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     new 5f1c9c1  Publishing website 2021/03/13 18:03:37 at commit 153876f
5f1c9c1 is described below

commit 5f1c9c14fc67ee826b46c02ed2336aae1f64b9b3
Author: jenkins <bui...@apache.org>
AuthorDate: Sat Mar 13 18:03:37 2021 +0000

    Publishing website 2021/03/13 18:03:37 at commit 153876f
---
 website/generated-content/contribute/index.xml                      | 2 +-
 website/generated-content/contribute/release-guide/index.html       | 4 ++--
 website/generated-content/documentation/runners/spark/index.html    | 6 +++---
 .../documentation/sdks/java/testing/nexmark/index.html              | 4 ++--
 website/generated-content/sitemap.xml                               | 2 +-
 5 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/website/generated-content/contribute/index.xml 
b/website/generated-content/contribute/index.xml
index e2cf503..762515e 100644
--- a/website/generated-content/contribute/index.xml
+++ b/website/generated-content/contribute/index.xml
@@ -1231,7 +1231,7 @@ In case of script failure, you can still run all of them 
manually.&lt;/p>
 
-Prepourl=https://repository.apache.org/content/repositories/orgapachebeam-${KEY}
 \
 -Pver=${RELEASE_VERSION}
 &lt;/code>&lt;/pre>&lt;p>&lt;strong>Spark Local Runner&lt;/strong>&lt;/p>
-&lt;pre>&lt;code>./gradlew :runners:spark:runQuickstartJavaSpark \
+&lt;pre>&lt;code>./gradlew :runners:spark:2:runQuickstartJavaSpark \
 
-Prepourl=https://repository.apache.org/content/repositories/orgapachebeam-${KEY}
 \
 -Pver=${RELEASE_VERSION}
 &lt;/code>&lt;/pre>&lt;p>&lt;strong>Dataflow Runner&lt;/strong>&lt;/p>
diff --git a/website/generated-content/contribute/release-guide/index.html 
b/website/generated-content/contribute/release-guide/index.html
index 7591415..c80ee86 100644
--- a/website/generated-content/contribute/release-guide/index.html
+++ b/website/generated-content/contribute/release-guide/index.html
@@ -309,7 +309,7 @@ In case of script failure, you can still run all of them 
manually.</p><h4 id=run
 </code></pre><p><strong>Flink Local Runner</strong></p><pre><code>./gradlew 
:runners:flink:1.10:runQuickstartJavaFlinkLocal \
 
-Prepourl=https://repository.apache.org/content/repositories/orgapachebeam-${KEY}
 \
 -Pver=${RELEASE_VERSION}
-</code></pre><p><strong>Spark Local Runner</strong></p><pre><code>./gradlew 
:runners:spark:runQuickstartJavaSpark \
+</code></pre><p><strong>Spark Local Runner</strong></p><pre><code>./gradlew 
:runners:spark:2:runQuickstartJavaSpark \
 
