .dropdown-toggle.btn-primary {
+ background-image: none;
+}
+.btn-primary.disabled,
+.btn-primary[disabled],
+fieldset[disabled] .btn-primary,
+.btn-primary.disabled:hover,
+.btn-primary[disabled]:hover,
+fieldset[disabled] .btn-primary:hover,
+.btn-primary.disabled:focus,
+.btn-primary[disabled]:focus,
+fieldset[disabled] .btn-primary:focus,
+.btn-primary.disabled:active,
+.btn-primary[disabled]:active,
+fieldset[disabled] .btn-primary:active,
+.btn-primary.disabled.active,
+.btn-primary[disabled].active,
+fieldset[disabled] .btn-primary.active {
+ background-color: #74ab50;
+ border-color: #689a48;
+}
+.btn-warning {
+ color: #ffffff;
+ background-color: #f0ad4e;
+ border-color: #eea236;
+}
+.btn-warning:hover,
+.btn-warning:focus,
+.btn-warning:active,
+.btn-warning.active,
+.open .dropdown-toggle.btn-warning {
+ color: #ffffff;
+ background-color: #ed9c28;
+ border-color: #d58512;
+}
+.btn-warning:active,
+.btn-warning.active,
+.open .dropdown-toggle.btn-warning {
+ background-image: none;
+}
+.btn-warning.disabled,
+.btn-warning[disabled],
+fieldset[disabled] .btn-warning,
+.btn-warning.disabled:hover,
+.btn-warning[disabled]:hover,
+fieldset[disabled] .btn-warning:hover,
+.btn-warning.disabled:focus,
+.btn-warning[disabled]:focus,
+fieldset[disabled] .btn-warning:focus,
+.btn-warning.disabled:active,
+.btn-warning[disabled]:active,
+fieldset[disabled] .btn-warning:active,
+.btn-warning.disabled.active,
+.btn-warning[disabled].active,
+fieldset[disabled] .btn-warning.active {
+ background-color: #f0ad4e;
+ border-color: #eea236;
+}
+.btn-danger {
+ color: #ffffff;
+ background-color: #d9534f;
+ border-color: #d43f3a;
+}
+.btn-danger:hover,
+.btn-danger:focus,
+.btn-danger:active,
+.btn-danger.active,
+.open .dropdown-toggle.btn-danger {
+ color: #ffffff;
+ background-color: #d2322d;
+ border-color: #ac2925;
+}
+.btn-danger:active,
+.btn-danger.active,
+.open .dropdown-toggle.btn-danger {
+ background-image: none;
+}
+.btn-danger.disabled,
+.btn-danger[disabled],
+fieldset[disabled] .btn-danger,
+.btn-danger.disabled:hover,
+.btn-danger[disabled]:hover,
+fieldset[disabled] .btn-danger:hover,
+.btn-danger.disabled:focus,
+.btn-danger[disabled]:focus,
+fieldset[disabled] .btn-danger:focus,
+.btn-danger.disabled:active,
+.btn-danger[disabled]:active,
+fieldset[disabled] .btn-danger:active,
+.btn-danger.disabled.active,
+.btn-danger[disabled].active,
+fieldset[disabled] .btn-danger.active {
+ background-color: #d9534f;
+ border-color: #d43f3a;
+}
+.btn-success {
+ color: #ffffff;
+ background-color: #5cb85c;
+ border-color: #4cae4c;
+}
+.btn-success:hover,
+.btn-success:focus,
+.btn-success:active,
+.btn-success.active,
+.open .dropdown-toggle.btn-success {
+ color: #ffffff;
+ background-color: #47a447;
+ border-color: #398439;
+}
+.btn-success:active,
+.btn-success.active,
+.open .dropdown-toggle.btn-success {
+ background-image: none;
+}
+.btn-success.disabled,
+.btn-success[disabled],
+fieldset[disabled] .btn-success,
+.btn-success.disabled:hover,
+.btn-success[disabled]:hover,
+fieldset[disabled] .btn-success:hover,
+.btn-success.disabled:focus,
+.btn-success[disabled]:focus,
+fieldset[disabled] .btn-success:focus,
+.btn-success.disabled:active,
+.btn-success[disabled]:active,
+fieldset[disabled] .btn-success:active,
+.btn-success.disabled.active,
+.btn-success[disabled].active,
+fieldset[disabled] .btn-success.active {
+ background-color: #5cb85c;
+ border-color: #4cae4c;
+}
+.btn-info {
+ color: #ffffff;
+ background-color: #347DBE;
+ border-color: #347DBE;
+}
+.btn-info:hover,
+.btn-info:focus,
+.btn-info:active,
+.btn-info.active,
+.open .dropdown-toggle.btn-info {
+ color: #ffffff;
+ background-color: #015CAE;
+ border-color: #015CAE;
+}
+.btn-info:active,
+.btn-info.active,
+.open .dropdown-toggle.btn-info {
+ background-image: none;
+}
+.btn-info.disabled,
+.btn-info[disabled],
+fieldset[disabled] .btn-info,
+.btn-info.disabled:hover,
+.btn-info[disabled]:hover,
+fieldset[disabled] .btn-info:hover,
+.btn-info.disabled:focus,
+.btn-info[disabled]:focus,
+fieldset[disabled] .btn-info:focus,
+.btn-info.disabled:active,
+.btn-info[disabled]:active,
+fieldset[disabled] .btn-info:active,
+.btn-info.disabled.active,
+.btn-info[disabled].active,
+fieldset[disabled] .btn-info.active {
+ background-color: #5bc0de;
+ border-color: #46b8da;
+}
+.btn-link {
+ color: #74ab50;
+ font-weight: normal;
+ cursor: pointer;
+ border-radius: 0;
+}
+.btn-link,
+.btn-link:active,
+.btn-link[disabled],
+fieldset[disabled] .btn-link {
+ background-color: transparent;
+ -webkit-box-shadow: none;
+ box-shadow: none;
+}
+.btn-link,
+.btn-link:hover,
+.btn-link:focus,
+.btn-link:active {
+ border-color: transparent;
+}
+.btn-link:hover,
+.btn-link:focus {
+ color: #517738;
+ text-decoration: underline;
+ background-color: transparent;
+}
+.btn-link[disabled]:hover,
+fieldset[disabled] .btn-link:hover,
+.btn-link[disabled]:focus,
+fieldset[disabled] .btn-link:focus {
+ color: #f9faf9;
+ text-decoration: none;
+}
+.btn-lg {
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+.btn-sm,
+.btn-xs {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+.btn-xs {
+ padding: 1px 5px;
+}
+.btn-block {
+ display: block;
+ width: 100%;
+ padding-left: 0;
+ padding-right: 0;
+}
+.btn-block + .btn-block {
+ margin-top: 5px;
+}
+input[type="submit"].btn-block,
+input[type="reset"].btn-block,
+input[type="button"].btn-block {
+ width: 100%;
+}
+.fade {
+ opacity: 0;
+ -webkit-transition: opacity 0.15s linear;
+ transition: opacity 0.15s linear;
+}
+.fade.in {
+ opacity: 1;
+}
+.collapse {
+ display: none;
+}
+.collapse.in {
+ display: block;
+}
+.collapsing {
+ position: relative;
+ height: 0;
+ overflow: hidden;
+ -webkit-transition: height 0.35s ease;
+ transition: height 0.35s ease;
+}
+@font-face {
+ font-family: 'Glyphicons Halflings';
+ src: url('../fonts/glyphicons-halflings-regular.eot');
+ src: url('../fonts/glyphicons-halflings-regular.eot?#iefix') format('embedded-opentype'), url('../fonts/glyphicons-halflings-regular.woff') format('woff'), url('../fonts/glyphicons-halflings-regular.ttf') format('truetype'), url('../fonts/glyphicons-halflings-regular.svg#glyphicons-halflingsregular') format('svg');
+}
+.glyphicon {
+ position: relative;
+ top: 1px;
+ display: inline-block;
+ font-family: 'Glyphicons Halflings';
+ font-style: normal;
+ font-weight: normal;
+ line-height: 1;
+ -webkit-font-smoothing: antialiased;
+}
+.glyphicon-asterisk:before {
+ content: "\2a";
+}
+.glyphicon-plus:before {
+ content: "\2b";
+}
+.glyphicon-euro:before {
+ content: "\20ac";
+}
+.glyphicon-minus:before {
+ content: "\2212";
+}
+.glyphicon-cloud:before {
+ content: "\2601";
+}
+.glyphicon-envelope:before {
+ content: "\2709";
+}
+.glyphicon-pencil:before {
+ content: "\270f";
+}
+.glyphicon-glass:before {
+ content: "\e001";
+}
+.glyphicon-music:before {
+ content: "\e002";
+}
+.glyphicon-search:before {
+ content: "\e003";
+}
+.glyphicon-heart:before {
+ content: "\e005";
+}
+.glyphicon-star:before {
+ content: "\e006";
+}
+.glyphicon-star-empty:before {
+ content: "\e007";
+}
+.glyphicon-user:before {
+ content: "\e008";
+}
+.glyphicon-film:before {
+ content: "\e009";
+}
+.glyphicon-th-large:before {
+ content: "\e010";
+}
+.glyphicon-th:before {
+ content: "\e011";
+}
+.glyphicon-th-list:before {
+ content: "\e012";
+}
+.glyphicon-ok:before {
+ content: "\e013";
+}
+.glyphicon-remove:before {
+ content: "\e014";
+}
+.glyphicon-zoom-in:before {
+ content: "\e015";
+}
+.glyphicon-zoom-out:before {
+ content: "\e016";
+}
+.glyphicon-off:before {
+ content: "\e017";
+}
+.glyphicon-signal:before {
+ content: "\e018";
+}
+.glyphicon-cog:before {
+ content: "\e019";
+}
+.glyphicon-trash:before {
+ content: "\e020";
+}
+.glyphicon-home:before {
+ content: "\e021";
+}
+.glyphicon-file:before {
+ content: "\e022";
+}
+.glyphicon-time:before {
+ content: "\e023";
+}
+.glyphicon-road:before {
+ content: "\e024";
+}
+.glyphicon-download-alt:before {
+ content: "\e025";
+}
+.glyphicon-download:before {
+ content: "\e026";
+}
+.glyphicon-upload:before {
+ content: "\e027";
+}
+.glyphicon-inbox:before {
+ content: "\e028";
+}
+.glyphicon-play-circle:before {
+ content: "\e029";
+}
+.glyphicon-repeat:before {
+ content: "\e030";
+}
+.glyphicon-refresh:before {
+ content: "\e031";
+}
+.glyphicon-list-alt:before {
+ content: "\e032";
+}
+.glyphicon-flag:before {
+ content: "\e034";
+}
+.glyphicon-headphones:before {
+ content: "\e035";
+}
+.glyphicon-volume-off:before {
+ content: "\e036";
+}
+.glyphicon-volume-down:before {
+ content: "\e037";
+}
+.glyphicon-volume-up:before {
+ content: "\e038";
+}
+.glyphicon-qrcode:before {
+ content: "\e039";
+}
+.glyphicon-barcode:before {
+ content: "\e040";
+}
+.glyphicon-tag:before {
+ content: "\e041";
+}
+.glyphicon-tags:before {
+ content: "\e042";
+}
+.glyphicon-book:before {
+ content: "\e043";
+}
+.glyphicon-print:before {
+ content: "\e045";
+}
+.glyphicon-font:before {
+ content: "\e047";
+}
+.glyphicon-bold:before {
+ content: "\e048";
+}
+.glyphicon-italic:before {
+ content: "\e049";
+}
+.glyphicon-text-height:before {
