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Posted to commits@spark.apache.org by sr...@apache.org on 2022/09/07 13:30:31 UTC
[spark-website] branch asf-site updated: Fix dead link in documentation.html and third-party-projects.html
This is an automated email from the ASF dual-hosted git repository.
srowen pushed a commit to branch asf-site
in repository https://gitbox.apache.org/repos/asf/spark-website.git
The following commit(s) were added to refs/heads/asf-site by this push:
new b8b47eeff Fix dead link in documentation.html and third-party-projects.html
b8b47eeff is described below
commit b8b47eeffb0c1167b1eb9ef4b331dcd7e223d167
Author: yangjie01 <ya...@baidu.com>
AuthorDate: Wed Sep 7 08:30:23 2022 -0500
Fix dead link in documentation.html and third-party-projects.html
This pr is the first part of SPARK-40322, there are a total of 5 pages with dead links:
- documentation.html
- third-party-projects.html
- release-process.html
- news
- powered-by.html
This pr fix `documentation.html` and `third-party-projects.html`
Author: yangjie01 <ya...@baidu.com>
Closes #411 from LuciferYang/deadlink-p1.
---
documentation.md | 3 +--
site/documentation.html | 3 +--
site/third-party-projects.html | 4 +---
third-party-projects.md | 4 +---
4 files changed, 4 insertions(+), 10 deletions(-)
diff --git a/documentation.md b/documentation.md
index 4b71656c4..f75f9dcf2 100644
--- a/documentation.md
+++ b/documentation.md
@@ -77,7 +77,7 @@ navigation:
</ul>
<p>The documentation linked to above covers getting started with Spark, as well the built-in components <a href="{{site.baseurl}}/docs/latest/mllib-guide.html">MLlib</a>,
-<a href="{{site.baseurl}}/docs/latest/streaming-programming-guide.html">Spark Streaming</a>, and <a href="{{site.baseurl}}/docs/latest/graphx-guide.html">GraphX</a>.</p>
+<a href="{{site.baseurl}}/docs/latest/streaming-programming-guide.html">Spark Streaming</a>, and <a href="{{site.baseurl}}/docs/latest/graphx-programming-guide.html">GraphX</a>.</p>
<p>In addition, this page lists other resources for learning Spark.</p>
@@ -176,7 +176,6 @@ Slides, videos and EC2-based exercises from each of these are available online:
<h3>External Tutorials, Blog Posts, and Talks</h3>
<ul>
- <li><a href="http://engineering.ooyala.com/blog/using-parquet-and-scrooge-spark">Using Parquet and Scrooge with Spark</a> — Scala-friendly Parquet and Avro usage tutorial from Ooyala's Evan Chan</li>
<li><a href="http://codeforhire.com/2014/02/18/using-spark-with-mongodb/">Using Spark with MongoDB</a> — by Sampo Niskanen from Wellmo</li>
<li><a href="https://spark-summit.org/2013">Spark Summit 2013</a> — contained 30 talks about Spark use cases, available as slides and videos</li>
<li><a href="http://zenfractal.com/2013/08/21/a-powerful-big-data-trio/">A Powerful Big Data Trio: Spark, Parquet and Avro</a> — Using Parquet in Spark by Matt Massie</li>
diff --git a/site/documentation.html b/site/documentation.html
index ef0095ce6..cd0fc8cdf 100644
--- a/site/documentation.html
+++ b/site/documentation.html
@@ -192,7 +192,7 @@
</ul>
<p>The documentation linked to above covers getting started with Spark, as well the built-in components <a href="/docs/latest/mllib-guide.html">MLlib</a>,
-<a href="/docs/latest/streaming-programming-guide.html">Spark Streaming</a>, and <a href="/docs/latest/graphx-guide.html">GraphX</a>.</p>
+<a href="/docs/latest/streaming-programming-guide.html">Spark Streaming</a>, and <a href="/docs/latest/graphx-programming-guide.html">GraphX</a>.</p>
<p>In addition, this page lists other resources for learning Spark.</p>
@@ -290,7 +290,6 @@ Slides, videos and EC2-based exercises from each of these are available online:
