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Posted to commits@carbondata.apache.org by ch...@apache.org on 2018/09/07 16:53:49 UTC
[02/39] carbondata-site git commit: Added new page layout & updated
as per new md files
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/installation-guide.md
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-<!--
- Licensed to the Apache Software Foundation (ASF) under one or more
- contributor license agreements. See the NOTICE file distributed with
- this work for additional information regarding copyright ownership.
- The ASF licenses this file to you under the Apache License, Version 2.0
- (the "License"); you may not use this file except in compliance with
- the License. You may obtain a copy of the License at
-
- http://www.apache.org/licenses/LICENSE-2.0
-
- Unless required by applicable law or agreed to in writing, software
- distributed under the License is distributed on an "AS IS" BASIS,
- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- See the License for the specific language governing permissions and
- limitations under the License.
--->
-
-# Installation Guide
-This tutorial guides you through the installation and configuration of CarbonData in the following two modes :
-
-* [Installing and Configuring CarbonData on Standalone Spark Cluster](#installing-and-configuring-carbondata-on-standalone-spark-cluster)
-* [Installing and Configuring CarbonData on Spark on YARN Cluster](#installing-and-configuring-carbondata-on-spark-on-yarn-cluster)
-
-followed by :
-
-* [Query Execution using CarbonData Thrift Server](#query-execution-using-carbondata-thrift-server)
-
-## Installing and Configuring CarbonData on Standalone Spark Cluster
-
-### Prerequisites
-
- - Hadoop HDFS and Yarn should be installed and running.
-
- - Spark should be installed and running on all the cluster nodes.
-
- - CarbonData user should have permission to access HDFS.
-
-
-### Procedure
-
-1. [Build the CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) project and get the assembly jar from `./assembly/target/scala-2.1x/carbondata_xxx.jar`.
-
-2. Copy `./assembly/target/scala-2.1x/carbondata_xxx.jar` to `$SPARK_HOME/carbonlib` folder.
-
- **NOTE**: Create the carbonlib folder if it does not exist inside `$SPARK_HOME` path.
-
-3. Add the carbonlib folder path in the Spark classpath. (Edit `$SPARK_HOME/conf/spark-env.sh` file and modify the value of `SPARK_CLASSPATH` by appending `$SPARK_HOME/carbonlib/*` to the existing value)
-
-4. Copy the `./conf/carbon.properties.template` file from CarbonData repository to `$SPARK_HOME/conf/` folder and rename the file to `carbon.properties`.
-
-5. Repeat Step 2 to Step 5 in all the nodes of the cluster.
-
-6. In Spark node[master], configure the properties mentioned in the following table in `$SPARK_HOME/conf/spark-defaults.conf` file.
-
-| Property | Value | Description |
-|---------------------------------|-----------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------|
-| spark.driver.extraJavaOptions | `-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` | A string of extra JVM options to pass to the driver. For instance, GC settings or other logging. |
-| spark.executor.extraJavaOptions | `-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` | A string of extra JVM options to pass to executors. For instance, GC settings or other logging. **NOTE**: You can enter multiple values separated by space. |
-
-7. Add the following properties in `$SPARK_HOME/conf/carbon.properties` file:
-
-| Property | Required | Description | Example | Remark |
-|----------------------|----------|----------------------------------------------------------------------------------------|-------------------------------------|---------|
-| carbon.storelocation | NO | Location where data CarbonData will create the store and write the data in its own format. If not specified then it takes spark.sql.warehouse.dir path. | hdfs://HOSTNAME:PORT/Opt/CarbonStore | Propose to set HDFS directory |
-
-
-8. Verify the installation. For example:
-
-```
-./spark-shell --master spark://HOSTNAME:PORT --total-executor-cores 2
---executor-memory 2G
-```
-
-**NOTE**: Make sure you have permissions for CarbonData JARs and files through which driver and executor will start.
-
-To get started with CarbonData : [Quick Start](quick-start-guide.md), [Data Management on CarbonData](data-management-on-carbondata.md)
-
-## Installing and Configuring CarbonData on Spark on YARN Cluster
-
- This section provides the procedure to install CarbonData on "Spark on YARN" cluster.
-
-### Prerequisites
- * Hadoop HDFS and Yarn should be installed and running.
- * Spark should be installed and running in all the clients.
- * CarbonData user should have permission to access HDFS.
-
-### Procedure
-
- The following steps are only for Driver Nodes. (Driver nodes are the one which starts the spark context.)
-
-1. [Build the CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) project and get the assembly jar from `./assembly/target/scala-2.1x/carbondata_xxx.jar` and copy to `$SPARK_HOME/carbonlib` folder.
-
- **NOTE**: Create the carbonlib folder if it does not exists inside `$SPARK_HOME` path.
-
-2. Copy the `./conf/carbon.properties.template` file from CarbonData repository to `$SPARK_HOME/conf/` folder and rename the file to `carbon.properties`.
-
-3. Create `tar.gz` file of carbonlib folder and move it inside the carbonlib folder.
-
-```
-cd $SPARK_HOME
-tar -zcvf carbondata.tar.gz carbonlib/
-mv carbondata.tar.gz carbonlib/
-```
-
-4. Configure the properties mentioned in the following table in `$SPARK_HOME/conf/spark-defaults.conf` file.
-
-| Property | Description | Value |
-|---------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------|
-| spark.master | Set this value to run the Spark in yarn cluster mode. | Set yarn-client to run the Spark in yarn cluster mode. |
-| spark.yarn.dist.files | Comma-separated list of files to be placed in the working directory of each executor. |`$SPARK_HOME/conf/carbon.properties` |
-| spark.yarn.dist.archives | Comma-separated list of archives to be extracted into the working directory of each executor. |`$SPARK_HOME/carbonlib/carbondata.tar.gz` |
-| spark.executor.extraJavaOptions | A string of extra JVM options to pass to executors. For instance **NOTE**: You can enter multiple values separated by space. |`-Dcarbon.properties.filepath = carbon.properties` |
-| spark.executor.extraClassPath | Extra classpath entries to prepend to the classpath of executors. **NOTE**: If SPARK_CLASSPATH is defined in spark-env.sh, then comment it and append the values in below parameter spark.driver.extraClassPath |`carbondata.tar.gz/carbonlib/*` |
-| spark.driver.extraClassPath | Extra classpath entries to prepend to the classpath of the driver. **NOTE**: If SPARK_CLASSPATH is defined in spark-env.sh, then comment it and append the value in below parameter spark.driver.extraClassPath. |`$SPARK_HOME/carbonlib/*` |
-| spark.driver.extraJavaOptions | A string of extra JVM options to pass to the driver. For instance, GC settings or other logging. |`-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` |
-
-
-5. Add the following properties in `$SPARK_HOME/conf/carbon.properties`:
-
-| Property | Required | Description | Example | Default Value |
-|----------------------|----------|----------------------------------------------------------------------------------------|-------------------------------------|---------------|
-| carbon.storelocation | NO | Location where CarbonData will create the store and write the data in its own format. If not specified then it takes spark.sql.warehouse.dir path.| hdfs://HOSTNAME:PORT/Opt/CarbonStore | Propose to set HDFS directory|
-
-6. Verify the installation.
-
-```
- ./bin/spark-shell --master yarn-client --driver-memory 1g
- --executor-cores 2 --executor-memory 2G
-```
- **NOTE**: Make sure you have permissions for CarbonData JARs and files through which driver and executor will start.
-
- Getting started with CarbonData : [Quick Start](quick-start-guide.md), [Data Management on CarbonData](data-management-on-carbondata.md)
-
-## Query Execution Using CarbonData Thrift Server
-
-### Starting CarbonData Thrift Server.
-
- a. cd `$SPARK_HOME`
-
- b. Run the following command to start the CarbonData thrift server.
-
-```
-./bin/spark-submit
---class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-$SPARK_HOME/carbonlib/$CARBON_ASSEMBLY_JAR <carbon_store_path>
-```
-
-| Parameter | Description | Example |
-|---------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------|
-| CARBON_ASSEMBLY_JAR | CarbonData assembly jar name present in the `$SPARK_HOME/carbonlib/` folder. | carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar |
-| carbon_store_path | This is a parameter to the CarbonThriftServer class. This a HDFS path where CarbonData files will be kept. Strongly Recommended to put same as carbon.storelocation parameter of carbon.properties. If not specified then it takes spark.sql.warehouse.dir path. | `hdfs://<host_name>:port/user/hive/warehouse/carbon.store` |
-
-**NOTE**: From Spark 1.6, by default the Thrift server runs in multi-session mode. Which means each JDBC/ODBC connection owns a copy of their own SQL configuration and temporary function registry. Cached tables are still shared though. If you prefer to run the Thrift server in single-session mode and share all SQL configuration and temporary function registry, please set option `spark.sql.hive.thriftServer.singleSession` to `true`. You may either add this option to `spark-defaults.conf`, or pass it to `spark-submit.sh` via `--conf`:
-
-```
-./bin/spark-submit
---conf spark.sql.hive.thriftServer.singleSession=true
---class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-$SPARK_HOME/carbonlib/$CARBON_ASSEMBLY_JAR <carbon_store_path>
-```
-
-**But** in single-session mode, if one user changes the database from one connection, the database of the other connections will be changed too.
-
-**Examples**
-
- * Start with default memory and executors.
-
-```
-./bin/spark-submit
---class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
-$SPARK_HOME/carbonlib
-/carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar
-hdfs://<host_name>:port/user/hive/warehouse/carbon.store
-```
-
- * Start with Fixed executors and resources.