+ content: "\e050";
+}
+.glyphicon-text-width:before {
+ content: "\e051";
+}
+.glyphicon-align-left:before {
+ content: "\e052";
+}
+.glyphicon-align-center:before {
+ content: "\e053";
+}
+.glyphicon-align-right:before {
+ content: "\e054";
+}
+.glyphicon-align-justify:before {
+ content: "\e055";
+}
+.glyphicon-list:before {
+ content: "\e056";
+}
+.glyphicon-indent-left:before {
+ content: "\e057";
+}
+.glyphicon-indent-right:before {
+ content: "\e058";
+}
+.glyphicon-facetime-video:before {
+ content: "\e059";
+}
+.glyphicon-picture:before {
+ content: "\e060";
+}
+.glyphicon-map-marker:before {
+ content: "\e062";
+}
+.glyphicon-adjust:before {
+ content: "\e063";
+}
+.glyphicon-tint:before {
+ content: "\e064";
+}
+.glyphicon-edit:before {
+ content: "\e065";
+}
+.glyphicon-share:before {
+ content: "\e066";
+}
+.glyphicon-check:before {
+ content: "\e067";
+}
+.glyphicon-move:before {
+ content: "\e068";
+}
+.glyphicon-step-backward:before {
+ content: "\e069";
+}
+.glyphicon-fast-backward:before {
+ content: "\e070";
+}
+.glyphicon-backward:before {
+ content: "\e071";
+}
+.glyphicon-play:before {
+ content: "\e072";
+}
+.glyphicon-pause:before {
+ content: "\e073";
+}
+.glyphicon-stop:before {
+ content: "\e074";
+}
+.glyphicon-forward:before {
+ content: "\e075";
+}
+.glyphicon-fast-forward:before {
+ content: "\e076";
+}
+.glyphicon-step-forward:before {
+ content: "\e077";
+}
+.glyphicon-eject:before {
+ content: "\e078";
+}
+.glyphicon-chevron-left:before {
+ content: "\e079";
+}
+.glyphicon-chevron-right:before {
+ content: "\e080";
+}
+.glyphicon-plus-sign:before {
+ content: "\e081";
+}
+.glyphicon-minus-sign:before {
+ content: "\e082";
+}
+.glyphicon-remove-sign:before {
+ content: "\e083";
+}
+.glyphicon-ok-sign:before {
+ content: "\e084";
+}
+.glyphicon-question-sign:before {
+ content: "\e085";
+}
+.glyphicon-info-sign:before {
+ content: "\e086";
+}
+.glyphicon-screenshot:before {
+ content: "\e087";
+}
+.glyphicon-remove-circle:before {
+ content: "\e088";
+}
+.glyphicon-ok-circle:before {
+ content: "\e089";
+}
+.glyphicon-ban-circle:before {
+ content: "\e090";
+}
+.glyphicon-arrow-left:before {
+ content: "\e091";
+}
+.glyphicon-arrow-right:before {
+ content: "\e092";
+}
+.glyphicon-arrow-up:before {
+ content: "\e093";
+}
+.glyphicon-arrow-down:before {
+ content: "\e094";
+}
+.glyphicon-share-alt:before {
+ content: "\e095";
+}
+.glyphicon-resize-full:before {
+ content: "\e096";
+}
+.glyphicon-resize-small:before {
+ content: "\e097";
+}
+.glyphicon-exclamation-sign:before {
+ content: "\e101";
+}
+.glyphicon-gift:before {
+ content: "\e102";
+}
+.glyphicon-leaf:before {
+ content: "\e103";
+}
+.glyphicon-eye-open:before {
+ content: "\e105";
+}
+.glyphicon-eye-close:before {
+ content: "\e106";
+}
+.glyphicon-warning-sign:before {
+ content: "\e107";
+}
+.glyphicon-plane:before {
+ content: "\e108";
+}
+.glyphicon-random:before {
+ content: "\e110";
+}
+.glyphicon-comment:before {
+ content: "\e111";
+}
+.glyphicon-magnet:before {
+ content: "\e112";
+}
+.glyphicon-chevron-up:before {
+ content: "\e113";
+}
+.glyphicon-chevron-down:before {
+ content: "\e114";
+}
+.glyphicon-retweet:before {
+ content: "\e115";
+}
+.glyphicon-shopping-cart:before {
+ content: "\e116";
+}
+.glyphicon-folder-close:before {
+ content: "\e117";
+}
+.glyphicon-folder-open:before {
+ content: "\e118";
+}
+.glyphicon-resize-vertical:before {
+ content: "\e119";
+}
+.glyphicon-resize-horizontal:before {
+ content: "\e120";
+}
+.glyphicon-hdd:before {
+ content: "\e121";
+}
+.glyphicon-bullhorn:before {
+ content: "\e122";
+}
+.glyphicon-certificate:before {
+ content: "\e124";
+}
+.glyphicon-thumbs-up:before {
+ content: "\e125";
+}
+.glyphicon-thumbs-down:before {
+ content: "\e126";
+}
+.glyphicon-hand-right:before {
+ content: "\e127";
+}
+.glyphicon-hand-left:before {
+ content: "\e128";
+}
+.glyphicon-hand-up:before {
+ content: "\e129";
+}
+.glyphicon-hand-down:before {
+ content: "\e130";
+}
+.glyphicon-circle-arrow-right:before {
+ content: "\e131";
+}
+.glyphicon-circle-arrow-left:before {
+ content: "\e132";
+}
+.glyphicon-circle-arrow-up:before {
+ content: "\e133";
+}
+.glyphicon-circle-arrow-down:before {
+ content: "\e134";
+}
+.glyphicon-globe:before {
+ content: "\e135";
+}
+.glyphicon-tasks:before {
+ content: "\e137";
+}
+.glyphicon-filter:before {
+ content: "\e138";
+}
+.glyphicon-fullscreen:before {
+ content: "\e140";
+}
+.glyphicon-dashboard:before {
+ content: "\e141";
+}
+.glyphicon-heart-empty:before {
+ content: "\e143";
+}
+.glyphicon-link:before {
+ content: "\e144";
+}
+.glyphicon-phone:before {
+ content: "\e145";
+}
+.glyphicon-usd:before {
+ content: "\e148";
+}
+.glyphicon-gbp:before {
+ content: "\e149";
+}
+.glyphicon-sort:before {
+ content: "\e150";
+}
+.glyphicon-sort-by-alphabet:before {
+ content: "\e151";
+}
+.glyphicon-sort-by-alphabet-alt:before {
+ content: "\e152";
+}
+.glyphicon-sort-by-order:before {
+ content: "\e153";
+}
+.glyphicon-sort-by-order-alt:before {
+ content: "\e154";
+}
+.glyphicon-sort-by-attributes:before {
+ content: "\e155";
+}
+.glyphicon-sort-by-attributes-alt:before {
+ content: "\e156";
+}
+.glyphicon-unchecked:before {
+ content: "\e157";
+}
+.glyphicon-expand:before {
+ content: "\e158";
+}
+.glyphicon-collapse-down:before {
+ content: "\e159";
+}
+.glyphicon-collapse-up:before {
+ content: "\e160";
+}
+.glyphicon-log-in:before {
+ content: "\e161";
+}
+.glyphicon-flash:before {
+ content: "\e162";
+}
+.glyphicon-log-out:before {
+ content: "\e163";
+}
+.glyphicon-new-window:before {
+ content: "\e164";
+}
+.glyphicon-record:before {
+ content: "\e165";
+}
+.glyphicon-save:before {
+ content: "\e166";
+}
+.glyphicon-open:before {
+ content: "\e167";
+}
+.glyphicon-saved:before {
+ content: "\e168";
+}
+.glyphicon-import:before {
+ content: "\e169";
+}
+.glyphicon-export:before {
+ content: "\e170";
+}
+.glyphicon-send:before {
+ content: "\e171";
+}
+.glyphicon-floppy-disk:before {
+ content: "\e172";
+}
+.glyphicon-floppy-saved:before {
+ content: "\e173";
+}
+.glyphicon-floppy-remove:before {
+ content: "\e174";
+}
+.glyphicon-floppy-save:before {
+ content: "\e175";
+}
+.glyphicon-floppy-open:before {
+ content: "\e176";
+}
+.glyphicon-credit-card:before {
+ content: "\e177";
+}
+.glyphicon-transfer:before {
+ content: "\e178";
+}
+.glyphicon-cutlery:before {
+ content: "\e179";
+}
+.glyphicon-header:before {
+ content: "\e180";
+}
+.glyphicon-compressed:before {
+ content: "\e181";
+}
+.glyphicon-earphone:before {
+ content: "\e182";
+}
+.glyphicon-phone-alt:before {
+ content: "\e183";
+}
+.glyphicon-tower:before {
+ content: "\e184";
+}
+.glyphicon-stats:before {
+ content: "\e185";
+}
+.glyphicon-sd-video:before {
+ content: "\e186";
+}
+.glyphicon-hd-video:before {
+ content: "\e187";
+}
+.glyphicon-subtitles:before {
+ content: "\e188";
+}
+.glyphicon-sound-stereo:before {
+ content: "\e189";
+}
+.glyphicon-sound-dolby:before {
+ content: "\e190";
+}
+.glyphicon-sound-5-1:before {
+ content: "\e191";
+}
+.glyphicon-sound-6-1:before {
+ content: "\e192";
+}
+.glyphicon-sound-7-1:before {
+ content: "\e193";
+}
+.glyphicon-copyright-mark:before {
+ content: "\e194";
+}
+.glyphicon-registration-mark:before {
+ content: "\e195";
+}
+.glyphicon-cloud-download:before {
+ content: "\e197";
+}
+.glyphicon-cloud-upload:before {
+ content: "\e198";
+}
+.glyphicon-tree-conifer:before {
+ content: "\e199";
+}
+.glyphicon-tree-deciduous:before {
+ content: "\e200";
+}
+.glyphicon-briefcase:before {
+ content: "\1f4bc";
+}
+.glyphicon-calendar:before {
+ content: "\1f4c5";
+}
+.glyphicon-pushpin:before {
+ content: "\1f4cc";
+}
+.glyphicon-paperclip:before {
+ content: "\1f4ce";
+}
+.glyphicon-camera:before {
+ content: "\1f4f7";
+}
+.glyphicon-lock:before {
+ content: "\1f512";
+}
+.glyphicon-bell:before {
+ content: "\1f514";
+}
+.glyphicon-bookmark:before {
+ content: "\1f516";
+}
+.glyphicon-fire:before {
+ content: "\1f525";
+}
+.glyphicon-wrench:before {
+ content: "\1f527";
+}
+.caret {
+ display: inline-block;
+ width: 0;
+ height: 0;
+ margin-left: 2px;
+ vertical-align: middle;
+ border-top: 4px solid #000000;
+ border-right: 4px solid transparent;
+ border-left: 4px solid transparent;
+ border-bottom: 0 dotted;
+ content: "";
+}
+.dropdown {
+ position: relative;
+}
+.dropdown-toggle:focus {
+ outline: 0;
+}
+.dropdown-menu {
+ position: absolute;
+ top: 100%;
+ left: 0;
+ z-index: 1000;
+ display: none;
+ float: left;
+ min-width: 160px;
+ padding: 5px 0;
+ margin: 2px 0 0;
+ list-style: none;
+ font-size: 14px;
+ background-color: #ffffff;
+ border: 1px solid #cccccc;
+ border: 1px solid rgba(0, 0, 0, 0.15);
+ border-radius: 4px;
+ -webkit-box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+ box-shadow: 0 6px 12px rgba(0, 0, 0, 0.175);
+ background-clip: padding-box;
+}
+.dropdown-menu.pull-right {
+ right: 0;
+ left: auto;
+}
+.dropdown-menu .divider {
+ height: 1px;
+ margin: 9px 0;
+ overflow: hidden;
+ background-color: #e5e5e5;
+}
+.dropdown-menu > li > a {
+ display: block;
+ padding: 3px 20px;
+ clear: both;
+ font-weight: normal;