-Prepourl=https://repository.apache.org/content/repositories/orgapachebeam-${KEY}
 \
 -Pver=${RELEASE_VERSION}
 </code></pre><p><strong>Dataflow Runner</strong></p><pre><code>./gradlew 
:runners:google-cloud-dataflow-java:runQuickstartJavaDataflow \
@@ -425,7 +425,7 @@ If you end up getting permissions errors ask on the mailing 
list for assistance.
 Ask other contributors to do the same.</p><p>Also, update <a 
href=https://en.wikipedia.org/wiki/Apache_Beam>the Wikipedia article on Apache 
Beam</a>.</p><h3 id=checklist-to-declare-the-process-completed>Checklist to 
declare the process completed</h3><ol><li>Release announced on the user@ 
mailing list.</li><li>Blog post published, if applicable.</li><li>Release 
recorded in reporter.apache.org.</li><li>Release announced on social 
media.</li><li>Completion declared on the dev@ mailing list. [...]
 Once you’ve finished the release, please take a step back and look what areas 
of this process and be improved. Perhaps some part of the process can be 
simplified.
 Perhaps parts of this guide can be clarified.</p><p>If we have specific ideas, 
please start a discussion on the dev@ mailing list and/or propose a pull 
request to update this guide.
-Thanks!</p><div class=feedback><p class=update>Last updated on 
2021/02/02</p><h3>Have you found everything you were looking for?</h3><p 
class=description>Was it all useful and clear? Is there anything that you would 
like to change? Let us know!</p><button class=load-button><a 
href="mailto:d...@beam.apache.org?subject=Beam Website Feedback">SEND 
FEEDBACK</a></button></div></div></div><footer class=footer><div 
class=footer__contained><div class=footer__cols><div class="footer__cols__col 
foo [...]
+Thanks!</p><div class=feedback><p class=update>Last updated on 
2021/01/22</p><h3>Have you found everything you were looking for?</h3><p 
class=description>Was it all useful and clear? Is there anything that you would 
like to change? Let us know!</p><button class=load-button><a 
href="mailto:d...@beam.apache.org?subject=Beam Website Feedback">SEND 
FEEDBACK</a></button></div></div></div><footer class=footer><div 
class=footer__contained><div class=footer__cols><div class="footer__cols__col 
foo [...]
 <a href=http://www.apache.org>The Apache Software Foundation</a>
 | <a href=/privacy_policy>Privacy Policy</a>
 | <a href=/feed.xml>RSS Feed</a><br><br>Apache Beam, Apache, Beam, the Beam 
logo, and the Apache feather logo are either registered trademarks or 
trademarks of The Apache Software Foundation. All other products or name brands 
are trademarks of their respective holders, including The Apache Software 
Foundation.</div></div></div></div></footer></body></html>
\ No newline at end of file
diff --git a/website/generated-content/documentation/runners/spark/index.html 
b/website/generated-content/documentation/runners/spark/index.html
index a396364..0ecd032 100644
--- a/website/generated-content/documentation/runners/spark/index.html
+++ b/website/generated-content/documentation/runners/spark/index.html
@@ -77,7 +77,7 @@ the portable Runner. For more information on portability, 
please visit the
 Apache Beam with Python you have to install the Apache Beam Python SDK: 
<code>pip install apache_beam</code>. Please refer to the <a 
href=/documentation/sdks/python/>Python documentation</a>
 on how to create a Python pipeline.</p><div class="language-py snippet"><div 
class="notebook-skip code-snippet"><a class=copy type=button 
data-bs-toggle=tooltip data-bs-placement=bottom title="Copy to clipboard"><img 
src=/images/copy-icon.svg></a><div class=highlight><pre class=chroma><code 
class=language-py data-lang=py><span class=n>pip</span> <span 
class=n>install</span> <span 
class=n>apache_beam</span></code></pre></div></div></div><p 
class=language-py>Starting from Beam 2.20.0, pre- [...]
 <a href=https://hub.docker.com/r/apache/beam_spark_job_server>Docker 
Hub</a>.</p><p class=language-py>For older Beam versions, you will need a copy 
of Apache Beam&rsquo;s source code. You can
-download it on the <a href=/get-started/downloads/>Downloads page</a>.</p><p 
class=language-py><ol><li>Start the JobService endpoint:<ul><li>with Docker 
(preferred): <code>docker run --net=host 
apache/beam_spark_job_server:latest</code></li><li>or from Beam source code: 
<code>./gradlew 
:runners:spark:job-server:runShadow</code></li></ul></li></ol></p><p 
class=language-py>The JobService is the central instance where you submit your 
Beam pipeline.
+download it on the <a href=/get-started/downloads/>Downloads page</a>.</p><p 