-
-```
-./bin/spark-submit
---class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
---num-executors 3 --driver-memory 20g --executor-memory 250g
---executor-cores 32
-/srv/OSCON/BigData/HACluster/install/spark/sparkJdbc/lib
-/carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar
-hdfs://<host_name>:port/user/hive/warehouse/carbon.store
-```
-
-### Connecting to CarbonData Thrift Server Using Beeline.
-
-```
- cd $SPARK_HOME
- ./sbin/start-thriftserver.sh
- ./bin/beeline -u jdbc:hive2://<thriftserver_host>:port
-
- Example
- ./bin/beeline -u jdbc:hive2://10.10.10.10:10000
-```
-
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/introduction.md
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+## What is CarbonData
+
+CarbonData is a fully indexed columnar and Hadoop native data-store for processing heavy analytical workloads and detailed queries on big data with Spark SQL. CarbonData allows faster interactive queries over PetaBytes of data.
+
+
+
+## What does this mean
+
+CarbonData has specially engineered optimizations like multi level indexing, compression and encoding techniques targeted to improve performance of analytical queries which can include filters, aggregation and distinct counts where users expect sub second response time for queries on TB level data on commodity hardware clusters with just a few nodes.
+
+CarbonData has
+
+- **Unique data organisation** for faster retrievals and minimise amount of data retrieved
+
+- **Advanced push down optimisations** for deep integration with Spark so as to improvise the Spark DataSource API and other experimental features thereby ensure computing is performed close to the data to minimise amount of data read, processed, converted and transmitted(shuffled)
+
+- **Multi level indexing** to efficiently prune the files and data to be scanned and hence reduce I/O scans and CPU processing
+
+
+
+## Architecture
+
+
+
+
+
+#### Spark Interface Layer:
+
+CarbonData has deep integration with Apache Spark.CarbonData integrates custom Parser,Strategies,Optimization rules into Spark to take advantage of computing performed closer to data.
+
+
+
+1. **Carbon parser** Enhances Spark’s SQL parser to support Carbon specific DDL and DML commands to create carbon table, create aggregate tables, manage data loading, data retention and cleanup.
+2. **Carbon Strategies**:- Modify Spark SQL’s physical query execution plan to push down possible operations to Carbon for example:- Grouping, Distinct Count, Top N etc.. for improving query performance.
+3. **Carbon Data RDD**:- Makes the data present in Carbon tables visible to Spark as a RDD which enables spark to perform distributed computation on Carbon tables.
+
+
+
+#### Carbon Processor:
+
+Receives a query execution fragment from spark and executes the same on the Carbon storage. This involves Scanning the carbon store files for matching record, using the indices to directly locate the row sets and even the rows that may containing the data being searched for. The Carbon processor also performs all pushed down operations such as
+
+Aggregation/Group By
+
+Distinct Count
+
+Top N
+
+Expression Evaluation
+
+And many more…
+
+#### Carbon Storage:
+
+Custom columnar data store which is heavily compressed, binary, dictionary encoded and heavily indexed.Usaually stored in HDFS.
+
+## CarbonData Features
+
+CarbonData has rich set of featues to support various use cases in Big Data analytics.
+
+
+
+## Design
+
+- ### Dictionary Encoding
+
+CarbonData supports encoding of data with suggogate values to reduce storage space and speed up processing.Most databases and big data SQL data stores adopt dictionary encoding(integer surrogate numbers) to achieve data compression.Unlike other column store databases where the dictionary is local to each data block, CarbonData maintains a global dictionary which provides opportunity for lazy conversion to actual values enabling all computation to be performed on the lightweight surrogate values.
+
+##### Dictionary generation
+
+
+
+
+
+##### MDK Indexing
+
+All the surrogate keys are byte packed to generate an MDK (Multi Dimensional Key) Index.
+
+Any non surrogate columns of String data types are compressed using one of the configured compression algorithms and stored.For those numeric columns where surrogates are not generated, such data is stored as it is after compression.
+
+
+
+##### Sorted MDK
+
+The data is sorted based on the MDK Index.Sorting helps for logical grouping of similar data and there by aids in faster look up during query.
+
+#### 
+
+##### Custom Columnar Encoding
+
+The Sorted MDK Index is split into each column.Unlike other stores where the column is compressed and stored as it is, CarbonData sorts this column data so that Binary Search can be performed on individual column data based on the filter conditions.This aids in magnitude increase in query performance and also in better compression.Since the individual column's data gets sorted, it is necessary to maintain the row mapping with the sorted MDK Index data in order to retrieve data from other columns which are not participating in filter.This row mapping is termed as **Inverted Index** and is stored along with the column data.The below picture depicts the logical column view.User has the option to **turn off** Inverted Index for such columns where filters are never applied or is very rare.In such cases, scanning would be sequential, but can aid in reducing the storage size(occupied due to inverted index data).
+
+#### 
+
+- ### CarbonData Storage Format
+
+ CarbonData has a unique storage structure which aids in efficient storage and retrieval of data.Please refer to [File Structure of CarbonData](#./file-structure-of-carbondata.md) for detailed information on the format.
+
+- ### Indexing
+
+ CarbonData maintains multiple indexes at multiple levels to assist in efficient pruning of unwanted data from scan during query.Also CarbonData has support for plugging in external indexing solutions to speed up the query process.
+
+ ##### Min-Max Indexing
+
+ Storing data along with index significantly accelerates query performance and reduces the I/O scans and CPU resources in case of filters in the query. CarbonData index consists of multiple levels of indices, a processing framework can leverage this index to reduce the number of tasks it needs to schedule and process. It can also do skip scan in more fine grained units (called blocklet) in task side scanning instead of scanning the whole file. **CarbonData maintains Min-Max Index for all the columns.**
+
+ CarbonData maintains a separate index file which contains the footer information for efficient IO reads.
+
+ Using the Min-Max info in these index files, two levels of filtering can be achieved.
+
+ Min-Max at the carbondata file level,to efficiently prune the files when the filter condition doesn't fall in the range.This information when maintained at the Spark Driver, will help to efficiently schedule the tasks for scanning
+
+ Min-Max at the blocklet level, to efficiently prune the blocklets when the filter condition doesn't fall in the range.This information when maintained at the executor can significantly reduce the amount unnecessary data processed by the executor tasks.
+
+
+
+ 
+
+- #### DataMaps
+
+ DataMap is a framework for indexing and also for statistics that can be used to add primary index (Blocklet Index) , secondary index type and statistical type to CarbonData.
+
+ DataMap is a standardized general interface which CarbonData uses to prune data blocks for scanning.
+
+ DataMaps are of 2 types:
+
+ **CG(Coarse Grained) DataMaps** Can prune data to the blocklet or to Page level.ie., Holds information for deciding which blocks/blocklets to be scanned.This DataMap is used in Spark Driver to decide the number of tasks to be scheduled.
+
+ **FG(Fine Grained) DataMaps** Can prune data to row level.This DataMap is used in Spark executor for scanning an fetching the data much faster.
+
+ Since DataMap interfaces are generalised, We can write a thin adaptor called as **DataMap Providers** to interface between CarbonData and other external Indexing engines. For eg., Lucene, Solr,ES,...
+
+ CarbonData has its own DSL to create and manage DataMaps.Please refer to [CarbonData DSL](#./datamap/datamap-management.md#overview) for more information.
+
+ The below diagram explains about the DataMap execution in CarbonData.
+
+ 
+
+- #### Update & Delete
+
+
+CarbonData supports Update and delete operations over big data.This functionality is not targetted for OLTP scenarios where high concurrent update/delete are required.Following are the assumptions considered when this feature is designed.
+
+1. Updates or Deletes are periodic and in Bulk
+2. Updates or Deletes are atomic
+3. Data is immediately visible
+4. Concurrent query to be allowed during an update or delete operation
+5. Single statement auto-commit support (not OLTP-style transaction)
+
+Since data stored in HDFS are immutable,data blocks cannot be updated in-place.Re-write of entire data block is not efficient for IO and also is a slow process.
+
+To over come these limitations, CarbonData adopts methodology of writing a delta file containing the rows to be deleted and another delta file containing the values to be updated with.During processing, These two delta files are merged with the main carbondata file and the correct result is returned for the query.
+
+The below diagram describes the process.
+
+
+
+
+
+## Integration with Big Data ecosystem
+
+Refer to Integration with [Spark](#./quick-start-guide.md#spark), [Presto](#./quick-start-guide.md#presto) for detailed information on integrating CarbonData with these execution engines.
+
+## Scenarios where CarbonData is suitable
+
+
+
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__intro').addClass('selected'); });
+</script>
\ No newline at end of file
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/language-manual.md
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diff --git a/src/site/markdown/language-manual.md b/src/site/markdown/language-manual.md
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@@ -0,0 +1,51 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one or more
+ contributor license agreements. See the NOTICE file distributed with
+ this work for additional information regarding copyright ownership.
+ The ASF licenses this file to you under the Apache License, Version 2.0
+ (the "License"); you may not use this file except in compliance with
+ the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+-->
+
+# Overview
+
+
+
+CarbonData has its own parser, in addition to Spark's SQL Parser, to parse and process certain Commands related to CarbonData table handling. You can interact with the SQL interface using the [command-line](https://spark.apache.org/docs/latest/sql-programming-guide.html#running-the-spark-sql-cli) or over [JDBC/ODBC](https://spark.apache.org/docs/latest/sql-programming-guide.html#running-the-thrift-jdbcodbc-server).