+ line-height: 1.428571429;
+ color: #77777a;
+ white-space: nowrap;
+}
+.dropdown-menu > li > a:hover,
+.dropdown-menu > li > a:focus {
+ text-decoration: none;
+ color: #ffffff;
+ background-color: #679DCE;
+}
+.dropdown-menu > .active > a,
+.dropdown-menu > .active > a:hover,
+.dropdown-menu > .active > a:focus {
+ color: #ffffff;
+ text-decoration: none;
+ outline: 0;
+ background-color: #679DCE;
+}
+.dropdown-menu > .disabled > a,
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+ color: #f9faf9;
+}
+.dropdown-menu > .disabled > a:hover,
+.dropdown-menu > .disabled > a:focus {
+ text-decoration: none;
+ background-color: transparent;
+ background-image: none;
+ filter: progid:DXImageTransform.Microsoft.gradient(enabled = false);
+ cursor: not-allowed;
+}
+.open > .dropdown-menu {
+ display: block;
+}
+.open > a {
+ outline: 0;
+}
+.dropdown-header {
+ display: block;
+ padding: 3px 20px;
+ font-size: 12px;
+ line-height: 1.428571429;
+ color: #f9faf9;
+}
+.dropdown-backdrop {
+ position: fixed;
+ left: 0;
+ right: 0;
+ bottom: 0;
+ top: 0;
+ z-index: 990;
+}
+.pull-right > .dropdown-menu {
+ right: 0;
+ left: auto;
+}
+.dropup .caret,
+.navbar-fixed-bottom .dropdown .caret {
+ border-top: 0 dotted;
+ border-bottom: 4px solid #000000;
+ content: "";
+}
+.dropup .dropdown-menu,
+.navbar-fixed-bottom .dropdown .dropdown-menu {
+ top: auto;
+ bottom: 100%;
+ margin-bottom: 1px;
+}
+@media (min-width: 768px) {
+ .navbar-right .dropdown-menu {
+ right: 0;
+ left: auto;
+ }
+}
+.btn-default .caret {
+ border-top-color: #333333;
+}
+.btn-primary .caret,
+.btn-success .caret,
+.btn-warning .caret,
+.btn-danger .caret,
+.btn-info .caret {
+ border-top-color: #fff;
+}
+.dropup .btn-default .caret {
+ border-bottom-color: #333333;
+}
+.dropup .btn-primary .caret,
+.dropup .btn-success .caret,
+.dropup .btn-warning .caret,
+.dropup .btn-danger .caret,
+.dropup .btn-info .caret {
+ border-bottom-color: #fff;
+}
+.btn-group,
+.btn-group-vertical {
+ position: relative;
+ display: inline-block;
+ vertical-align: middle;
+}
+.btn-group > .btn,
+.btn-group-vertical > .btn {
+ position: relative;
+ float: left;
+}
+.btn-group > .btn:hover,
+.btn-group-vertical > .btn:hover,
+.btn-group > .btn:focus,
+.btn-group-vertical > .btn:focus,
+.btn-group > .btn:active,
+.btn-group-vertical > .btn:active,
+.btn-group > .btn.active,
+.btn-group-vertical > .btn.active {
+ z-index: 2;
+}
+.btn-group > .btn:focus,
+.btn-group-vertical > .btn:focus {
+ outline: none;
+}
+.btn-group .btn + .btn,
+.btn-group .btn + .btn-group,
+.btn-group .btn-group + .btn,
+.btn-group .btn-group + .btn-group {
+ margin-left: -1px;
+}
+.btn-toolbar:before,
+.btn-toolbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-toolbar:after {
+ clear: both;
+}
+.btn-toolbar:before,
+.btn-toolbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-toolbar:after {
+ clear: both;
+}
+.btn-toolbar .btn-group {
+ float: left;
+}
+.btn-toolbar > .btn + .btn,
+.btn-toolbar > .btn-group + .btn,
+.btn-toolbar > .btn + .btn-group,
+.btn-toolbar > .btn-group + .btn-group {
+ margin-left: 5px;
+}
+.btn-group > .btn:not(:first-child):not(:last-child):not(.dropdown-toggle) {
+ border-radius: 0;
+}
+.btn-group > .btn:first-child {
+ margin-left: 0;
+}
+.btn-group > .btn:first-child:not(:last-child):not(.dropdown-toggle) {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.btn-group > .btn:last-child:not(:first-child),
+.btn-group > .dropdown-toggle:not(:first-child) {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group > .btn-group {
+ float: left;
+}
+.btn-group > .btn-group:not(:first-child):not(:last-child) > .btn {
+ border-radius: 0;
+}
+.btn-group > .btn-group:first-child > .btn:last-child,
+.btn-group > .btn-group:first-child > .dropdown-toggle {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.btn-group > .btn-group:last-child > .btn:first-child {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group .dropdown-toggle:active,
+.btn-group.open .dropdown-toggle {
+ outline: 0;
+}
+.btn-group-xs > .btn {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+ padding: 1px 5px;
+}
+.btn-group-sm > .btn {
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+.btn-group-lg > .btn {
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+.btn-group > .btn + .dropdown-toggle {
+ padding-left: 8px;
+ padding-right: 8px;
+}
+.btn-group > .btn-lg + .dropdown-toggle {
+ padding-left: 12px;
+ padding-right: 12px;
+}
+.btn-group.open .dropdown-toggle {
+ -webkit-box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+ box-shadow: inset 0 3px 5px rgba(0, 0, 0, 0.125);
+}
+.btn .caret {
+ margin-left: 0;
+}
+.btn-lg .caret {
+ border-width: 5px 5px 0;
+ border-bottom-width: 0;
+}
+.dropup .btn-lg .caret {
+ border-width: 0 5px 5px;
+}
+.btn-group-vertical > .btn,
+.btn-group-vertical > .btn-group {
+ display: block;
+ float: none;
+ width: 100%;
+ max-width: 100%;
+}
+.btn-group-vertical > .btn-group:before,
+.btn-group-vertical > .btn-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-group-vertical > .btn-group:after {
+ clear: both;
+}
+.btn-group-vertical > .btn-group:before,
+.btn-group-vertical > .btn-group:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.btn-group-vertical > .btn-group:after {
+ clear: both;
+}
+.btn-group-vertical > .btn-group > .btn {
+ float: none;
+}
+.btn-group-vertical > .btn + .btn,
+.btn-group-vertical > .btn + .btn-group,
+.btn-group-vertical > .btn-group + .btn,
+.btn-group-vertical > .btn-group + .btn-group {
+ margin-top: -1px;
+ margin-left: 0;
+}
+.btn-group-vertical > .btn:not(:first-child):not(:last-child) {
+ border-radius: 0;
+}
+.btn-group-vertical > .btn:first-child:not(:last-child) {
+ border-top-right-radius: 4px;
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn:last-child:not(:first-child) {
+ border-bottom-left-radius: 4px;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group-vertical > .btn-group:not(:first-child):not(:last-child) > .btn {
+ border-radius: 0;
+}
+.btn-group-vertical > .btn-group:first-child > .btn:last-child,
+.btn-group-vertical > .btn-group:first-child > .dropdown-toggle {
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.btn-group-vertical > .btn-group:last-child > .btn:first-child {
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.btn-group-justified {
+ display: table;
+ width: 100%;
+ table-layout: fixed;
+ border-collapse: separate;
+}
+.btn-group-justified .btn {
+ float: none;
+ display: table-cell;
+ width: 1%;
+}
+[data-toggle="buttons"] > .btn > input[type="radio"],
+[data-toggle="buttons"] > .btn > input[type="checkbox"] {
+ display: none;
+}
+.input-group {
+ position: relative;
+ display: table;
+ border-collapse: separate;
+}
+.input-group.col {
+ float: none;
+ padding-left: 0;
+ padding-right: 0;
+}
+.input-group .form-control {
+ width: 100%;
+ margin-bottom: 0;
+}
+.input-group-lg > .form-control,
+.input-group-lg > .input-group-addon,
+.input-group-lg > .input-group-btn > .btn {
+ height: 45px;
+ padding: 10px 16px;
+ font-size: 18px;
+ line-height: 1.33;
+ border-radius: 6px;
+}
+select.input-group-lg > .form-control,
+select.input-group-lg > .input-group-addon,
+select.input-group-lg > .input-group-btn > .btn {
+ height: 45px;
+ line-height: 45px;
+}
+textarea.input-group-lg > .form-control,
+textarea.input-group-lg > .input-group-addon,
+textarea.input-group-lg > .input-group-btn > .btn {
+ height: auto;
+}
+.input-group-sm > .form-control,
+.input-group-sm > .input-group-addon,
+.input-group-sm > .input-group-btn > .btn {
+ height: 30px;
+ padding: 5px 10px;
+ font-size: 12px;
+ line-height: 1.5;
+ border-radius: 3px;
+}
+select.input-group-sm > .form-control,
+select.input-group-sm > .input-group-addon,
+select.input-group-sm > .input-group-btn > .btn {
+ height: 30px;
+ line-height: 30px;
+}
+textarea.input-group-sm > .form-control,
+textarea.input-group-sm > .input-group-addon,
+textarea.input-group-sm > .input-group-btn > .btn {
+ height: auto;
+}
+.input-group-addon,
+.input-group-btn,
+.input-group .form-control {
+ display: table-cell;
+}
+.input-group-addon:not(:first-child):not(:last-child),
+.input-group-btn:not(:first-child):not(:last-child),
+.input-group .form-control:not(:first-child):not(:last-child) {
+ border-radius: 0;
+}
+.input-group-addon,
+.input-group-btn {
+ width: 1%;
+ white-space: nowrap;
+ vertical-align: middle;
+}
+.input-group-addon {
+ padding: 6px 12px;
+ font-size: 14px;
+ font-weight: normal;
+ line-height: 1;
+ text-align: center;
+ background-color: #bac9c2;
+ border: 1px solid #cccccc;
+ border-radius: 4px;
+}
+.input-group-addon.input-sm {
+ padding: 5px 10px;
+ font-size: 12px;
+ border-radius: 3px;
+}
+.input-group-addon.input-lg {
+ padding: 10px 16px;
+ font-size: 18px;
+ border-radius: 6px;
+}
+.input-group-addon input[type="radio"],
+.input-group-addon input[type="checkbox"] {
+ margin-top: 0;
+}
+.input-group .form-control:first-child,
+.input-group-addon:first-child,
+.input-group-btn:first-child > .btn,
+.input-group-btn:first-child > .dropdown-toggle,
+.input-group-btn:last-child > .btn:not(:last-child):not(.dropdown-toggle) {