class=language-py><ol><li>Start the JobService endpoint:<ul><li>with Docker 
(preferred): <code>docker run --net=host 
apache/beam_spark_job_server:latest</code></li><li>or from Beam source code: 
<code>./gradlew 
:runners:spark:2:job-server:runShadow</code></li></ul></li></ol></p><p 
class=language-py>The JobService is the central instance where you submit your 
Beam pipeline.
 The JobService will create a Spark job for the pipeline and execute the
 job. To execute the job on a Spark cluster, the Beam JobService needs to be
 provided with the Spark master address.</p><p class=language-py><ol 
start=2><li>Submit the Python pipeline to the above endpoint by using the 
<code>PortableRunner</code>, <code>job_endpoint</code> set to 
<code>localhost:8099</code> (this is the default address of the JobService), 
and <code>environment_type</code> set to <code>LOOPBACK</code>. For 
example:</li></ol></p><div class="language-py snippet"><div 
class="notebook-skip code-snippet"><a class=copy type=button 
data-bs-toggle=tooltip [...]
@@ -90,7 +90,7 @@ provided with the Spark master address.</p><p 
class=language-py><ol start=2><li>
 <span class=p>])</span>
 <span class=k>with</span> <span class=n>beam</span><span class=o>.</span><span 
class=n>Pipeline</span><span class=p>(</span><span class=n>options</span><span 
class=p>)</span> <span class=k>as</span> <span class=n>p</span><span 
class=p>:</span>
     <span class=o>...</span></code></pre></div></div></div><h3 
id=running-on-a-pre-deployed-spark-cluster>Running on a pre-deployed Spark 
cluster</h3><p>Deploying your Beam pipeline on a cluster that already has a 
Spark deployment (Spark classes are available in container classpath) does not 
require any additional dependencies.
-For more details on the different deployment modes see: <a 
href=https://spark.apache.org/docs/latest/spark-standalone.html>Standalone</a>, 
<a href=https://spark.apache.org/docs/latest/running-on-yarn.html>YARN</a>, or 
<a 
href=https://spark.apache.org/docs/latest/running-on-mesos.html>Mesos</a>.</p><p
 class=language-py><ol><li>Start a Spark cluster which exposes the master on 
port 7077 by default.</li></ol></p><p class=language-py><ol start=2><li>Start 
JobService that will connect with th [...]
+For more details on the different deployment modes see: <a 
href=https://spark.apache.org/docs/latest/spark-standalone.html>Standalone</a>, 
<a href=https://spark.apache.org/docs/latest/running-on-yarn.html>YARN</a>, or 
<a 
href=https://spark.apache.org/docs/latest/running-on-mesos.html>Mesos</a>.</p><p
 class=language-py><ol><li>Start a Spark cluster which exposes the master on 
port 7077 by default.</li></ol></p><p class=language-py><ol start=2><li>Start 
JobService that will connect with th [...]
 Note however that <code>environment_type=LOOPBACK</code> is only intended for 
local testing.
 See <a href=/roadmap/portability/#sdk-harness-config>here</a> for 
details.</li></ol></p><p class=language-py>(Note that, depending on your 
cluster setup, you may need to change the <code>environment_type</code> option.
 See <a href=/roadmap/portability/#sdk-harness-config>here</a> for 
details.)</p><h2 id=pipeline-options-for-the-spark-runner>Pipeline options for 
the Spark Runner</h2><p>When executing your pipeline with the Spark Runner, you 
should consider the following pipeline options.</p><p 
class=language-java><br><b>For RDD/DStream based runner:</b><br></p><table 
class="language-java table 
table-bordered"><tr><th>Field</th><th>Description</th><th>Default 
Value</th></tr><tr><td><code>runner</code></t [...]
@@ -99,7 +99,7 @@ Passing any of the above mentioned options could be done as 
one of the <code>app
 For more on how to generally use <code>spark-submit</code> checkout Spark <a 
href=https://spark.apache.org/docs/latest/submitting-applications.html#launching-applications-with-spark-submit>documentation</a>.</p><h3
 id=monitoring-your-job>Monitoring your job</h3><p>You can monitor a running 
Spark job using the Spark <a 
href=https://spark.apache.org/docs/latest/monitoring.html#web-interfaces>Web 
Interfaces</a>. By default, this is available at port <code>4040</code> on the 
driver node. If  [...]
 Spark also has a history server to <a 
href=https://spark.apache.org/docs/latest/monitoring.html#viewing-after-the-fact>view
 after the fact</a>.<p class=language-java>Metrics are also available via <a 
href=https://spark.apache.org/docs/latest/monitoring.html#rest-api>REST API</a>.
 Spark provides a <a 
href=https://spark.apache.org/docs/latest/monitoring.html#metrics>metrics 
system</a> that allows reporting Spark metrics to a variety of Sinks. The Spark 