+
+- [Data Types](./supported-data-types-in-carbondata.md)
+- Data Definition Statements
+ - [DDL:](./ddl-of-carbondata.md)[Create](./ddl-of-carbondata.md#create-table),[Drop](./ddl-of-carbondata.md#drop-table),[Partition](./ddl-of-carbondata.md#partition),[Bucketing](./ddl-of-carbondata.md#bucketing),[Alter](./ddl-of-carbondata.md#alter-table),[CTAS](./ddl-of-carbondata.md#create-table-as-select),[External Table](./ddl-of-carbondata.md#create-external-table)
+ - Indexes
+ - [DataMaps](./datamap-management.md)
+ - [Bloom](./bloomfilter-datamap-guide.md)
+ - [Lucene](./lucene-datamap-guide.md)
+ - [Pre-Aggregate](./preaggregate-datamap-guide.md)
+ - [Time Series](./timeseries-datamap-guide.md)
+ - Materialized Views (MV)
+ - [Streaming](./streaming-guide.md)
+- Data Manipulation Statements
+ - [DML:](./dml-of-carbondata.md) [Load](./dml-of-carbondata.md#load-data), [Insert](./ddl-of-carbondata.md#insert-overwrite), [Update](./dml-of-carbondata.md#update), [Delete](./dml-of-carbondata.md#delete)
+ - [Segment Management](./segment-management-on-carbondata.md)
+- [Configuration Properties](./configuration-parameters.md)
+
+<script>
+$(function() {
+ // Show selected style on nav item
+ $('.b-nav__docs').addClass('selected');
+
+ // Display docs subnav items
+ if (!$('.b-nav__docs').parent().hasClass('nav__item__with__subs--expanded')) {
+ $('.b-nav__docs').parent().toggleClass('nav__item__with__subs--expanded');
+ }
+});
+</script>
+
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/lucene-datamap-guide.md
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diff --git a/src/site/markdown/lucene-datamap-guide.md b/src/site/markdown/lucene-datamap-guide.md
index 06cd194..248c8e5 100644
--- a/src/site/markdown/lucene-datamap-guide.md
+++ b/src/site/markdown/lucene-datamap-guide.md
@@ -173,4 +173,15 @@ release, user can do as following:
3. Create the lucene datamap again by `CREATE DATAMAP` command.
Basically, user can manually trigger the operation by re-building the datamap.
+<script>
+$(function() {
+ // Show selected style on nav item
+ $('.b-nav__datamap').addClass('selected');
+
+ if (!$('.b-nav__datamap').parent().hasClass('nav__item__with__subs--expanded')) {
+ // Display datamap subnav items
+ $('.b-nav__datamap').parent().toggleClass('nav__item__with__subs--expanded');
+ }
+});
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/performance-tuning.md
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diff --git a/src/site/markdown/performance-tuning.md b/src/site/markdown/performance-tuning.md
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@@ -0,0 +1,183 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one or more
+ contributor license agreements. See the NOTICE file distributed with
+ this work for additional information regarding copyright ownership.
+ The ASF licenses this file to you under the Apache License, Version 2.0
+ (the "License"); you may not use this file except in compliance with
+ the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+-->
+
+# Useful Tips
+ This tutorial guides you to create CarbonData Tables and optimize performance.
+ The following sections will elaborate on the below topics :
+
+ * [Suggestions to create CarbonData Table](#suggestions-to-create-carbondata-table)
+ * [Configuration for Optimizing Data Loading performance for Massive Data](#configuration-for-optimizing-data-loading-performance-for-massive-data)
+ * [Optimizing Query Performance](#configurations-for-optimizing-carbondata-performance)
+
+## Suggestions to Create CarbonData Table
+
+ For example, the results of the analysis for table creation with dimensions ranging from 10 thousand to 10 billion rows and 100 to 300 columns have been summarized below.
+ The following table describes some of the columns from the table used.
+
+ - **Table Column Description**
+
+| Column Name | Data Type | Cardinality | Attribution |
+|-------------|---------------|-------------|-------------|
+| msisdn | String | 30 million | Dimension |
+| BEGIN_TIME | BigInt | 10 Thousand | Dimension |
+| HOST | String | 1 million | Dimension |
+| Dime_1 | String | 1 Thousand | Dimension |
+| counter_1 | Decimal | NA | Measure |
+| counter_2 | Numeric(20,0) | NA | Measure |
+| ... | ... | NA | Measure |
+| counter_100 | Decimal | NA | Measure |
+
+
+ - **Put the frequently-used column filter in the beginning of SORT_COLUMNS**
+
+ For example, MSISDN filter is used in most of the query then we must put the MSISDN as the first column in SORT_COLUMNS property.
+ The create table command can be modified as suggested below :
+
+ ```
+ create table carbondata_table(
+ msisdn String,
+ BEGIN_TIME bigint,
+ HOST String,
+ Dime_1 String,
+ counter_1, Decimal
+ ...
+
+ )STORED BY 'carbondata'
+ TBLPROPERTIES ('SORT_COLUMNS'='msisdn, Dime_1')
+ ```
+
+ Now the query with MSISDN in the filter will be more efficient.
+
+ - **Put the frequently-used columns in the order of low to high cardinality in SORT_COLUMNS**
+
+ If the table in the specified query has multiple columns which are frequently used to filter the results, it is suggested to put
+ the columns in the order of cardinality low to high in SORT_COLUMNS configuration. This ordering of frequently used columns improves the compression ratio and
+ enhances the performance of queries with filter on these columns.
+
+ For example, if MSISDN, HOST and Dime_1 are frequently-used columns, then the column order of table is suggested as
+ Dime_1>HOST>MSISDN, because Dime_1 has the lowest cardinality.
+ The create table command can be modified as suggested below :
+
+ ```
+ create table carbondata_table(
+ msisdn String,
+ BEGIN_TIME bigint,
+ HOST String,
+ Dime_1 String,
+ counter_1, Decimal
+ ...
+
+ )STORED BY 'carbondata'
+ TBLPROPERTIES ('SORT_COLUMNS'='Dime_1, HOST, MSISDN')
+ ```
+
+ - **For measure type columns with non high accuracy, replace Numeric(20,0) data type with Double data type**
+
+ For columns of measure type, not requiring high accuracy, it is suggested to replace Numeric data type with Double to enhance query performance.
+ The create table command can be modified as below :
+
+```
+ create table carbondata_table(
+ Dime_1 String,
+ BEGIN_TIME bigint,
+ END_TIME bigint,
+ HOST String,
+ MSISDN String,
+ counter_1 decimal,
+ counter_2 double,
+ ...
+ )STORED BY 'carbondata'
+ TBLPROPERTIES ('SORT_COLUMNS'='Dime_1, HOST, MSISDN')
+```
+ The result of performance analysis of test-case shows reduction in query execution time from 15 to 3 seconds, thereby improving performance by nearly 5 times.
+
+ - **Columns of incremental character should be re-arranged at the end of dimensions**
+
+ Consider the following scenario where data is loaded each day and the begin_time is incremental for each load, it is suggested to put begin_time at the end of dimensions.
+ Incremental values are efficient in using min/max index. The create table command can be modified as below :
+
+ ```
+ create table carbondata_table(
+ Dime_1 String,
+ HOST String,
+ MSISDN String,
+ counter_1 double,
+ counter_2 double,
+ BEGIN_TIME bigint,
+ END_TIME bigint,
+ ...
+ counter_100 double
+ )STORED BY 'carbondata'
+ TBLPROPERTIES ('SORT_COLUMNS'='Dime_1, HOST, MSISDN')
+ ```
+
+ **NOTE:**
+ + BloomFilter can be created to enhance performance for queries with precise equal/in conditions. You can find more information about it in BloomFilter datamap [document](https://github.com/apache/carbondata/blob/master/docs/datamap/bloomfilter-datamap-guide.md).
+
+
+## Configuration for Optimizing Data Loading performance for Massive Data
+
+
+ CarbonData supports large data load, in this process sorting data while loading consumes a lot of memory and disk IO and
+ this can result sometimes in "Out Of Memory" exception.
+ If you do not have much memory to use, then you may prefer to slow the speed of data loading instead of data load failure.
+ You can configure CarbonData by tuning following properties in carbon.properties file to get a better performance.
+
+| Parameter | Default Value | Description/Tuning |
+|-----------|-------------|--------|
+|carbon.number.of.cores.while.loading|Default: 2.This value should be >= 2|Specifies the number of cores used for data processing during data loading in CarbonData. |
+|carbon.sort.size|Default: 100000. The value should be >= 100.|Threshold to write local file in sort step when loading data|
+|carbon.sort.file.write.buffer.size|Default: 50000.|DataOutputStream buffer. |
+|carbon.merge.sort.reader.thread|Default: 3 |Specifies the number of cores used for temp file merging during data loading in CarbonData.|
+|carbon.merge.sort.prefetch|Default: true | You may want set this value to false if you have not enough memory|
+
+ For example, if there are 10 million records, and i have only 16 cores, 64GB memory, will be loaded to CarbonData table.