+ border-bottom-right-radius: 0;
+ border-top-right-radius: 0;
+}
+.input-group-addon:first-child {
+ border-right: 0;
+}
+.input-group .form-control:last-child,
+.input-group-addon:last-child,
+.input-group-btn:last-child > .btn,
+.input-group-btn:last-child > .dropdown-toggle,
+.input-group-btn:first-child > .btn:not(:first-child) {
+ border-bottom-left-radius: 0;
+ border-top-left-radius: 0;
+}
+.input-group-addon:last-child {
+ border-left: 0;
+}
+.input-group-btn {
+ position: relative;
+ white-space: nowrap;
+}
+.input-group-btn > .btn {
+ position: relative;
+}
+.input-group-btn > .btn + .btn {
+ margin-left: -4px;
+}
+.input-group-btn > .btn:hover,
+.input-group-btn > .btn:active {
+ z-index: 2;
+}
+.nav {
+ margin-bottom: 0;
+ padding-left: 0;
+ list-style: none;
+}
+.nav:before,
+.nav:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.nav:after {
+ clear: both;
+}
+.nav:before,
+.nav:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.nav:after {
+ clear: both;
+}
+.nav > li {
+ position: relative;
+ display: block;
+}
+.nav > li > a {
+ position: relative;
+ display: block;
+ padding: 10px 15px;
+}
+.nav > li > a:hover,
+.nav > li > a:focus {
+ text-decoration: none;
+ background-color: #bac9c2;
+}
+.nav > li.disabled > a {
+ color: #f9faf9;
+}
+.nav > li.disabled > a:hover,
+.nav > li.disabled > a:focus {
+ color: #f9faf9;
+ text-decoration: none;
+ background-color: transparent;
+ cursor: not-allowed;
+}
+.nav .open > a,
+.nav .open > a:hover,
+.nav .open > a:focus {
+ background-color: #bac9c2;
+ border-color: #74ab50;
+}
+.nav .nav-divider {
+ height: 1px;
+ margin: 9px 0;
+ overflow: hidden;
+ background-color: #e5e5e5;
+}
+.nav > li > a > img {
+ max-width: none;
+}
+.nav-tabs {
+ border-bottom: 1px solid #dddddd;
+}
+.nav-tabs > li {
+ float: left;
+ margin-bottom: -1px;
+}
+.nav-tabs > li > a {
+ margin-right: 2px;
+ line-height: 1.428571429;
+ border: 1px solid transparent;
+ border-radius: 4px 4px 0 0;
+}
+.nav-tabs > li > a:hover {
+ border-color: #bac9c2 #bac9c2 #dddddd;
+}
+.nav-tabs > li.active > a,
+.nav-tabs > li.active > a:hover,
+.nav-tabs > li.active > a:focus {
+ color: #4aadd6;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-bottom-color: transparent;
+ cursor: default;
+}
+.nav-tabs.nav-justified {
+ width: 100%;
+ border-bottom: 0;
+}
+.nav-tabs.nav-justified > li {
+ float: none;
+}
+.nav-tabs.nav-justified > li > a {
+ text-align: center;
+}
+@media (min-width: 768px) {
+ .nav-tabs.nav-justified > li {
+ display: table-cell;
+ width: 1%;
+ }
+}
+.nav-tabs.nav-justified > li > a {
+ border-bottom: 1px solid #dddddd;
+ margin-right: 0;
+}
+.nav-tabs.nav-justified > .active > a {
+ border-bottom-color: #ffffff;
+}
+.nav-pills > li {
+ float: left;
+}
+.nav-pills > li > a {
+ border-radius: 5px;
+}
+.nav-pills > li + li {
+ margin-left: 2px;
+}
+.nav-pills > li.active > a,
+.nav-pills > li.active > a:hover,
+.nav-pills > li.active > a:focus {
+ color: #ffffff;
+ background-color: #74ab50;
+}
+.nav-stacked > li {
+ float: none;
+}
+.nav-stacked > li + li {
+ margin-top: 2px;
+ margin-left: 0;
+}
+.nav-justified {
+ width: 100%;
+}
+.nav-justified > li {
+ float: none;
+}
+.nav-justified > li > a {
+ text-align: center;
+}
+@media (min-width: 768px) {
+ .nav-justified > li {
+ display: table-cell;
+ width: 1%;
+ }
+}
+.nav-tabs-justified {
+ border-bottom: 0;
+}
+.nav-tabs-justified > li > a {
+ border-bottom: 1px solid #dddddd;
+ margin-right: 0;
+}
+.nav-tabs-justified > .active > a {
+ border-bottom-color: #ffffff;
+}
+.tabbable:before,
+.tabbable:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.tabbable:after {
+ clear: both;
+}
+.tabbable:before,
+.tabbable:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.tabbable:after {
+ clear: both;
+}
+.tab-content > .tab-pane,
+.pill-content > .pill-pane {
+ display: none;
+}
+.tab-content > .active,
+.pill-content > .active {
+ display: block;
+}
+.nav .caret {
+ border-top-color: #74ab50;
+ border-bottom-color: #74ab50;
+}
+.nav a:hover .caret {
+ border-top-color: #517738;
+ border-bottom-color: #517738;
+}
+.nav-tabs .dropdown-menu {
+ margin-top: -1px;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.navbar {
+ position: relative;
+ z-index: 1000;
+ min-height: 50px;
+ margin-bottom: 20px;
+ border: 1px solid transparent;
+}
+.navbar:before,
+.navbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar:after {
+ clear: both;
+}
+.navbar:before,
+.navbar:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .navbar {
+ border-radius: 4px;
+ }
+}
+.navbar-header:before,
+.navbar-header:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-header:after {
+ clear: both;
+}
+.navbar-header:before,
+.navbar-header:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-header:after {
+ clear: both;
+}
+@media (min-width: 768px) {
+ .navbar-header {
+ float: left;
+ }
+}
+.navbar-collapse {
+ max-height: 340px;
+ overflow-x: visible;
+ padding-right: 15px;
+ padding-left: 15px;
+ border-top: 1px solid transparent;
+ box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1);
+ -webkit-overflow-scrolling: touch;
+}
+.navbar-collapse:before,
+.navbar-collapse:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-collapse:after {
+ clear: both;
+}
+.navbar-collapse:before,
+.navbar-collapse:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.navbar-collapse:after {
+ clear: both;
+}
+.navbar-collapse.in {
+ overflow-y: auto;
+}
+@media (min-width: 768px) {
+ .navbar-collapse {
+ width: auto;
+ border-top: 0;
+ box-shadow: none;
+ }
+ .navbar-collapse.collapse {
+ display: block !important;
+ height: auto !important;
+ padding-bottom: 0;
+ overflow: visible !important;
+ }
+ .navbar-collapse.in {
+ overflow-y: visible;
+ }
+ .navbar-collapse .navbar-nav.navbar-left:first-child {
+ margin-left: -15px;
+ }
+ .navbar-collapse .navbar-nav.navbar-right:last-child {
+ margin-right: -15px;
+ }
+ .navbar-collapse .navbar-text:last-child {
+ margin-right: 0;
+ }
+}
+.container > .navbar-header,
+.container > .navbar-collapse {
+ margin-right: -15px;
+ margin-left: -15px;
+}
+@media (min-width: 768px) {
+ .container > .navbar-header,
+ .container > .navbar-collapse {
+ margin-right: 0;
+ margin-left: 0;
+ }
+}
+.navbar-static-top {
+ border-width: 0 0 1px;
+}
+@media (min-width: 768px) {
+ .navbar-static-top {
+ border-radius: 0;
+ }
+}
+.navbar-fixed-top,
+.navbar-fixed-bottom {
+ position: fixed;
+ right: 0;
+ left: 0;
+ border-width: 0 0 1px;
+}
+@media (min-width: 768px) {
+ .navbar-fixed-top,
+ .navbar-fixed-bottom {
+ border-radius: 0;
+ }
+}
+.navbar-fixed-top {
+ z-index: 1030;
+ top: 0;
+}
+.navbar-fixed-bottom {
+ bottom: 0;
+ margin-bottom: 0;
+}
+.navbar-brand {
+ float: left;
+ padding: 15px 15px;
+ font-size: 18px;
+ line-height: 20px;
+}
+.navbar-brand:hover,
+.navbar-brand:focus {
+ text-decoration: none;
+}
+@media (min-width: 768px) {
+ .navbar > .container .navbar-brand {
+ margin-left: -15px;
+ }
+}
+.navbar-toggle {
+ position: relative;
+ float: right;
+ margin-right: 15px;
+ padding: 9px 10px;
+ margin-top: 8px;
+ margin-bottom: 8px;
+ background-color: transparent;
+ border: 1px solid transparent;
+ border-radius: 4px;
+}
+.navbar-toggle .icon-bar {
+ display: block;
+ width: 22px;
+ height: 2px;
+ border-radius: 1px;
+}
+.navbar-toggle .icon-bar + .icon-bar {
+ margin-top: 4px;
+}
+@media (min-width: 768px) {
+ .navbar-toggle {
+ display: none;
+ }
+}
+.navbar-nav {
+ margin: 7.5px -15px;
+}
+.navbar-nav > li > a {
+ padding-top: 10px;
+ padding-bottom: 10px;
+ line-height: 20px;
+}
+@media (max-width: 767px) {
+ .navbar-nav .open .dropdown-menu {
+ position: static;
+ float: none;
+ width: auto;
+ margin-top: 0;
+ background-color: transparent;
+ border: 0;
+ box-shadow: none;
+ }
+ .navbar-nav .open .dropdown-menu > li > a,
+ .navbar-nav .open .dropdown-menu .dropdown-header {
+ padding: 5px 15px 5px 25px;
+ }
+ .navbar-nav .open .dropdown-menu > li > a {
+ line-height: 20px;
+ }
+ .navbar-nav .open .dropdown-menu > li > a:hover,
+ .navbar-nav .open .dropdown-menu > li > a:focus {
+ background-image: none;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-nav {
+ float: left;
+ margin: 0;
+ }
+ .navbar-nav > li {
+ float: left;
+ }
+ .navbar-nav > li > a {
+ padding-top: 15px;
+ padding-bottom: 15px;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-left {
+ float: left !important;
+ }
+ .navbar-right {
+ float: right !important;
+ }
+}
+.navbar-form {
+ margin-left: -15px;
+ margin-right: -15px;
+ padding: 10px 15px;
+ border-top: 1px solid transparent;
+ border-bottom: 1px solid transparent;
+ -webkit-box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+ box-shadow: inset 0 1px 0 rgba(255, 255, 255, 0.1), 0 1px 0 rgba(255, 255, 255, 0.1);
+ margin-top: 8px;
+ margin-bottom: 8px;
+}
+@media (min-width: 768px) {
+ .navbar-form .form-group {
+ display: inline-block;
+ margin-bottom: 0;
+ vertical-align: middle;
+ }
+ .navbar-form .form-control {
+ display: inline-block;
+ }
+ .navbar-form .radio,
+ .navbar-form .checkbox {
+ display: inline-block;
+ margin-top: 0;
+ margin-bottom: 0;
+ padding-left: 0;