<h3>External Tutorials, Blog Posts, and Talks</h3>
<ul>
- <li><a href="http://engineering.ooyala.com/blog/using-parquet-and-scrooge-spark">Using Parquet and Scrooge with Spark</a> — Scala-friendly Parquet and Avro usage tutorial from Ooyala's Evan Chan</li>
<li><a href="http://codeforhire.com/2014/02/18/using-spark-with-mongodb/">Using Spark with MongoDB</a> — by Sampo Niskanen from Wellmo</li>
<li><a href="https://spark-summit.org/2013">Spark Summit 2013</a> — contained 30 talks about Spark use cases, available as slides and videos</li>
<li><a href="http://zenfractal.com/2013/08/21/a-powerful-big-data-trio/">A Powerful Big Data Trio: Spark, Parquet and Avro</a> — Using Parquet in Spark by Matt Massie</li>
diff --git a/site/third-party-projects.html b/site/third-party-projects.html
index bb07e2e8e..fedefe081 100644
--- a/site/third-party-projects.html
+++ b/site/third-party-projects.html
@@ -170,14 +170,12 @@ against Spark, and data scientists to use Javascript in Jupyter notebooks.</li>
Mahout has switched to using Spark as the backend</li>
<li><a href="https://wiki.apache.org/mrql/">Apache MRQL</a> - A query processing and optimization
system for large-scale, distributed data analysis, built on top of Apache Hadoop, Hama, and Spark</li>
- <li><a href="http://blinkdb.org/">BlinkDB</a> - a massively parallel, approximate query engine built
+ <li><a href="https://github.com/sameeragarwal/blinkdb">BlinkDB</a> - a massively parallel, approximate query engine built
on top of Shark and Spark</li>
<li><a href="https://github.com/adobe-research/spindle">Spindle</a> - Spark/Parquet-based web
analytics query engine</li>
<li><a href="https://github.com/thunderain-project/thunderain">Thunderain</a> - a framework
for combining stream processing with historical data, think Lambda architecture</li>
- <li><a href="https://github.com/AyasdiOpenSource/df">DF</a> from Ayasdi - a Pandas-like data frame
-implementation for Spark</li>
<li><a href="https://github.com/OryxProject/oryx">Oryx</a> - Lambda architecture on Apache Spark,
Apache Kafka for real-time large scale machine learning</li>
<li><a href="https://github.com/bigdatagenomics/adam">ADAM</a> - A framework and CLI for loading,
diff --git a/third-party-projects.md b/third-party-projects.md
index b08c18e13..1db600c35 100644
--- a/third-party-projects.md
+++ b/third-party-projects.md
@@ -52,14 +52,12 @@ against Spark, and data scientists to use Javascript in Jupyter notebooks.
Mahout has switched to using Spark as the backend
- <a href="https://wiki.apache.org/mrql/">Apache MRQL</a> - A query processing and optimization
system for large-scale, distributed data analysis, built on top of Apache Hadoop, Hama, and Spark
-- <a href="http://blinkdb.org/">BlinkDB</a> - a massively parallel, approximate query engine built
+- <a href="https://github.com/sameeragarwal/blinkdb">BlinkDB</a> - a massively parallel, approximate query engine built
on top of Shark and Spark
- <a href="https://github.com/adobe-research/spindle">Spindle</a> - Spark/Parquet-based web
analytics query engine
- <a href="https://github.com/thunderain-project/thunderain">Thunderain</a> - a framework
for combining stream processing with historical data, think Lambda architecture
-- <a href="https://github.com/AyasdiOpenSource/df">DF</a> from Ayasdi - a Pandas-like data frame
-implementation for Spark
- <a href="https://github.com/OryxProject/oryx">Oryx</a> - Lambda architecture on Apache Spark,
Apache Kafka for real-time large scale machine learning
- <a href="https://github.com/bigdatagenomics/adam">ADAM</a> - A framework and CLI for loading,
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