+ Using the default configuration always fail in sort step. Modify carbon.properties as suggested below:
+
+ ```
+ carbon.merge.sort.reader.thread=1
+ carbon.sort.size=5000
+ carbon.sort.file.write.buffer.size=5000
+ carbon.merge.sort.prefetch=false
+ ```
+
+## Configurations for Optimizing CarbonData Performance
+
+ Recently we did some performance POC on CarbonData for Finance and telecommunication Field. It involved detailed queries and aggregation
+ scenarios. After the completion of POC, some of the configurations impacting the performance have been identified and tabulated below :
+
+| Parameter | Location | Used For | Description | Tuning |
+|----------------------------------------------|-----------------------------------|---------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
+| carbon.sort.intermediate.files.limit | spark/carbonlib/carbon.properties | Data loading | During the loading of data, local temp is used to sort the data. This number specifies the minimum number of intermediate files after which the merge sort has to be initiated. | Increasing the parameter to a higher value will improve the load performance. For example, when we increase the value from 20 to 100, it increases the data load performance from 35MB/S to more than 50MB/S. Higher values of this parameter consumes more memory during the load. |
+| carbon.number.of.cores.while.loading | spark/carbonlib/carbon.properties | Data loading | Specifies the number of cores used for data processing during data loading in CarbonData. | If you have more number of CPUs, then you can increase the number of CPUs, which will increase the performance. For example if we increase the value from 2 to 4 then the CSV reading performance can increase about 1 times |
+| carbon.compaction.level.threshold | spark/carbonlib/carbon.properties | Data loading and Querying | For minor compaction, specifies the number of segments to be merged in stage 1 and number of compacted segments to be merged in stage 2. | Each CarbonData load will create one segment, if every load is small in size it will generate many small file over a period of time impacting the query performance. Configuring this parameter will merge the small segment to one big segment which will sort the data and improve the performance. For Example in one telecommunication scenario, the performance improves about 2 times after minor compaction. |
+| spark.sql.shuffle.partitions | spark/conf/spark-defaults.conf | Querying | The number of task started when spark shuffle. | The value can be 1 to 2 times as much as the executor cores. In an aggregation scenario, reducing the number from 200 to 32 reduced the query time from 17 to 9 seconds. |
+| spark.executor.instances/spark.executor.cores/spark.executor.memory | spark/conf/spark-defaults.conf | Querying | The number of executors, CPU cores, and memory used for CarbonData query. | In the bank scenario, we provide the 4 CPUs cores and 15 GB for each executor which can get good performance. This 2 value does not mean more the better. It needs to be configured properly in case of limited resources. For example, In the bank scenario, it has enough CPU 32 cores each node but less memory 64 GB each node. So we cannot give more CPU but less memory. For example, when 4 cores and 12GB for each executor. It sometimes happens GC during the query which impact the query performance very much from the 3 second to more than 15 seconds. In this scenario need to increase the memory or decrease the CPU cores. |
+| carbon.detail.batch.size | spark/carbonlib/carbon.properties | Data loading | The buffer size to store records, returned from the block scan. | In limit scenario this parameter is very important. For example your query limit is 1000. But if we set this value to 3000 that means we get 3000 records from scan but spark will only take 1000 rows. So the 2000 remaining are useless. In one Finance test case after we set it to 100, in the limit 1000 scenario the performance increase about 2 times in comparison to if we set this value to 12000. |
+| carbon.use.local.dir | spark/carbonlib/carbon.properties | Data loading | Whether use YARN local directories for multi-table load disk load balance | If this is set it to true CarbonData will use YARN local directories for multi-table load disk load balance, that will improve the data load performance. |
+| carbon.use.multiple.temp.dir | spark/carbonlib/carbon.properties | Data loading | Whether to use multiple YARN local directories during table data loading for disk load balance | After enabling 'carbon.use.local.dir', if this is set to true, CarbonData will use all YARN local directories during data load for disk load balance, that will improve the data load performance. Please enable this property when you encounter disk hotspot problem during data loading. |
+| carbon.sort.temp.compressor | spark/carbonlib/carbon.properties | Data loading | Specify the name of compressor to compress the intermediate sort temporary files during sort procedure in data loading. | The optional values are 'SNAPPY','GZIP','BZIP2','LZ4','ZSTD' and empty. By default, empty means that Carbondata will not compress the sort temp files. This parameter will be useful if you encounter disk bottleneck. |
+| carbon.load.skewedDataOptimization.enabled | spark/carbonlib/carbon.properties | Data loading | Whether to enable size based block allocation strategy for data loading. | When loading, carbondata will use file size based block allocation strategy for task distribution. It will make sure that all the executors process the same size of data -- It's useful if the size of your input data files varies widely, say 1MB~1GB. |
+| carbon.load.min.size.enabled | spark/carbonlib/carbon.properties | Data loading | Whether to enable node minumun input data size allocation strategy for data loading.| When loading, carbondata will use node minumun input data size allocation strategy for task distribution. It will make sure the node load the minimum amount of data -- It's useful if the size of your input data files very small, say 1MB~256MB,Avoid generating a large number of small files. |
+
+ Note: If your CarbonData instance is provided only for query, you may specify the property 'spark.speculation=true' which is in conf directory of spark.
+
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__perf').addClass('selected'); });
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/preaggregate-datamap-guide.md
----------------------------------------------------------------------
diff --git a/src/site/markdown/preaggregate-datamap-guide.md b/src/site/markdown/preaggregate-datamap-guide.md
index ff4c28e..9c7a5f8 100644
--- a/src/site/markdown/preaggregate-datamap-guide.md
+++ b/src/site/markdown/preaggregate-datamap-guide.md
@@ -126,7 +126,7 @@ kinds of DataMap:
a. 'path' is used to specify the store location of the datamap.('path'='/location/').
b. 'partitioning' when set to false enables user to disable partitioning of the datamap.
Default value is true for this property.
-2. timeseries, for timeseries roll-up table. Please refer to [Timeseries DataMap](https://github.com/apache/carbondata/blob/master/docs/datamap/timeseries-datamap-guide.md)
+2. timeseries, for timeseries roll-up table. Please refer to [Timeseries DataMap](./timeseries-datamap-guide.md)
DataMap can be dropped using following DDL
```
@@ -271,3 +271,14 @@ release, user can do as following:
Basically, user can manually trigger the operation by re-building the datamap.
+<script>
+$(function() {
+ // Show selected style on nav item
+ $('.b-nav__datamap').addClass('selected');
+
+ if (!$('.b-nav__datamap').parent().hasClass('nav__item__with__subs--expanded')) {
+ // Display datamap subnav items
+ $('.b-nav__datamap').parent().toggleClass('nav__item__with__subs--expanded');
+ }
+});
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/quick-start-guide.md
----------------------------------------------------------------------
diff --git a/src/site/markdown/quick-start-guide.md b/src/site/markdown/quick-start-guide.md
index 84f871d..7ac5a3f 100644
--- a/src/site/markdown/quick-start-guide.md
+++ b/src/site/markdown/quick-start-guide.md
@@ -7,7 +7,7 @@
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
-
+
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@@ -16,10 +16,11 @@
-->
# Quick Start
-This tutorial provides a quick introduction to using CarbonData.
+This tutorial provides a quick introduction to using CarbonData.To follow along with this guide, first download a packaged release of CarbonData from the [CarbonData website](https://dist.apache.org/repos/dist/release/carbondata/).Alternatively it can be created following [Building CarbonData](https://github.com/apache/carbondata/tree/master/build) steps.
## Prerequisites
-* [Installation and building CarbonData](https://github.com/apache/carbondata/blob/master/build).
+* Spark 2.2.1 version is installed and running.CarbonData supports Spark versions upto 2.2.1.Please follow steps described in [Spark docs website](https://spark.apache.org/docs/latest) for installing and running Spark.
+
* Create a sample.csv file using the following commands. The CSV file is required for loading data into CarbonData.
```
@@ -32,7 +33,30 @@ This tutorial provides a quick introduction to using CarbonData.
EOF
```
-## Interactive Analysis with Spark Shell Version 2.1
+## Deployment modes
+
+CarbonData can be integrated with Spark and Presto Execution Engines.The below documentation guides on Installing and Configuring with these execution engines.
+
+### Spark
+
+[Installing and Configuring CarbonData to run locally with Spark Shell](#installing-and-configuring-carbondata-to-run-locally-with-spark-shell)
+
+[Installing and Configuring CarbonData on Standalone Spark Cluster](#installing-and-configuring-carbondata-on-standalone-spark-cluster)
+
+[Installing and Configuring CarbonData on Spark on YARN Cluster](#installing-and-configuring-carbondata-on-spark-on-yarn-cluster)
+
+
+### Presto
+[Installing and Configuring CarbonData on Presto](#installing-and-configuring-carbondata-on-presto)
+
+
+## Querying Data
+
+[Query Execution using CarbonData Thrift Server](#query-execution-using-carbondata-thrift-server)
+
+##
+
+## Installing and Configuring CarbonData to run locally with Spark Shell
Apache Spark Shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. Please visit [Apache Spark Documentation](http://spark.apache.org/docs/latest/) for more details on Spark shell.
@@ -43,7 +67,7 @@ Start Spark shell by running the following command in the Spark directory:
```
./bin/spark-shell --jars <carbondata assembly jar path>
```
-**NOTE**: Assembly jar will be available after [building CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) and can be copied from `./assembly/target/scala-2.1x/carbondata_xxx.jar`
+**NOTE**: Path where packaged release of CarbonData was downloaded or assembly jar will be available after [building CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) and can be copied from `./assembly/target/scala-2.1x/carbondata_xxx.jar`
In this shell, SparkSession is readily available as `spark` and Spark context is readily available as `sc`.