+ }
+ .navbar-form .radio input[type="radio"],
+ .navbar-form .checkbox input[type="checkbox"] {
+ float: none;
+ margin-left: 0;
+ }
+}
+@media (max-width: 767px) {
+ .navbar-form .form-group {
+ margin-bottom: 5px;
+ }
+}
+@media (min-width: 768px) {
+ .navbar-form {
+ width: auto;
+ border: 0;
+ margin-left: 0;
+ margin-right: 0;
+ padding-top: 0;
+ padding-bottom: 0;
+ -webkit-box-shadow: none;
+ box-shadow: none;
+ }
+}
+.navbar-nav > li > .dropdown-menu {
+ margin-top: 0;
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.navbar-fixed-bottom .navbar-nav > li > .dropdown-menu {
+ border-bottom-right-radius: 0;
+ border-bottom-left-radius: 0;
+}
+.navbar-nav.pull-right > li > .dropdown-menu,
+.navbar-nav > li > .dropdown-menu.pull-right {
+ left: auto;
+ right: 0;
+}
+.navbar-btn {
+ margin-top: 8px;
+ margin-bottom: 8px;
+}
+.navbar-text {
+ float: left;
+ margin-top: 15px;
+ margin-bottom: 15px;
+}
+@media (min-width: 768px) {
+ .navbar-text {
+ margin-left: 15px;
+ margin-right: 15px;
+ }
+}
+.navbar-default {
+ background-color: #f8f8f8;
+ border-color: #e7e7e7;
+}
+.navbar-default .navbar-brand {
+ color: #777777;
+}
+.navbar-default .navbar-brand:hover,
+.navbar-default .navbar-brand:focus {
+ color: #5e5e5e;
+ background-color: transparent;
+}
+.navbar-default .navbar-text {
+ color: #777777;
+}
+.navbar-default .navbar-nav > li > a {
+ color: #777777;
+}
+.navbar-default .navbar-nav > li > a:hover,
+.navbar-default .navbar-nav > li > a:focus {
+ color: #333333;
+ background-color: transparent;
+}
+.navbar-default .navbar-nav > .active > a,
+.navbar-default .navbar-nav > .active > a:hover,
+.navbar-default .navbar-nav > .active > a:focus {
+ color: #555555;
+ background-color: #e7e7e7;
+}
+.navbar-default .navbar-nav > .disabled > a,
+.navbar-default .navbar-nav > .disabled > a:hover,
+.navbar-default .navbar-nav > .disabled > a:focus {
+ color: #cccccc;
+ background-color: transparent;
+}
+.navbar-default .navbar-toggle {
+ border-color: #dddddd;
+}
+.navbar-default .navbar-toggle:hover,
+.navbar-default .navbar-toggle:focus {
+ background-color: #dddddd;
+}
+.navbar-default .navbar-toggle .icon-bar {
+ background-color: #cccccc;
+}
+.navbar-default .navbar-collapse,
+.navbar-default .navbar-form {
+ border-color: #e6e6e6;
+}
+.navbar-default .navbar-nav > .dropdown > a:hover .caret,
+.navbar-default .navbar-nav > .dropdown > a:focus .caret {
+ border-top-color: #333333;
+ border-bottom-color: #333333;
+}
+.navbar-default .navbar-nav > .open > a,
+.navbar-default .navbar-nav > .open > a:hover,
+.navbar-default .navbar-nav > .open > a:focus {
+ background-color: #e7e7e7;
+ color: #555555;
+}
+.navbar-default .navbar-nav > .open > a .caret,
+.navbar-default .navbar-nav > .open > a:hover .caret,
+.navbar-default .navbar-nav > .open > a:focus .caret {
+ border-top-color: #555555;
+ border-bottom-color: #555555;
+}
+.navbar-default .navbar-nav > .dropdown > a .caret {
+ border-top-color: #777777;
+ border-bottom-color: #777777;
+}
+@media (max-width: 767px) {
+ .navbar-default .navbar-nav .open .dropdown-menu > li > a {
+ color: #777777;
+ }
+ .navbar-default .navbar-nav .open .dropdown-menu > li > a:hover,
+ .navbar-default .navbar-nav .open .dropdown-menu > li > a:focus {
+ color: #333333;
+ background-color: transparent;
+ }
+ .navbar-default .navbar-nav .open .dropdown-menu > .active > a,
+ .navbar-default .navbar-nav .open .dropdown-menu > .active > a:hover,
+ .navbar-default .navbar-nav .open .dropdown-menu > .active > a:focus {
+ color: #555555;
+ background-color: #e7e7e7;
+ }
+ .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a,
+ .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:hover,
+ .navbar-default .navbar-nav .open .dropdown-menu > .disabled > a:focus {
+ color: #cccccc;
+ background-color: transparent;
+ }
+}
+.navbar-default .navbar-link {
+ color: #777777;
+}
+.navbar-default .navbar-link:hover {
+ color: #333333;
+}
+.navbar-inverse {
+ background-color: #74ab50;
+ border-color: #5c8840;
+}
+.navbar-inverse .navbar-brand {
+ color: #f9faf9;
+}
+.navbar-inverse .navbar-brand:hover,
+.navbar-inverse .navbar-brand:focus {
+ color: #ffffff;
+ background-color: transparent;
+}
+.navbar-inverse .navbar-text {
+ color: #f9faf9;
+}
+.navbar-inverse .navbar-nav > li > a {
+ color: #f9faf9;
+}
+.navbar-inverse .navbar-nav > li > a:hover,
+.navbar-inverse .navbar-nav > li > a:focus {
+ color: #ffffff;
+ background-color: transparent;
+}
+.navbar-inverse .navbar-nav > .active > a,
+.navbar-inverse .navbar-nav > .active > a:hover,
+.navbar-inverse .navbar-nav > .active > a:focus {
+ color: #ffffff;
+ background-color: #5c8840;
+}
+.navbar-inverse .navbar-nav > .disabled > a,
+.navbar-inverse .navbar-nav > .disabled > a:hover,
+.navbar-inverse .navbar-nav > .disabled > a:focus {
+ color: #444444;
+ background-color: transparent;
+}
+.navbar-inverse .navbar-toggle {
+ border-color: #333333;
+}
+.navbar-inverse .navbar-toggle:hover,
+.navbar-inverse .navbar-toggle:focus {
+ background-color: #333333;
+}
+.navbar-inverse .navbar-toggle .icon-bar {
+ background-color: #ffffff;
+}
+.navbar-inverse .navbar-collapse,
+.navbar-inverse .navbar-form {
+ border-color: #649345;
+}
+.navbar-inverse .navbar-nav > .open > a,
+.navbar-inverse .navbar-nav > .open > a:hover,
+.navbar-inverse .navbar-nav > .open > a:focus {
+ background-color: #5c8840;
+ color: #ffffff;
+}
+.navbar-inverse .navbar-nav > .dropdown > a:hover .caret {
+ border-top-color: #ffffff;
+ border-bottom-color: #ffffff;
+}
+.navbar-inverse .navbar-nav > .dropdown > a .caret {
+ border-top-color: #f9faf9;
+ border-bottom-color: #f9faf9;
+}
+.navbar-inverse .navbar-nav > .open > a .caret,
+.navbar-inverse .navbar-nav > .open > a:hover .caret,
+.navbar-inverse .navbar-nav > .open > a:focus .caret {
+ border-top-color: #ffffff;
+ border-bottom-color: #ffffff;
+}
+@media (max-width: 767px) {
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .dropdown-header {
+ border-color: #5c8840;
+ }
+ .navbar-inverse .navbar-nav .open .dropdown-menu > li > a {
+ color: #f9faf9;
+ }
+ .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:hover,
+ .navbar-inverse .navbar-nav .open .dropdown-menu > li > a:focus {
+ color: #ffffff;
+ background-color: transparent;
+ }
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a,
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:hover,
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .active > a:focus {
+ color: #ffffff;
+ background-color: #5c8840;
+ }
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a,
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:hover,
+ .navbar-inverse .navbar-nav .open .dropdown-menu > .disabled > a:focus {
+ color: #444444;
+ background-color: transparent;
+ }
+}
+.navbar-inverse .navbar-link {
+ color: #f9faf9;
+}
+.navbar-inverse .navbar-link:hover {
+ color: #ffffff;
+}
+.breadcrumb {
+ padding: 8px 15px;
+ margin-bottom: 20px;
+ list-style: none;
+ background-color: #f5f5f5;
+ border-radius: 4px;
+}
+.breadcrumb > li {
+ display: inline-block;
+}
+.breadcrumb > li + li:before {
+ content: "/\00a0";
+ padding: 0 5px;
+ color: #cccccc;
+}
+.breadcrumb > .active {
+ color: #f9faf9;
+}
+.pagination {
+ display: inline-block;
+ padding-left: 0;
+ margin: 20px 0;
+ border-radius: 4px;
+}
+.pagination > li {
+ display: inline;
+}
+.pagination > li > a,
+.pagination > li > span {
+ position: relative;
+ float: left;
+ padding: 6px 12px;
+ line-height: 1.428571429;
+ text-decoration: none;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ margin-left: -1px;
+}
+.pagination > li:first-child > a,
+.pagination > li:first-child > span {
+ margin-left: 0;
+ border-bottom-left-radius: 4px;
+ border-top-left-radius: 4px;
+}
+.pagination > li:last-child > a,
+.pagination > li:last-child > span {
+ border-bottom-right-radius: 4px;
+ border-top-right-radius: 4px;
+}
+.pagination > li > a:hover,
+.pagination > li > span:hover,
+.pagination > li > a:focus,
+.pagination > li > span:focus {
+ background-color: #bac9c2;
+}
+.pagination > .active > a,
+.pagination > .active > span,
+.pagination > .active > a:hover,
+.pagination > .active > span:hover,
+.pagination > .active > a:focus,
+.pagination > .active > span:focus {
+ z-index: 2;
+ color: #ffffff;
+ background-color: #74ab50;
+ border-color: #74ab50;
+ cursor: default;
+}
+.pagination > .disabled > span,
+.pagination > .disabled > a,
+.pagination > .disabled > a:hover,
+.pagination > .disabled > a:focus {
+ color: #f9faf9;
+ background-color: #ffffff;
+ border-color: #dddddd;
+ cursor: not-allowed;
+}
+.pagination-lg > li > a,
+.pagination-lg > li > span {
+ padding: 10px 16px;
+ font-size: 18px;
+}
+.pagination-lg > li:first-child > a,
+.pagination-lg > li:first-child > span {
+ border-bottom-left-radius: 6px;
+ border-top-left-radius: 6px;
+}
+.pagination-lg > li:last-child > a,
+.pagination-lg > li:last-child > span {
+ border-bottom-right-radius: 6px;
+ border-top-right-radius: 6px;
+}
+.pagination-sm > li > a,
+.pagination-sm > li > span {
+ padding: 5px 10px;
+ font-size: 12px;
+}
+.pagination-sm > li:first-child > a,