runner reports user-defined Beam Aggregators using this same metrics system and 
currently supports <code>GraphiteSink</code> and <code>CSVSink</code>, and 
providing support for additional Sinks supported by Spark is easy and 
straight-forward.</p><p class=language-py>Spark metrics are not yet supported 
on the portable [...]
-Instead, you should use <code>SparkContextOptions</code> which can only be 
used programmatically and is not a common <code>PipelineOptions</code> 
implementation.<br><br><b>For Structured Streaming based 
runner:</b><br>Provided SparkSession and StreamingListeners are not supported 
on the Spark Structured Streaming runner</p><p class=language-py>Provided 
SparkContext and StreamingListeners are not supported on the Spark portable 
runner.</p><div class=feedback><p class=update>Last updated o [...]
+Instead, you should use <code>SparkContextOptions</code> which can only be 
used programmatically and is not a common <code>PipelineOptions</code> 
implementation.<br><br><b>For Structured Streaming based 
runner:</b><br>Provided SparkSession and StreamingListeners are not supported 
on the Spark Structured Streaming runner</p><p class=language-py>Provided 
SparkContext and StreamingListeners are not supported on the Spark portable 
runner.</p><div class=feedback><p class=update>Last updated o [...]
 <a href=http://www.apache.org>The Apache Software Foundation</a>
 | <a href=/privacy_policy>Privacy Policy</a>
 | <a href=/feed.xml>RSS Feed</a><br><br>Apache Beam, Apache, Beam, the Beam 
logo, and the Apache feather logo are either registered trademarks or 
trademarks of The Apache Software Foundation. All other products or name brands 
are trademarks of their respective holders, including The Apache Software 
Foundation.</div></div></div></div></footer></body></html>
\ No newline at end of file
diff --git 
a/website/generated-content/documentation/sdks/java/testing/nexmark/index.html 
b/website/generated-content/documentation/sdks/java/testing/nexmark/index.html
index 389b7c6..5ad2d77 100644
--- 
a/website/generated-content/documentation/sdks/java/testing/nexmark/index.html
+++ 
b/website/generated-content/documentation/sdks/java/testing/nexmark/index.html
@@ -125,7 +125,7 @@ SMOKE suite can make sure there is nothing broken in the 
Nexmark suite.</p><p>Ba
 </code></pre><h3 id=running-smoke-suite-on-the-sparkrunner-local>Running SMOKE 
suite on the SparkRunner (local)</h3><p>The SparkRunner is special-cased in the 
Nexmark gradle launch. The task will
 provide the version of Spark that the SparkRunner is built against, and
 configure logging.</p><p>Batch Mode:</p><pre><code>./gradlew 
:sdks:java:testing:nexmark:run \
-    -Pnexmark.runner=&quot;:runners:spark&quot; \
+    -Pnexmark.runner=&quot;:runners:spark:2&quot; \
     -Pnexmark.args=&quot;
         --runner=SparkRunner
         --suite=SMOKE
@@ -134,7 +134,7 @@ configure logging.</p><p>Batch 
Mode:</p><pre><code>./gradlew :sdks:java:testing:
         --manageResources=false
         --monitorJobs=true&quot;
 </code></pre><p>Streaming Mode:</p><pre><code>./gradlew 
:sdks:java:testing:nexmark:run \
-    -Pnexmark.runner=&quot;:runners:spark&quot; \
+    -Pnexmark.runner=&quot;:runners:spark:2&quot; \
     -Pnexmark.args=&quot;
         --runner=SparkRunner
         --suite=SMOKE
diff --git a/website/generated-content/sitemap.xml 
b/website/generated-content/sitemap.xml
index 2e8815d..2bc720f 100644
--- a/website/generated-content/sitemap.xml
+++ b/website/generated-content/sitemap.xml
@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset 
xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"; 
xmlns:xhtml="http://www.w3.org/1999/xhtml";><url><loc>/blog/beam-2.28.0/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/categories/blog/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/blog/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/categories/</loc><lastmod>2021-02-23T13:40:55+01:00</lastmod></url><url><loc>/blog/k
 [...]
\ No newline at end of file
+<?xml version="1.0" encoding="utf-8" standalone="yes"?><urlset 
xmlns="http://www.sitemaps.org/schemas/sitemap/0.9"; 
xmlns:xhtml="http://www.w3.org/1999/xhtml";><url><loc>/blog/beam-2.28.0/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/categories/blog/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/blog/</loc><lastmod>2021-02-22T11:40:20-08:00</lastmod></url><url><loc>/categories/</loc><lastmod>2021-02-23T13:40:55+01:00</lastmod></url><url><loc>/blog/k
 [...]
\ No newline at end of file

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