@@ -62,7 +86,7 @@ import org.apache.spark.sql.CarbonSession._
val carbon = SparkSession.builder().config(sc.getConf)
.getOrCreateCarbonSession("<hdfs store path>")
```
-**NOTE**: By default metastore location is pointed to `../carbon.metastore`, user can provide own metastore location to CarbonSession like `SparkSession.builder().config(sc.getConf)
+**NOTE**: By default metastore location points to `../carbon.metastore`, user can provide own metastore location to CarbonSession like `SparkSession.builder().config(sc.getConf)
.getOrCreateCarbonSession("<hdfs store path>", "<local metastore path>")`
#### Executing Queries
@@ -86,7 +110,7 @@ scala>carbon.sql("LOAD DATA INPATH '/path/to/sample.csv'
INTO TABLE test_table")
```
**NOTE**: Please provide the real file path of `sample.csv` for the above script.
-If you get "tablestatus.lock" issue, please refer to [troubleshooting](troubleshooting.md)
+If you get "tablestatus.lock" issue, please refer to [FAQ](faq.md)
###### Query Data from a Table
@@ -97,3 +121,317 @@ scala>carbon.sql("SELECT city, avg(age), sum(age)
FROM test_table
GROUP BY city").show()
```
+
+
+
+## Installing and Configuring CarbonData on Standalone Spark Cluster
+
+### Prerequisites
+
+- Hadoop HDFS and Yarn should be installed and running.
+- Spark should be installed and running on all the cluster nodes.
+- CarbonData user should have permission to access HDFS.
+
+### Procedure
+
+1. [Build the CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) project and get the assembly jar from `./assembly/target/scala-2.1x/carbondata_xxx.jar`.
+
+2. Copy `./assembly/target/scala-2.1x/carbondata_xxx.jar` to `$SPARK_HOME/carbonlib` folder.
+
+ **NOTE**: Create the carbonlib folder if it does not exist inside `$SPARK_HOME` path.
+
+3. Add the carbonlib folder path in the Spark classpath. (Edit `$SPARK_HOME/conf/spark-env.sh` file and modify the value of `SPARK_CLASSPATH` by appending `$SPARK_HOME/carbonlib/*` to the existing value)
+
+4. Copy the `./conf/carbon.properties.template` file from CarbonData repository to `$SPARK_HOME/conf/` folder and rename the file to `carbon.properties`.
+
+5. Repeat Step 2 to Step 5 in all the nodes of the cluster.
+
+6. In Spark node[master], configure the properties mentioned in the following table in `$SPARK_HOME/conf/spark-defaults.conf` file.
+
+| Property | Value | Description |
+| ------------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| spark.driver.extraJavaOptions | `-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` | A string of extra JVM options to pass to the driver. For instance, GC settings or other logging. |
+| spark.executor.extraJavaOptions | `-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` | A string of extra JVM options to pass to executors. For instance, GC settings or other logging. **NOTE**: You can enter multiple values separated by space. |
+
+1. Add the following properties in `$SPARK_HOME/conf/carbon.properties` file:
+
+| Property | Required | Description | Example | Remark |
+| -------------------- | -------- | ------------------------------------------------------------ | ------------------------------------ | ----------------------------- |
+| carbon.storelocation | NO | Location where data CarbonData will create the store and write the data in its own format. If not specified then it takes spark.sql.warehouse.dir path. | hdfs://HOSTNAME:PORT/Opt/CarbonStore | Propose to set HDFS directory |
+
+1. Verify the installation. For example:
+
+```
+./spark-shell --master spark://HOSTNAME:PORT --total-executor-cores 2
+--executor-memory 2G
+```
+
+**NOTE**: Make sure you have permissions for CarbonData JARs and files through which driver and executor will start.
+
+
+
+## Installing and Configuring CarbonData on Spark on YARN Cluster
+
+ This section provides the procedure to install CarbonData on "Spark on YARN" cluster.
+
+### Prerequisites
+
+- Hadoop HDFS and Yarn should be installed and running.
+- Spark should be installed and running in all the clients.
+- CarbonData user should have permission to access HDFS.
+
+### Procedure
+
+ The following steps are only for Driver Nodes. (Driver nodes are the one which starts the spark context.)
+
+1. [Build the CarbonData](https://github.com/apache/carbondata/blob/master/build/README.md) project and get the assembly jar from `./assembly/target/scala-2.1x/carbondata_xxx.jar` and copy to `$SPARK_HOME/carbonlib` folder.
+
+ **NOTE**: Create the carbonlib folder if it does not exists inside `$SPARK_HOME` path.
+
+2. Copy the `./conf/carbon.properties.template` file from CarbonData repository to `$SPARK_HOME/conf/` folder and rename the file to `carbon.properties`.
+
+3. Create `tar.gz` file of carbonlib folder and move it inside the carbonlib folder.
+
+```
+cd $SPARK_HOME
+tar -zcvf carbondata.tar.gz carbonlib/
+mv carbondata.tar.gz carbonlib/
+```
+
+1. Configure the properties mentioned in the following table in `$SPARK_HOME/conf/spark-defaults.conf` file.
+
+| Property | Description | Value |
+| ------------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ |
+| spark.master | Set this value to run the Spark in yarn cluster mode. | Set yarn-client to run the Spark in yarn cluster mode. |
+| spark.yarn.dist.files | Comma-separated list of files to be placed in the working directory of each executor. | `$SPARK_HOME/conf/carbon.properties` |
+| spark.yarn.dist.archives | Comma-separated list of archives to be extracted into the working directory of each executor. | `$SPARK_HOME/carbonlib/carbondata.tar.gz` |
+| spark.executor.extraJavaOptions | A string of extra JVM options to pass to executors. For instance **NOTE**: You can enter multiple values separated by space. | `-Dcarbon.properties.filepath = carbon.properties` |
+| spark.executor.extraClassPath | Extra classpath entries to prepend to the classpath of executors. **NOTE**: If SPARK_CLASSPATH is defined in spark-env.sh, then comment it and append the values in below parameter spark.driver.extraClassPath | `carbondata.tar.gz/carbonlib/*` |
+| spark.driver.extraClassPath | Extra classpath entries to prepend to the classpath of the driver. **NOTE**: If SPARK_CLASSPATH is defined in spark-env.sh, then comment it and append the value in below parameter spark.driver.extraClassPath. | `$SPARK_HOME/carbonlib/*` |
+| spark.driver.extraJavaOptions | A string of extra JVM options to pass to the driver. For instance, GC settings or other logging. | `-Dcarbon.properties.filepath = $SPARK_HOME/conf/carbon.properties` |
+
+1. Add the following properties in `$SPARK_HOME/conf/carbon.properties`:
+
+| Property | Required | Description | Example | Default Value |
+| -------------------- | -------- | ------------------------------------------------------------ | ------------------------------------ | ----------------------------- |
+| carbon.storelocation | NO | Location where CarbonData will create the store and write the data in its own format. If not specified then it takes spark.sql.warehouse.dir path. | hdfs://HOSTNAME:PORT/Opt/CarbonStore | Propose to set HDFS directory |
+
+1. Verify the installation.
+
+```
+ ./bin/spark-shell --master yarn-client --driver-memory 1g
+ --executor-cores 2 --executor-memory 2G
+```
+
+ **NOTE**: Make sure you have permissions for CarbonData JARs and files through which driver and executor will start.
+
+
+
+## Query Execution Using CarbonData Thrift Server
+
+### Starting CarbonData Thrift Server.
+
+ a. cd `$SPARK_HOME`
+
+ b. Run the following command to start the CarbonData thrift server.
+
+```
+./bin/spark-submit
+--class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
+$SPARK_HOME/carbonlib/$CARBON_ASSEMBLY_JAR <carbon_store_path>
+```
+
+| Parameter | Description | Example |
+| ------------------- | ------------------------------------------------------------ | ---------------------------------------------------------- |
+| CARBON_ASSEMBLY_JAR | CarbonData assembly jar name present in the `$SPARK_HOME/carbonlib/` folder. | carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar |
+| carbon_store_path | This is a parameter to the CarbonThriftServer class. This a HDFS path where CarbonData files will be kept. Strongly Recommended to put same as carbon.storelocation parameter of carbon.properties. If not specified then it takes spark.sql.warehouse.dir path. | `hdfs://<host_name>:port/user/hive/warehouse/carbon.store` |
+
+**NOTE**: From Spark 1.6, by default the Thrift server runs in multi-session mode. Which means each JDBC/ODBC connection owns a copy of their own SQL configuration and temporary function registry. Cached tables are still shared though. If you prefer to run the Thrift server in single-session mode and share all SQL configuration and temporary function registry, please set option `spark.sql.hive.thriftServer.singleSession` to `true`. You may either add this option to `spark-defaults.conf`, or pass it to `spark-submit.sh` via `--conf`:
+
+```
+./bin/spark-submit
+--conf spark.sql.hive.thriftServer.singleSession=true
+--class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
+$SPARK_HOME/carbonlib/$CARBON_ASSEMBLY_JAR <carbon_store_path>
+```
+
+**But** in single-session mode, if one user changes the database from one connection, the database of the other connections will be changed too.
+
+**Examples**
+
+- Start with default memory and executors.
+
+```
+./bin/spark-submit
+--class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
+$SPARK_HOME/carbonlib
+/carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar
+hdfs://<host_name>:port/user/hive/warehouse/carbon.store
+```
+
+- Start with Fixed executors and resources.