+.pagination-sm > li:first-child > span {
+ border-bottom-left-radius: 3px;
+ border-top-left-radius: 3px;
+}
+.pagination-sm > li:last-child > a,
+.pagination-sm > li:last-child > span {
+ border-bottom-right-radius: 3px;
+ border-top-right-radius: 3px;
+}
+.pager {
+ padding-left: 0;
+ margin: 20px 0;
+ list-style: none;
+ text-align: center;
+}
+.pager:before,
+.pager:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.pager:after {
+ clear: both;
+}
+.pager:before,
+.pager:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.pager:after {
+ clear: both;
+}
+.pager li {
+ display: inline;
+}
+.pager li > a,
+.pager li > span {
+ display: inline-block;
+ padding: 5px 14px;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-radius: 15px;
+}
+.pager li > a:hover,
+.pager li > a:focus {
+ text-decoration: none;
+ background-color: #bac9c2;
+}
+.pager .next > a,
+.pager .next > span {
+ float: right;
+}
+.pager .previous > a,
+.pager .previous > span {
+ float: left;
+}
+.pager .disabled > a,
+.pager .disabled > a:hover,
+.pager .disabled > a:focus,
+.pager .disabled > span {
+ color: #f9faf9;
+ background-color: #ffffff;
+ cursor: not-allowed;
+}
+.label {
+ display: inline;
+ padding: .2em .6em .3em;
+ font-size: 75%;
+ font-weight: bold;
+ line-height: 1;
+ color: #ffffff;
+ text-align: center;
+ white-space: nowrap;
+ vertical-align: baseline;
+ border-radius: .25em;
+}
+.label[href]:hover,
+.label[href]:focus {
+ color: #ffffff;
+ text-decoration: none;
+ cursor: pointer;
+}
+.label:empty {
+ display: none;
+}
+
+.label-default[href]:hover,
+.label-default[href]:focus {
+ background-color: #dde3dd;
+}
+.label-primary {
+ background-color: #74ab50;
+}
+.label-primary[href]:hover,
+.label-primary[href]:focus {
+ background-color: #5c8840;
+}
+.label-success {
+ background-color: #5cb85c;
+}
+.label-success[href]:hover,
+.label-success[href]:focus {
+ background-color: #449d44;
+}
+.label-info {
+ background-color: #5bc0de;
+}
+.label-info[href]:hover,
+.label-info[href]:focus {
+ background-color: #31b0d5;
+}
+.label-warning {
+ background-color: #f0ad4e;
+}
+.label-warning[href]:hover,
+.label-warning[href]:focus {
+ background-color: #ec971f;
+}
+.label-danger {
+ background-color: #d9534f;
+}
+.label-danger[href]:hover,
+.label-danger[href]:focus {
+ background-color: #c9302c;
+}
+.badge {
+ display: inline-block;
+ min-width: 10px;
+ padding: 3px 7px;
+ font-size: 12px;
+ font-weight: bold;
+ color: #ffffff;
+ line-height: 1;
+ vertical-align: baseline;
+ white-space: nowrap;
+ text-align: center;
+ background-color: #f9faf9;
+ border-radius: 10px;
+}
+.badge:empty {
+ display: none;
+}
+a.badge:hover,
+a.badge:focus {
+ color: #ffffff;
+ text-decoration: none;
+ cursor: pointer;
+}
+.btn .badge {
+ position: relative;
+ top: -1px;
+}
+a.list-group-item.active > .badge,
+.nav-pills > .active > a > .badge {
+ color: #74ab50;
+ background-color: #ffffff;
+}
+.nav-pills > li > a > .badge {
+ margin-left: 3px;
+}
+.jumbotron {
+ padding: 30px;
+ margin-bottom: 30px;
+ font-size: 21px;
+ font-weight: 200;
+ line-height: 2.1428571435;
+ color: inherit;
+ background-color: #bac9c2;
+}
+.jumbotron h1 {
+ line-height: 1;
+ color: inherit;
+}
+.jumbotron p {
+ line-height: 1.4;
+}
+.container .jumbotron {
+ border-radius: 6px;
+}
+@media screen and (min-width: 768px) {
+ .jumbotron {
+ padding-top: 48px;
+ padding-bottom: 48px;
+ }
+ .container .jumbotron {
+ padding-left: 60px;
+ padding-right: 60px;
+ }
+ .jumbotron h1 {
+ font-size: 63px;
+ }
+}
+.thumbnail {
+ padding: 4px;
+ line-height: 1.428571429;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+ border-radius: 4px;
+ -webkit-transition: all 0.2s ease-in-out;
+ transition: all 0.2s ease-in-out;
+ display: inline-block;
+ max-width: 100%;
+ height: auto;
+ display: block;
+}
+.thumbnail > img {
+ display: block;
+ max-width: 100%;
+ height: auto;
+}
+a.thumbnail:hover,
+a.thumbnail:focus {
+ border-color: #74ab50;
+}
+.thumbnail > img {
+ margin-left: auto;
+ margin-right: auto;
+}
+.thumbnail .caption {
+ padding: 9px;
+ color: #77777a;
+}
+.alert {
+ padding: 15px;
+ margin-bottom: 20px;
+ border: 1px solid transparent;
+ border-radius: 4px;
+}
+.alert h4 {
+ margin-top: 0;
+ color: inherit;
+}
+.alert .alert-link {
+ font-weight: bold;
+}
+.alert > p,
+.alert > ul {
+ margin-bottom: 0;
+}
+.alert > p + p {
+ margin-top: 5px;
+}
+.alert-dismissable {
+ padding-right: 35px;
+}
+.alert-dismissable .close {
+ position: relative;
+ top: -2px;
+ right: -21px;
+ color: inherit;
+}
+.alert-success {
+ background-color: #dff0d8;
+ border-color: #d6e9c6;
+ color: #468847;
+}
+.alert-success hr {
+ border-top-color: #c9e2b3;
+}
+.alert-success .alert-link {
+ color: #356635;
+}
+.alert-info {
+ background-color: #d9edf7;
+ border-color: #bce8f1;
+ color: #3a87ad;
+}
+.alert-info hr {
+ border-top-color: #a6e1ec;
+}
+.alert-info .alert-link {
+ color: #2d6987;
+}
+.alert-warning {
+ background-color: #fcf8e3;
+ border-color: #fbeed5;
+ color: #c09853;
+}
+.alert-warning hr {
+ border-top-color: #f8e5be;
+}
+.alert-warning .alert-link {
+ color: #a47e3c;
+}
+.alert-danger {
+ background-color: #f2dede;
+ border-color: #eed3d7;
+ color: #b94a48;
+}
+.alert-danger hr {
+ border-top-color: #e6c1c7;
+}
+.alert-danger .alert-link {
+ color: #953b39;
+}
+@-webkit-keyframes progress-bar-stripes {
+ from {
+ background-position: 40px 0;
+ }
+ to {
+ background-position: 0 0;
+ }
+}
+@-moz-keyframes progress-bar-stripes {
+ from {
+ background-position: 40px 0;
+ }
+ to {
+ background-position: 0 0;
+ }
+}
+@-o-keyframes progress-bar-stripes {
+ from {
+ background-position: 0 0;
+ }
+ to {
+ background-position: 40px 0;
+ }
+}
+@keyframes progress-bar-stripes {
+ from {
+ background-position: 40px 0;
+ }
+ to {
+ background-position: 0 0;
+ }
+}
+.progress {
+ overflow: hidden;
+ height: 20px;
+ margin-bottom: 20px;
+ background-color: #f5f5f5;
+ border-radius: 4px;
+ -webkit-box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
+ box-shadow: inset 0 1px 2px rgba(0, 0, 0, 0.1);
+}
+.progress-bar {
+ float: left;
+ width: 0%;
+ height: 100%;
+ font-size: 12px;
+ color: #ffffff;
+ text-align: center;
+ background-color: #74ab50;
+ -webkit-box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
+ box-shadow: inset 0 -1px 0 rgba(0, 0, 0, 0.15);
+ -webkit-transition: width 0.6s ease;
+ transition: width 0.6s ease;
+}
+.progress-striped .progress-bar {
+ background-image: -webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));
+ background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: -moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-size: 40px 40px;
+}
+.progress.active .progress-bar {
+ -webkit-animation: progress-bar-stripes 2s linear infinite;
+ -moz-animation: progress-bar-stripes 2s linear infinite;
+ -ms-animation: progress-bar-stripes 2s linear infinite;
+ -o-animation: progress-bar-stripes 2s linear infinite;
+ animation: progress-bar-stripes 2s linear infinite;
+}
+.progress-bar-success {
+ background-color: #5cb85c;
+}
+.progress-striped .progress-bar-success {
+ background-image: -webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));
+ background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: -moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-info {
+ background-color: #5bc0de;
+}
+.progress-striped .progress-bar-info {
+ background-image: -webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));
+ background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: -moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-warning {
+ background-color: #f0ad4e;
+}
+.progress-striped .progress-bar-warning {
+ background-image: -webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));
+ background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: -moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.progress-bar-danger {
+ background-color: #d9534f;
+}
+.progress-striped .progress-bar-danger {
+ background-image: -webkit-gradient(linear, 0 100%, 100% 0, color-stop(0.25, rgba(255, 255, 255, 0.15)), color-stop(0.25, transparent), color-stop(0.5, transparent), color-stop(0.5, rgba(255, 255, 255, 0.15)), color-stop(0.75, rgba(255, 255, 255, 0.15)), color-stop(0.75, transparent), to(transparent));
+ background-image: -webkit-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: -moz-linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+ background-image: linear-gradient(45deg, rgba(255, 255, 255, 0.15) 25%, transparent 25%, transparent 50%, rgba(255, 255, 255, 0.15) 50%, rgba(255, 255, 255, 0.15) 75%, transparent 75%, transparent);
+}
+.media,
+.media-body {
+ overflow: hidden;
+ zoom: 1;
+}
+.media,
+.media .media {
+ margin-top: 15px;
+}
+.media:first-child {
+ margin-top: 0;
+}
+.media-object {
+ display: block;
+}
+.media-heading {
+ margin: 0 0 5px;
+}
+.media > .pull-left {
+ margin-right: 10px;
+}
+.media > .pull-right {
+ margin-left: 10px;
+}
+.media-list {
+ padding-left: 0;
+ list-style: none;
+}
+.list-group {
+ margin-bottom: 20px;
+ padding-left: 0;
+}
+.list-group-item {
+ position: relative;
+ display: block;
+ padding: 10px 15px;
+ margin-bottom: -1px;
+ background-color: #ffffff;
+ border: 1px solid #dddddd;
+}
+.list-group-item:first-child {
+ border-top-right-radius: 4px;
+ border-top-left-radius: 4px;
+}
+.list-group-item:last-child {
+ margin-bottom: 0;
+ border-bottom-right-radius: 4px;
+ border-bottom-left-radius: 4px;
+}
+.list-group-item > .badge {
+ float: right;
+}
+.list-group-item > .badge + .badge {
+ margin-right: 5px;
+}
+a.list-group-item {
+ color: #555555;
+}
+a.list-group-item .list-group-item-heading {
+ color: #333333;
+}
+a.list-group-item:hover,
+a.list-group-item:focus {
+ text-decoration: none;
+ background-color: #f5f5f5;
+}
+.list-group-item.active,
+.list-group-item.active:hover,
+.list-group-item.active:focus {
+ z-index: 2;
+ color: #ffffff;
+ background-color: #74ab50;
+ border-color: #74ab50;
+}
+.list-group-item.active .list-group-item-heading,
+.list-group-item.active:hover .list-group-item-heading,
+.list-group-item.active:focus .list-group-item-heading {
+ color: inherit;
+}
+.list-group-item.active .list-group-item-text,
+.list-group-item.active:hover .list-group-item-text,
+.list-group-item.active:focus .list-group-item-text {
+ color: #e1edda;
+}
+.list-group-item-heading {
+ margin-top: 0;
+ margin-bottom: 5px;
+}
+.list-group-item-text {
+ margin-bottom: 0;
+ line-height: 1.3;
+}
+.panel {
+ margin-bottom: 20px;
+ background-color: #ffffff;
+ border: 1px solid transparent;
+ border-radius: 4px;
+ -webkit-box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
+ box-shadow: 0 1px 1px rgba(0, 0, 0, 0.05);
+}
+.panel-body {
+ padding: 15px;
+}
+.panel-body:before,
+.panel-body:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.panel-body:after {
+ clear: both;
+}
+.panel-body:before,
+.panel-body:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.panel-body:after {
+ clear: both;
+}
+.panel > .list-group {
+ margin-bottom: 0;
+}
+.panel > .list-group .list-group-item {
+ border-width: 1px 0;
+}
+.panel > .list-group .list-group-item:first-child {
+ border-top-right-radius: 0;
+ border-top-left-radius: 0;
+}
+.panel > .list-group .list-group-item:last-child {
+ border-bottom: 0;
+}
+.panel-heading + .list-group .list-group-item:first-child {
+ border-top-width: 0;
+}
+.panel > .table {
+ margin-bottom: 0;
+}
+.panel > .panel-body + .table {
+ border-top: 1px solid #77777a;
+}
+.panel-heading {
+ padding: 10px 15px;
+ border-bottom: 1px solid transparent;
+ border-top-right-radius: 3px;
+ border-top-left-radius: 3px;
+}
+.panel-title {
+ margin-top: 0;
+ margin-bottom: 0;
+ font-size: 16px;
+}
+.panel-title > a {
+ color: inherit;
+}
+.panel-footer {
+ padding: 10px 15px;
+ background-color: #f5f5f5;
+ border-top: 1px solid #dddddd;
+ border-bottom-right-radius: 3px;
+ border-bottom-left-radius: 3px;
+}
+.panel-group .panel {
+ margin-bottom: 0;
+ border-radius: 4px;
+ overflow: hidden;
+}
+.panel-group .panel + .panel {
+ margin-top: 5px;
+}
+.panel-group .panel-heading {
+ border-bottom: 0;
+}
+.panel-group .panel-heading + .panel-collapse .panel-body {
+ border-top: 1px solid #dddddd;
+}
+.panel-group .panel-footer {
+ border-top: 0;
+}
+.panel-group .panel-footer + .panel-collapse .panel-body {
+ border-bottom: 1px solid #dddddd;
+}
+.panel-default {
+ border-color: #dddddd;
+}
+.panel-default > .panel-heading {
+ color: #77777a;
+ background-color: #f5f5f5;
+ border-color: #dddddd;
+}
+.panel-default > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #dddddd;
+}
+.panel-default > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #dddddd;
+}
+.panel-primary {
+ border-color: #74ab50;
+}
+.panel-primary > .panel-heading {
+ color: #ffffff;
+ background-color: #74ab50;
+ border-color: #74ab50;
+}
+.panel-primary > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #74ab50;
+}
+.panel-primary > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #74ab50;
+}
+.panel-success {
+ border-color: #d6e9c6;
+}
+.panel-success > .panel-heading {
+ color: #468847;
+ background-color: #dff0d8;
+ border-color: #d6e9c6;
+}
+.panel-success > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #d6e9c6;
+}
+.panel-success > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #d6e9c6;
+}
+.panel-warning {
+ border-color: #fbeed5;
+}
+.panel-warning > .panel-heading {
+ color: #c09853;
+ background-color: #fcf8e3;
+ border-color: #fbeed5;
+}
+.panel-warning > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #fbeed5;
+}
+.panel-warning > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #fbeed5;
+}
+.panel-danger {
+ border-color: #eed3d7;
+}
+.panel-danger > .panel-heading {
+ color: #b94a48;
+ background-color: #f2dede;
+ border-color: #eed3d7;
+}
+.panel-danger > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #eed3d7;
+}
+.panel-danger > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #eed3d7;
+}
+.panel-info {
+ border-color: #bce8f1;
+}
+.panel-info > .panel-heading {
+ color: #3a87ad;
+ background-color: #d9edf7;
+ border-color: #bce8f1;
+}
+.panel-info > .panel-heading + .panel-collapse .panel-body {
+ border-top-color: #bce8f1;
+}
+.panel-info > .panel-footer + .panel-collapse .panel-body {
+ border-bottom-color: #bce8f1;
+}
+.well {
+ min-height: 20px;
+ padding: 19px;
+ margin-bottom: 20px;
+ background-color: #f5f5f5;
+ border: 1px solid #e3e3e3;
+ border-radius: 4px;
+ -webkit-box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
+ box-shadow: inset 0 1px 1px rgba(0, 0, 0, 0.05);
+}
+.well blockquote {
+ border-color: #ddd;
+ border-color: rgba(0, 0, 0, 0.15);
+}
+.well-lg {
+ padding: 24px;
+ border-radius: 6px;
+}
+.well-sm {
+ padding: 9px;
+ border-radius: 3px;
+}
+.close {
+ float: right;
+ font-size: 21px;
+ font-weight: bold;
+ line-height: 1;
+ color: #000000;
+ text-shadow: 0 1px 0 #ffffff;
+ opacity: 0.2;
+ filter: alpha(opacity=20);
+}
+.close:hover,
+.close:focus {
+ color: #000000;
+ text-decoration: none;
+ cursor: pointer;
+ opacity: 0.5;
+ filter: alpha(opacity=50);
+}
+button.close {
+ padding: 0;
+ cursor: pointer;
+ background: transparent;
+ border: 0;
+ -webkit-appearance: none;
+}
+.modal-open {
+ overflow: hidden;
+}
+body.modal-open,
+.modal-open .navbar-fixed-top,
+.modal-open .navbar-fixed-bottom {
+ margin-right: 15px;
+}
+.modal {
+ display: none;
+ overflow: auto;
+ overflow-y: scroll;
+ position: fixed;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ z-index: 1040;
+}
+.modal.fade .modal-dialog {
+ -webkit-transform: translate(0, -25%);
+ -ms-transform: translate(0, -25%);
+ transform: translate(0, -25%);
+ -webkit-transition: -webkit-transform 0.3s ease-out;
+ -moz-transition: -moz-transform 0.3s ease-out;
+ -o-transition: -o-transform 0.3s ease-out;
+ transition: transform 0.3s ease-out;
+}
+.modal.in .modal-dialog {
+ -webkit-transform: translate(0, 0);
+ -ms-transform: translate(0, 0);
+ transform: translate(0, 0);
+}
+.modal-dialog {
+ margin-left: auto;
+ margin-right: auto;
+ width: auto;
+ padding: 10px;
+ z-index: 1050;
+}
+.modal-content {
+ position: relative;
+ background-color: #ffffff;
+ border: 1px solid #999999;
+ border: 1px solid rgba(0, 0, 0, 0.2);
+ border-radius: 6px;
+ -webkit-box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
+ box-shadow: 0 3px 9px rgba(0, 0, 0, 0.5);
+ background-clip: padding-box;
+ outline: none;
+}
+.modal-backdrop {
+ position: fixed;
+ top: 0;
+ right: 0;
+ bottom: 0;
+ left: 0;
+ z-index: 1030;
+ background-color: #000000;
+}
+.modal-backdrop.fade {
+ opacity: 0;
+ filter: alpha(opacity=0);
+}
+.modal-backdrop.in {
+ opacity: 0.5;
+ filter: alpha(opacity=50);
+}
+.modal-header {
+ padding: 15px;
+ border-bottom: 1px solid #e5e5e5;
+ min-height: 16.428571429px;
+}
+.modal-header .close {
+ margin-top: -2px;
+}
+.modal-title {
+ margin: 0;
+ line-height: 1.428571429;
+}
+.modal-body {
+ position: relative;
+ padding: 20px;
+}
+.modal-footer {
+ margin-top: 15px;
+ padding: 19px 20px 20px;
+ text-align: right;
+ border-top: 1px solid #e5e5e5;
+}
+.modal-footer:before,
+.modal-footer:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.modal-footer:after {
+ clear: both;
+}
+.modal-footer:before,
+.modal-footer:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.modal-footer:after {
+ clear: both;
+}
+.modal-footer .btn + .btn {
+ margin-left: 5px;
+ margin-bottom: 0;
+}
+.modal-footer .btn-group .btn + .btn {
+ margin-left: -1px;
+}
+.modal-footer .btn-block + .btn-block {
+ margin-left: 0;
+}
+@media screen and (min-width: 768px) {
+ .modal-dialog {
+ left: 50%;
+ right: auto;
+ width: 600px;
+ padding-top: 30px;
+ padding-bottom: 30px;
+ }
+ .modal-content {
+ -webkit-box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
+ box-shadow: 0 5px 15px rgba(0, 0, 0, 0.5);
+ }
+}
+.tooltip {
+ position: absolute;
+ z-index: 1030;
+ display: block;
+ visibility: visible;
+ font-size: 12px;
+ line-height: 1.4;
+ opacity: 0;
+ filter: alpha(opacity=0);
+}
+.tooltip.in {
+ opacity: 0.9;
+ filter: alpha(opacity=90);
+}
+.tooltip.top {
+ margin-top: -3px;
+ padding: 5px 0;
+}
+.tooltip.right {
+ margin-left: 3px;
+ padding: 0 5px;
+}
+.tooltip.bottom {
+ margin-top: 3px;
+ padding: 5px 0;
+}