+
+```
+./bin/spark-submit
+--class org.apache.carbondata.spark.thriftserver.CarbonThriftServer
+--num-executors 3 --driver-memory 20g --executor-memory 250g
+--executor-cores 32
+/srv/OSCON/BigData/HACluster/install/spark/sparkJdbc/lib
+/carbondata_2.xx-x.x.x-SNAPSHOT-shade-hadoop2.7.2.jar
+hdfs://<host_name>:port/user/hive/warehouse/carbon.store
+```
+
+### Connecting to CarbonData Thrift Server Using Beeline.
+
+```
+ cd $SPARK_HOME
+ ./sbin/start-thriftserver.sh
+ ./bin/beeline -u jdbc:hive2://<thriftserver_host>:port
+
+ Example
+ ./bin/beeline -u jdbc:hive2://10.10.10.10:10000
+```
+
+
+
+## Installing and Configuring CarbonData on Presto
+
+
+* ### Installing Presto
+
+ 1. Download the 0.187 version of Presto using:
+ `wget https://repo1.maven.org/maven2/com/facebook/presto/presto-server/0.187/presto-server-0.187.tar.gz`
+
+ 2. Extract Presto tar file: `tar zxvf presto-server-0.187.tar.gz`.
+
+ 3. Download the Presto CLI for the coordinator and name it presto.
+
+ ```
+ wget https://repo1.maven.org/maven2/com/facebook/presto/presto-cli/0.187/presto-cli-0.187-executable.jar
+
+ mv presto-cli-0.187-executable.jar presto
+
+ chmod +x presto
+ ```
+
+### Create Configuration Files
+
+ 1. Create `etc` folder in presto-server-0.187 directory.
+ 2. Create `config.properties`, `jvm.config`, `log.properties`, and `node.properties` files.
+ 3. Install uuid to generate a node.id.
+
+ ```
+ sudo apt-get install uuid
+
+ uuid
+ ```
+
+
+##### Contents of your node.properties file
+
+ ```
+ node.environment=production
+ node.id=<generated uuid>
+ node.data-dir=/home/ubuntu/data
+ ```
+
+##### Contents of your jvm.config file
+
+ ```
+ -server
+ -Xmx16G
+ -XX:+UseG1GC
+ -XX:G1HeapRegionSize=32M
+ -XX:+UseGCOverheadLimit
+ -XX:+ExplicitGCInvokesConcurrent
+ -XX:+HeapDumpOnOutOfMemoryError
+ -XX:OnOutOfMemoryError=kill -9 %p
+ ```
+
+##### Contents of your log.properties file
+ ```
+ com.facebook.presto=INFO
+ ```
+
+ The default minimum level is `INFO`. There are four levels: `DEBUG`, `INFO`, `WARN` and `ERROR`.
+
+### Coordinator Configurations
+
+##### Contents of your config.properties
+ ```
+ coordinator=true
+ node-scheduler.include-coordinator=false
+ http-server.http.port=8086
+ query.max-memory=50GB
+ query.max-memory-per-node=2GB
+ discovery-server.enabled=true
+ discovery.uri=<coordinator_ip>:8086
+ ```
+The options `node-scheduler.include-coordinator=false` and `coordinator=true` indicate that the node is the coordinator and tells the coordinator not to do any of the computation work itself and to use the workers.
+
+**Note**: It is recommended to set `query.max-memory-per-node` to half of the JVM config max memory, though the workload is highly concurrent, lower value for `query.max-memory-per-node` is to be used.
+
+Also relation between below two configuration-properties should be like:
+If, `query.max-memory-per-node=30GB`
+Then, `query.max-memory=<30GB * number of nodes>`.
+
+### Worker Configurations
+
+##### Contents of your config.properties
+
+ ```
+ coordinator=false
+ http-server.http.port=8086
+ query.max-memory=50GB
+ query.max-memory-per-node=2GB
+ discovery.uri=<coordinator_ip>:8086
+ ```
+
+**Note**: `jvm.config` and `node.properties` files are same for all the nodes (worker + coordinator). All the nodes should have different `node.id`.(generated by uuid command).
+
+### Catalog Configurations
+
+1. Create a folder named `catalog` in etc directory of presto on all the nodes of the cluster including the coordinator.
+
+##### Configuring Carbondata in Presto
+1. Create a file named `carbondata.properties` in the `catalog` folder and set the required properties on all the nodes.
+
+### Add Plugins
+
+1. Create a directory named `carbondata` in plugin directory of presto.
+2. Copy `carbondata` jars to `plugin/carbondata` directory on all nodes.
+
+### Start Presto Server on all nodes
+
+```
+./presto-server-0.187/bin/launcher start
+```
+To run it as a background process.
+
+```
+./presto-server-0.187/bin/launcher run
+```
+To run it in foreground.
+
+### Start Presto CLI
+```
+./presto
+```
+To connect to carbondata catalog use the following command:
+
+```
+./presto --server <coordinator_ip>:8086 --catalog carbondata --schema <schema_name>
+```
+Execute the following command to ensure the workers are connected.
+
+```
+select * from system.runtime.nodes;
+```
+Now you can use the Presto CLI on the coordinator to query data sources in the catalog using the Presto workers.
+
+**Note :** Create Tables and data loads should be done before executing queries as we can not create carbon table from this interface.
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__quickstart').addClass('selected'); });
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/release-guide.md
----------------------------------------------------------------------
diff --git a/src/site/markdown/release-guide.md b/src/site/markdown/release-guide.md
new file mode 100644
index 0000000..40a9058
--- /dev/null
+++ b/src/site/markdown/release-guide.md
@@ -0,0 +1,428 @@
+<!--
+ Licensed to the Apache Software Foundation (ASF) under one or more
+ contributor license agreements. See the NOTICE file distributed with
+ this work for additional information regarding copyright ownership.
+ The ASF licenses this file to you under the Apache License, Version 2.0
+ (the "License"); you may not use this file except in compliance with
+ the License. You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+-->
+
+# Apache CarbonData Release Guide
+
+Apache CarbonData periodically declares and publishes releases.
+
+Each release is executed by a _Release Manager_, who is selected among the CarbonData committers.
+ This document describes the process that the Release Manager follows to perform a release. Any
+ changes to this process should be discussed and adopted on the
+ [dev@ mailing list](mailto:dev@carbondata.apache.org).
+
+Please remember that publishing software has legal consequences. This guide complements the
+foundation-wide [Product Release Policy](http://www.apache.org/dev/release.html) and [Release
+Distribution Policy](http://www.apache.org/dev/release-distribution).
+
+## Decide to release
+
+Deciding to release and selecting a Release Manager is the first step of the release process.
+This is a consensus-based decision of the entire community.
+
+Anybody can propose a release on the dev@ mailing list, giving a solid argument and nominating a
+committer as the Release Manager (including themselves). There's no formal process, no vote
+requirements, and no timing requirements. Any objections should be resolved by consensus before
+starting the release.
+
+_Checklist to proceed to next step:_
+
+1. Community agrees to release
+2. Community selects a Release Manager
+
+## Prepare for the release
+
+Before your first release, you should perform one-time configuration steps. This will set up your
+ security keys for signing the artifacts and access release repository.
+
+To prepare for each release, you should audit the project status in the Jira, and do necessary
+bookkeeping. Finally, you should tag a release.
+
+### One-time setup instructions
+
+#### GPG Key
+
+You need to have a GPG key to sign the release artifacts. Please be aware of the ASF-wide
+[release signing guidelines](https://www.apache.org/dev/release-signing.html). If you don't have
+a GPG key associated with your Apache account, please create one according to the guidelines.
+
+Determine your Apache GPG key and key ID, as follows:
+
+```
+gpg --list-keys
+```
+
+This will list your GPG keys. One of these should reflect your Apache account, for example:
+
+```
+pub 2048R/845E6689 2016-02-23
+uid Nomen Nescio <an...@apache.org>
+sub 2048R/BA4D50BE 2016-02-23
+```
+
+Here, the key ID is the 8-digit hex string in the `pub` line: `845E6689`.
+
+Now, add your Apache GPG key to the CarbonData's `KEYS` file in `dev` and `release` repositories
+at `dist.apache.org`. Follow the instructions listed at the top of these files.
+
+Configure `git` to use this key when signing code by giving it your key ID, as follows:
+
+```
+git config --global user.signingkey 845E6689
+```
+
+You may drop the `--global` option if you'd prefer to use this key for the current repository only.
+
+You may wish to start `gpg-agent` to unlock your GPG key only once using your passphrase.
+Otherwise, you may need to enter this passphrase several times. The setup of `gpg-agent` varies
+based on operating system, but may be something like this:
+
+```
+eval $(gpg-agent --daemon --no-grab --write-env-file $HOME/.gpg-agent-info)
+export GPG_TTY=$(tty)
+export GPG_AGENT_INFO
+```
+
+#### Access to Apache Nexus
+
+Configure access to the [Apache Nexus repository](https://repository.apache.org), used for
+staging repository and promote the artifacts to Maven Central.
+
+1. You log in with your Apache account.
+2. Confirm you have appropriate access by finding `org.apache.carbondata` under `Staging Profiles`.
+3. Navigate to your `Profile` (top right dropdown menu of the page).
+4. Choose `User Token` from the dropdown, then click `Access User Token`. Copy a snippet of the
+Maven XML configuration block.
+5. Insert this snippet twice into your global Maven `settings.xml` file, typically `${HOME]/
+.m2/settings.xml`. The end result should look like this, where `TOKEN_NAME` and `TOKEN_PASSWORD`
+are your secret tokens:
+
+```
+ <settings>
+ <servers>
+ <server>
+ <id>apache.releases.https</id>
+ <username>TOKEN_NAME</username>
+ <password>TOKEN_PASSWORD</password>
+ </server>
+ <server>
+ <id>apache.snapshots.https</id>
+ <username>TOKEN_NAME</username>
+ <password>TOKEN_PASSWORD</password>
+ </server>
+ </servers>
+ </settings>
+```
+
+#### Create a new version in Jira
+
+When contributors resolve an issue in Jira, they are tagging it with a release that will contain
+their changes. With the release currently underway, new issues should be resolved against a
+subsequent future release. Therefore, you should create a release item for this subsequent
+release, as follows:
+
+1. In Jira, navigate to `CarbonData > Administration > Versions`.
+2. Add a new release: choose the next minor version number compared to the one currently
+underway, select today's date as the `Start Date`, and choose `Add`.
+
+#### Triage release-blocking issues in Jira
+
+There could be outstanding release-blocking issues, which should be triaged before proceeding to
+build the release. We track them by assigning a specific `Fix Version` field even before the
+issue is resolved.
+
+The list of release-blocking issues is available at the [version status page](https://issues.apache.org/jira/browse/CARBONDATA/?selectedTab=com.atlassian.jira.jira-projects-plugin:versions-panel).
+Triage each unresolved issue with one of the following resolutions:
+
+* If the issue has been resolved and Jira was not updated, resolve it accordingly.
+* If the issue has not been resolved and it is acceptable to defer until the next release, update
+ the `Fix Version` field to the new version you just created. Please consider discussing this
+ with stakeholders and the dev@ mailing list, as appropriate.
+* If the issue has not been resolved and it is not acceptable to release until it is fixed, the
+ release cannot proceed. Instead, work with the CarbonData community to resolve the issue.
+
+#### Review Release Notes in Jira
+
+Jira automatically generates Release Notes based on the `Fix Version` applied to the issues.
+Release Notes are intended for CarbonData users (not CarbonData committers/contributors). You
+should ensure that Release Notes are informative and useful.
+
+Open the release notes from the [version status page](https://issues.apache.org/jira/browse/CARBONDATA/?selectedTab=com.atlassian.jira.jira-projects-plugin:versions-panel)
+by choosing the release underway and clicking Release Notes.
+
+You should verify that the issues listed automatically by Jira are appropriate to appear in the
+Release Notes. Specifically, issues should:
+
+* Be appropriate classified as `Bug`, `New Feature`, `Improvement`, etc.
+* Represent noteworthy user-facing changes, such as new functionality, backward-incompatible
+changes, or performance improvements.
+* Have occurred since the previous release; an issue that was introduced and fixed between
+releases should not appear in the Release Notes.
+* Have an issue title that makes sense when read on its own.
+
+Adjust any of the above properties to the improve clarity and presentation of the Release Notes.
+
+#### Verify that a Release Build works
+
+Run `mvn clean install -Prelease` to ensure that the build processes that are specific to that
+profile are in good shape.
+
+_Checklist to proceed to the next step:_
+
+1. Release Manager's GPG key is published to `dist.apache.org`.
+2. Release Manager's GPG key is configured in `git` configuration.
+3. Release Manager has `org.apache.carbondata` listed under `Staging Profiles` in Nexus.
+4. Release Manager's Nexus User Token is configured in `settings.xml`.
+5. Jira release item for the subsequent release has been created.
+6. There are no release blocking Jira issues.
+7. Release Notes in Jira have been audited and adjusted.
+
+### Build a release
+
+Use Maven release plugin to tag and build release artifacts, as follows:
+
+```
+mvn release:prepare
+```
+
+Use Maven release plugin to stage these artifacts on the Apache Nexus repository, as follows:
+
+```
+mvn release:perform
+```
+
+Review all staged artifacts. They should contain all relevant parts for each module, including
+`pom.xml`, jar, test jar, source, etc. Artifact names should follow
+[the existing format](https://search.maven.org/#search%7Cga%7C1%7Cg%3A%22org.apache.carbondata%22)
+in which artifact name mirrors directory structure. Carefully review any new artifacts.
+
+Close the staging repository on Nexus. When prompted for a description, enter "Apache CarbonData
+x.x.x release".
+
+### Stage source release on dist.apache.org
+
+Copy the source release to dev repository on `dist.apache.org`.
+
+1. If you have not already, check out the section of the `dev` repository on `dist.apache.org` via Subversion. In a fresh directory:
+
+```
+svn co https://dist.apache.org/repos/dist/dev/carbondata
+```
+
+2. Make a directory for the new release:
+
+```
+mkdir x.x.x
+```
+
+3. Copy the CarbonData source distribution, hash, and GPG signature:
+
+```
+cp apache-carbondata-x.x.x-source-release.zip x.x.x
+```
+
+4. Add and commit the files:
+
+```
+svn add x.x.x
+svn commit
+```
+
+5. Verify the files are [present](https://dist.apache.org/repos/dist/dev/carbondata).
+
+### Propose a pull request for website updates
+
+The final step of building a release candidate is to propose a website pull request.
+
+This pull request should update the following page with the new release:
+
+* `src/main/webapp/index.html`
+* `src/main/webapp/docs/latest/mainpage.html`
+
+_Checklist to proceed to the next step:_
+
+1. Maven artifacts deployed to the staging repository of
+[repository.apache.org](https://repository.apache.org)
+2. Source distribution deployed to the dev repository of
+[dist.apache.org](https://dist.apache.org/repos/dist/dev/carbondata/)
+3. Website pull request to list the release.
+
+## Vote on the release candidate
+
+Once you have built and individually reviewed the release candidate, please share it for the
+community-wide review. Please review foundation-wide [voting guidelines](http://www.apache.org/foundation/voting.html)
+for more information.
+
+Start the review-and-vote thread on the dev@ mailing list. Here's an email template; please
+adjust as you see fit:
+
+```
+From: Release Manager
+To: dev@carbondata.apache.org
+Subject: [VOTE] Apache CarbonData Release x.x.x
+
+Hi everyone,
+Please review and vote on the release candidate for the version x.x.x, as follows:
+
+[ ] +1, Approve the release
+[ ] -1, Do not approve the release (please provide specific comments)
+
+The complete staging area is available for your review, which includes:
+* JIRA release notes [1],
+* the official Apache source release to be deployed to dist.apache.org [2], which is signed with the key with fingerprint FFFFFFFF [3],
+* all artifacts to be deployed to the Maven Central Repository [4],
+* source code tag "x.x.x" [5],
+* website pull request listing the release [6].
+
+The vote will be open for at least 72 hours. It is adopted by majority approval, with at least 3 PMC affirmative votes.
+
+Thanks,
+Release Manager
+
+[1] link
+[2] link
+[3] https://dist.apache.org/repos/dist/dist/carbondata/KEYS
+[4] link
+[5] link
+[6] link
+```
+
+If there are any issues found in the release candidate, reply on the vote thread to cancel the vote.
+There’s no need to wait 72 hours. Proceed to the `Cancel a Release (Fix Issues)` step below and
+address the problem.
+However, some issues don’t require cancellation.
+For example, if an issue is found in the website pull request, just correct it on the spot and the
+vote can continue as-is.
+
+If there are no issues, reply on the vote thread to close the voting. Then, tally the votes in a
+separate email. Here’s an email template; please adjust as you see fit.
+
+```
+From: Release Manager
+To: dev@carbondata.apache.org
+Subject: [RESULT][VOTE] Apache CarbonData Release x.x.x
+
+I'm happy to announce that we have unanimously approved this release.
+
+There are XXX approving votes, XXX of which are binding:
+* approver 1
+* approver 2
+* approver 3
+* approver 4
+
+There are no disapproving votes.
+
+Thanks everyone!
+```
+
+While in incubation, the Apache Incubator PMC must also vote on each release, using the same
+process as above. Start the review and vote thread on the `general@incubator.apache.org` list.
+
+
+_Checklist to proceed to the final step:_
+
+1. Community votes to release the proposed release
+2. While in incubation, Apache Incubator PMC votes to release the proposed release
+
+## Cancel a Release (Fix Issues)
+
+Any issue identified during the community review and vote should be fixed in this step.
+
+To fully cancel a vote:
+
+* Cancel the current release and verify the version is back to the correct SNAPSHOT:
+
+```
+mvn release:cancel
+```
+
+* Drop the release tag:
+
+```
+git tag -d x.x.x
+git push --delete apache x.x.x
+```
+
+* Drop the staging repository on Nexus ([repository.apache.org](https://repository.apache.org))
+
+
+Verify the version is back to the correct SNAPSHOT.
+
+Code changes should be proposed as standard pull requests and merged.
+
+Once all issues have been resolved, you should go back and build a new release candidate with
+these changes.
+
+## Finalize the release
+
+Once the release candidate has been reviewed and approved by the community, the release should be
+ finalized. This involves the final deployment of the release to the release repositories,
+ merging the website changes, and announce the release.
+
+### Deploy artifacts to Maven Central repository
+
+On Nexus, release the staged artifacts to Maven Central repository. In the `Staging Repositories`
+ section, find the relevant release candidate `orgapachecarbondata-XXX` entry and click `Release`.
+
+### Deploy source release to dist.apache.org
+
+Copy the source release from the `dev` repository to `release` repository at `dist.apache.org`
+using Subversion.
+
+### Merge website pull request
+
+Merge the website pull request to list the release created earlier.