+.tooltip.left {
+ margin-left: -3px;
+ padding: 0 5px;
+}
+.tooltip-inner {
+ max-width: 200px;
+ padding: 3px 8px;
+ color: #ffffff;
+ text-align: center;
+ text-decoration: none;
+ background-color: #000000;
+ border-radius: 4px;
+}
+.tooltip-arrow {
+ position: absolute;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+}
+.tooltip.top .tooltip-arrow {
+ bottom: 0;
+ left: 50%;
+ margin-left: -5px;
+ border-width: 5px 5px 0;
+ border-top-color: #000000;
+}
+.tooltip.top-left .tooltip-arrow {
+ bottom: 0;
+ left: 5px;
+ border-width: 5px 5px 0;
+ border-top-color: #000000;
+}
+.tooltip.top-right .tooltip-arrow {
+ bottom: 0;
+ right: 5px;
+ border-width: 5px 5px 0;
+ border-top-color: #000000;
+}
+.tooltip.right .tooltip-arrow {
+ top: 50%;
+ left: 0;
+ margin-top: -5px;
+ border-width: 5px 5px 5px 0;
+ border-right-color: #000000;
+}
+.tooltip.left .tooltip-arrow {
+ top: 50%;
+ right: 0;
+ margin-top: -5px;
+ border-width: 5px 0 5px 5px;
+ border-left-color: #000000;
+}
+.tooltip.bottom .tooltip-arrow {
+ top: 0;
+ left: 50%;
+ margin-left: -5px;
+ border-width: 0 5px 5px;
+ border-bottom-color: #000000;
+}
+.tooltip.bottom-left .tooltip-arrow {
+ top: 0;
+ left: 5px;
+ border-width: 0 5px 5px;
+ border-bottom-color: #000000;
+}
+.tooltip.bottom-right .tooltip-arrow {
+ top: 0;
+ right: 5px;
+ border-width: 0 5px 5px;
+ border-bottom-color: #000000;
+}
+.popover {
+ position: absolute;
+ top: 0;
+ left: 0;
+ z-index: 1010;
+ display: none;
+ max-width: 276px;
+ padding: 1px;
+ text-align: left;
+ background-color: #ffffff;
+ background-clip: padding-box;
+ border: 1px solid #cccccc;
+ border: 1px solid rgba(0, 0, 0, 0.2);
+ border-radius: 6px;
+ -webkit-box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
+ box-shadow: 0 5px 10px rgba(0, 0, 0, 0.2);
+ white-space: normal;
+}
+.popover.top {
+ margin-top: -10px;
+}
+.popover.right {
+ margin-left: 10px;
+}
+.popover.bottom {
+ margin-top: 10px;
+}
+.popover.left {
+ margin-left: -10px;
+}
+.popover-title {
+ margin: 0;
+ padding: 8px 14px;
+ font-size: 14px;
+ font-weight: normal;
+ line-height: 18px;
+ background-color: #f7f7f7;
+ border-bottom: 1px solid #ebebeb;
+ border-radius: 5px 5px 0 0;
+}
+.popover-content {
+ padding: 9px 14px;
+}
+.popover .arrow,
+.popover .arrow:after {
+ position: absolute;
+ display: block;
+ width: 0;
+ height: 0;
+ border-color: transparent;
+ border-style: solid;
+}
+.popover .arrow {
+ border-width: 11px;
+}
+.popover .arrow:after {
+ border-width: 10px;
+ content: "";
+}
+.popover.top .arrow {
+ left: 50%;
+ margin-left: -11px;
+ border-bottom-width: 0;
+ border-top-color: #999999;
+ border-top-color: rgba(0, 0, 0, 0.25);
+ bottom: -11px;
+}
+.popover.top .arrow:after {
+ content: " ";
+ bottom: 1px;
+ margin-left: -10px;
+ border-bottom-width: 0;
+ border-top-color: #ffffff;
+}
+.popover.right .arrow {
+ top: 50%;
+ left: -11px;
+ margin-top: -11px;
+ border-left-width: 0;
+ border-right-color: #999999;
+ border-right-color: rgba(0, 0, 0, 0.25);
+}
+.popover.right .arrow:after {
+ content: " ";
+ left: 1px;
+ bottom: -10px;
+ border-left-width: 0;
+ border-right-color: #ffffff;
+}
+.popover.bottom .arrow {
+ left: 50%;
+ margin-left: -11px;
+ border-top-width: 0;
+ border-bottom-color: #999999;
+ border-bottom-color: rgba(0, 0, 0, 0.25);
+ top: -11px;
+}
+.popover.bottom .arrow:after {
+ content: " ";
+ top: 1px;
+ margin-left: -10px;
+ border-top-width: 0;
+ border-bottom-color: #ffffff;
+}
+.popover.left .arrow {
+ top: 50%;
+ right: -11px;
+ margin-top: -11px;
+ border-right-width: 0;
+ border-left-color: #999999;
+ border-left-color: rgba(0, 0, 0, 0.25);
+}
+.popover.left .arrow:after {
+ content: " ";
+ right: 1px;
+ border-right-width: 0;
+ border-left-color: #ffffff;
+ bottom: -10px;
+}
+.carousel {
+ position: relative;
+}
+.carousel-inner {
+ position: relative;
+ overflow: hidden;
+ width: 100%;
+}
+.carousel-inner > .item {
+ display: none;
+ position: relative;
+ -webkit-transition: 0.6s ease-in-out left;
+ transition: 0.6s ease-in-out left;
+}
+.carousel-inner > .item > img,
+.carousel-inner > .item > a > img {
+ display: block;
+ max-width: 100%;
+ height: auto;
+ line-height: 1;
+}
+.carousel-inner > .active,
+.carousel-inner > .next,
+.carousel-inner > .prev {
+ display: block;
+}
+.carousel-inner > .active {
+ left: 0;
+}
+.carousel-inner > .next,
+.carousel-inner > .prev {
+ position: absolute;
+ top: 0;
+ width: 100%;
+}
+.carousel-inner > .next {
+ left: 100%;
+}
+.carousel-inner > .prev {
+ left: -100%;
+}
+.carousel-inner > .next.left,
+.carousel-inner > .prev.right {
+ left: 0;
+}
+.carousel-inner > .active.left {
+ left: -100%;
+}
+.carousel-inner > .active.right {
+ left: 100%;
+}
+.carousel-control {
+ position: absolute;
+ top: 0;
+ left: 0;
+ bottom: 0;
+ width: 15%;
+ opacity: 0.5;
+ filter: alpha(opacity=50);
+ font-size: 20px;
+ color: #ffffff;
+ text-align: center;
+ text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
+}
+.carousel-control.left {
+ background-image: -webkit-gradient(linear, 0% top, 100% top, from(rgba(0, 0, 0, 0.5)), to(rgba(0, 0, 0, 0.0001)));
+ background-image: -webkit-linear-gradient(left, color-stop(rgba(0, 0, 0, 0.5) 0%), color-stop(rgba(0, 0, 0, 0.0001) 100%));
+ background-image: -moz-linear-gradient(left, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
+ background-image: linear-gradient(to right, rgba(0, 0, 0, 0.5) 0%, rgba(0, 0, 0, 0.0001) 100%);
+ background-repeat: repeat-x;
+ filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#80000000', endColorstr='#00000000', GradientType=1);
+}
+.carousel-control.right {
+ left: auto;
+ right: 0;
+ background-image: -webkit-gradient(linear, 0% top, 100% top, from(rgba(0, 0, 0, 0.0001)), to(rgba(0, 0, 0, 0.5)));
+ background-image: -webkit-linear-gradient(left, color-stop(rgba(0, 0, 0, 0.0001) 0%), color-stop(rgba(0, 0, 0, 0.5) 100%));
+ background-image: -moz-linear-gradient(left, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
+ background-image: linear-gradient(to right, rgba(0, 0, 0, 0.0001) 0%, rgba(0, 0, 0, 0.5) 100%);
+ background-repeat: repeat-x;
+ filter: progid:DXImageTransform.Microsoft.gradient(startColorstr='#00000000', endColorstr='#80000000', GradientType=1);
+}
+.carousel-control:hover,
+.carousel-control:focus {
+ color: #ffffff;
+ text-decoration: none;
+ opacity: 0.9;
+ filter: alpha(opacity=90);
+}
+.carousel-control .icon-prev,
+.carousel-control .icon-next,
+.carousel-control .glyphicon-chevron-left,
+.carousel-control .glyphicon-chevron-right {
+ position: absolute;
+ top: 50%;
+ left: 50%;
+ z-index: 5;
+ display: inline-block;
+}
+.carousel-control .icon-prev,
+.carousel-control .icon-next {
+ width: 20px;
+ height: 20px;
+ margin-top: -10px;
+ margin-left: -10px;
+ font-family: serif;
+}
+.carousel-control .icon-prev:before {
+ content: '\2039';
+}
+.carousel-control .icon-next:before {
+ content: '\203a';
+}
+.carousel-indicators {
+ position: absolute;
+ bottom: 10px;
+ left: 50%;
+ z-index: 15;
+ width: 60%;
+ margin-left: -30%;
+ padding-left: 0;
+ list-style: none;
+ text-align: center;
+}
+.carousel-indicators li {
+ display: inline-block;
+ width: 10px;
+ height: 10px;
+ margin: 1px;
+ text-indent: -999px;
+ border: 1px solid #ffffff;
+ border-radius: 10px;
+ cursor: pointer;
+}
+.carousel-indicators .active {
+ margin: 0;
+ width: 12px;
+ height: 12px;
+ background-color: #ffffff;
+}
+.carousel-caption {
+ position: absolute;
+ left: 15%;
+ right: 15%;
+ bottom: 20px;
+ z-index: 10;
+ padding-top: 20px;
+ padding-bottom: 20px;
+ color: #ffffff;
+ text-align: center;
+ text-shadow: 0 1px 2px rgba(0, 0, 0, 0.6);
+}
+.carousel-caption .btn {
+ text-shadow: none;
+}
+@media screen and (min-width: 768px) {
+ .carousel-control .icon-prev,
+ .carousel-control .icon-next {
+ width: 30px;
+ height: 30px;
+ margin-top: -15px;
+ margin-left: -15px;
+ font-size: 30px;
+ }
+ .carousel-caption {
+ left: 20%;
+ right: 20%;
+ padding-bottom: 30px;
+ }
+ .carousel-indicators {
+ bottom: 20px;
+ }
+}
+.clearfix:before,
+.clearfix:after {
+ content: " ";
+ /* 1 */
+
+ display: table;
+ /* 2 */
+
+}
+.clearfix:after {
+ clear: both;
+}
+.pull-right {
+ float: right !important;
+}
+.pull-left {
+ float: left !important;
+}
+.hide {
+ display: none !important;
+}
+.show {
+ display: block !important;
+}
+.invisible {
+ visibility: hidden;
+}
+.text-hide {
+ font: 0/0 a;
+ color: transparent;
+ text-shadow: none;
+ background-color: transparent;
+ border: 0;
+}
+.affix {
+ position: fixed;
+}
+@-ms-viewport {
+ width: device-width;
+}
+@media screen and (max-width: 400px) {
+ @-ms-viewport {
+ width: 320px;
+ }
+}
+.hidden {
+ display: none !important;
+ visibility: hidden !important;
+}
+.visible-xs {
+ display: none !important;
+}
+tr.visible-xs {
+ display: none !important;
+}
+th.visible-xs,
+td.visible-xs {
+ display: none !important;
+}
+@media (max-width: 767px) {
+ .visible-xs {
+ display: block !important;
+ }
+ tr.visible-xs {
+ display: table-row !important;
+ }
+ th.visible-xs,
+ td.visible-xs {
+ display: table-cell !important;
+ }
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