+
+### Mark the version as released in Jira
+
+In Jira, inside [version management](https://issues.apache.org/jira/plugins/servlet/project-config/CARBONDATA/versions)
+, hover over the current release and a settings menu will appear. Click `Release`, and select
+today's state.
+
+_Checklist to proceed to the next step:_
+
+1. Maven artifacts released and indexed in the
+ [Maven Central repository](https://search.maven.org/#search%7Cga%7C1%7Cg%3A%22org.apache.carbondata%22)
+2. Source distribution available in the release repository of
+ [dist.apache.org](https://dist.apache.org/repos/dist/release/carbondata/)
+3. Website pull request to list the release merged
+4. Release version finalized in Jira
+
+## Promote the release
+
+Once the release has been finalized, the last step of the process is to promote the release
+within the project and beyond.
+
+### Apache mailing lists
+
+Announce on the dev@ mailing list that the release has been finished.
+
+Announce on the user@ mailing list that the release is available, listing major improvements and
+contributions.
+
+While in incubation, announce the release on the Incubator's general@ mailing list.
+
+_Checklist to declare the process completed:_
+
+1. Release announced on the user@ mailing list.
+2. Release announced on the Incubator's general@ mailing list.
+3. Completion declared on the dev@ mailing list.
+
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__release').addClass('selected'); });
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/s3-guide.md
----------------------------------------------------------------------
diff --git a/src/site/markdown/s3-guide.md b/src/site/markdown/s3-guide.md
index 2f4dfa9..37f157c 100644
--- a/src/site/markdown/s3-guide.md
+++ b/src/site/markdown/s3-guide.md
@@ -15,7 +15,7 @@
limitations under the License.
-->
-#S3 Guide (Alpha Feature 1.4.1)
+# S3 Guide (Alpha Feature 1.4.1)
Object storage is the recommended storage format in cloud as it can support storing large data
files. S3 APIs are widely used for accessing object stores. This can be
@@ -26,7 +26,7 @@ data and the data can be accessed from anywhere at any time.
Carbondata can support any Object Storage that conforms to Amazon S3 API.
Carbondata relies on Hadoop provided S3 filesystem APIs to access Object stores.
-#Writing to Object Storage
+# Writing to Object Storage
To store carbondata files onto Object Store, `carbon.storelocation` property will have
to be configured with Object Store path in CarbonProperties file.
@@ -46,9 +46,9 @@ For example:
CREATE TABLE IF NOT EXISTS db1.table1(col1 string, col2 int) STORED AS carbondata LOCATION 's3a://mybucket/carbonstore'
```
-For more details on create table, Refer [data-management-on-carbondata](./data-management-on-carbondata.md#create-table)
+For more details on create table, Refer [DDL of CarbonData](ddl-of-carbondata.md#create-table)
-#Authentication
+# Authentication
Authentication properties will have to be configured to store the carbondata files on to S3 location.
@@ -80,12 +80,15 @@ sparkSession.sparkContext.hadoopConfiguration.set("fs.s3a.secret.key", "123")
sparkSession.sparkContext.hadoopConfiguration.set("fs.s3a.access.key","456")
```
-#Recommendations
+# Recommendations
1. Object Storage like S3 does not support file leasing mechanism(supported by HDFS) that is
required to take locks which ensure consistency between concurrent operations therefore, it is
-recommended to set the configurable lock path property([carbon.lock.path](https://github.com/apache/carbondata/blob/master/docs/configuration-parameters.md#miscellaneous-configuration))
+recommended to set the configurable lock path property([carbon.lock.path](./configuration-parameters.md#system-configuration))
to a HDFS directory.
-2. Concurrent data manipulation operations are not supported. Object stores follow eventual
-consistency semantics, i.e., any put request might take some time to reflect when trying to list
-.This behaviour causes not to ensure the data read is always consistent or latest.
+2. Concurrent data manipulation operations are not supported. Object stores follow eventual consistency semantics, i.e., any put request might take some time to reflect when trying to list. This behaviour causes the data read is always not consistent or not the latest.
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__s3').addClass('selected'); });
+</script>
http://git-wip-us.apache.org/repos/asf/carbondata-site/blob/44eed099/src/site/markdown/sdk-guide.md
----------------------------------------------------------------------
diff --git a/src/site/markdown/sdk-guide.md b/src/site/markdown/sdk-guide.md
index e592aa5..66f3d61 100644
--- a/src/site/markdown/sdk-guide.md
+++ b/src/site/markdown/sdk-guide.md
@@ -351,6 +351,25 @@ public CarbonWriterBuilder withLoadOptions(Map<String, String> options);
```
/**
+ * To support the table properties for sdk writer
+ *
+ * @param options key,value pair of create table properties.
+ * supported keys values are
+ * a. blocksize -- [1-2048] values in MB. Default value is 1024
+ * b. blockletsize -- values in MB. Default value is 64 MB
+ * c. localDictionaryThreshold -- positive value, default is 10000
+ * d. enableLocalDictionary -- true / false. Default is false
+ * e. sortcolumns -- comma separated column. "c1,c2". Default all dimensions are sorted.
+ *
+ * @return updated CarbonWriterBuilder
+ */
+public CarbonWriterBuilder withTableProperties(Map<String, String> options);
+```
+
+
+```
+/**
+* this writer is not thread safe, use buildThreadSafeWriterForCSVInput in multi thread environment
* Build a {@link CarbonWriter}, which accepts row in CSV format object
* @param schema carbon Schema object {org.apache.carbondata.sdk.file.Schema}
* @return CSVCarbonWriter
@@ -360,8 +379,24 @@ public CarbonWriterBuilder withLoadOptions(Map<String, String> options);
public CarbonWriter buildWriterForCSVInput(org.apache.carbondata.sdk.file.Schema schema) throws IOException, InvalidLoadOptionException;
```
+```
+/**
+* Can use this writer in multi-thread instance.
+* Build a {@link CarbonWriter}, which accepts row in CSV format
+* @param schema carbon Schema object {org.apache.carbondata.sdk.file.Schema}
+* @param numOfThreads number of threads() in which .write will be called.
+* @return CSVCarbonWriter
+* @throws IOException
+* @throws InvalidLoadOptionException
+*/
+public CarbonWriter buildThreadSafeWriterForCSVInput(Schema schema, short numOfThreads)
+ throws IOException, InvalidLoadOptionException;
+```
+
+
```
/**
+* this writer is not thread safe, use buildThreadSafeWriterForAvroInput in multi thread environment
* Build a {@link CarbonWriter}, which accepts Avro format object
* @param avroSchema avro Schema object {org.apache.avro.Schema}
* @return AvroCarbonWriter
@@ -373,6 +408,22 @@ public CarbonWriter buildWriterForAvroInput(org.apache.avro.Schema schema) throw
```
/**
+* Can use this writer in multi-thread instance.
+* Build a {@link CarbonWriter}, which accepts Avro object
+* @param avroSchema avro Schema object {org.apache.avro.Schema}
+* @param numOfThreads number of threads() in which .write will be called.
+* @return AvroCarbonWriter
+* @throws IOException
+* @throws InvalidLoadOptionException
+*/
+public CarbonWriter buildThreadSafeWriterForAvroInput(org.apache.avro.Schema avroSchema, short numOfThreads)
+ throws IOException, InvalidLoadOptionException
+```
+
+
+```
+/**
+* this writer is not thread safe, use buildThreadSafeWriterForJsonInput in multi thread environment
* Build a {@link CarbonWriter}, which accepts Json object
* @param carbonSchema carbon Schema object
* @return JsonCarbonWriter
@@ -382,6 +433,19 @@ public CarbonWriter buildWriterForAvroInput(org.apache.avro.Schema schema) throw
public JsonCarbonWriter buildWriterForJsonInput(Schema carbonSchema);
```
+```
+/**
+* Can use this writer in multi-thread instance.
+* Build a {@link CarbonWriter}, which accepts Json object
+* @param carbonSchema carbon Schema object
+* @param numOfThreads number of threads() in which .write will be called.
+* @return JsonCarbonWriter
+* @throws IOException
+* @throws InvalidLoadOptionException
+*/
+public JsonCarbonWriter buildThreadSafeWriterForJsonInput(Schema carbonSchema, short numOfThreads)
+```
+
### Class org.apache.carbondata.sdk.file.CarbonWriter
```
/**
@@ -390,7 +454,7 @@ public JsonCarbonWriter buildWriterForJsonInput(Schema carbonSchema);
* which is one row of data.
* If CSVCarbonWriter, object is of type String[], which is one row of data
* If JsonCarbonWriter, object is of type String, which is one row of json
-* Note: This API is not thread safe
+* Note: This API is not thread safe if writer is not built with number of threads argument.
* @param object
* @throws IOException
*/
@@ -678,7 +742,6 @@ Find example code at [CarbonReaderExample](https://github.com/apache/carbondata/
*
* @param dataFilePath complete path including carbondata file name
* @return Schema object
- * @throws IOException
*/
public static Schema readSchemaInDataFile(String dataFilePath);
```
@@ -802,4 +865,10 @@ public String getProperty(String key);
*/
public String getProperty(String key, String defaultValue);
```
-Reference : [list of carbon properties](http://carbondata.apache.org/configuration-parameters.html)
+Reference : [list of carbon properties](./configuration-parameters.md)
+
+
+<script>
+// Show selected style on nav item
+$(function() { $('.b-nav__api').addClass('selected'); });
+</script>