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in repository https://gitbox.apache.org/repos/asf/beam.git
The following commit(s) were added to refs/heads/asf-site by this push:
new 5f1c9c1 Publishing website 2021/03/13 18:03:37 at commit 153876f
5f1c9c1 is described below
commit 5f1c9c14fc67ee826b46c02ed2336aae1f64b9b3
Author: jenkins <[email protected]>
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.</p>
-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 \
+<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>
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:[email protected]?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:[email protected]?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’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=":runners:spark" \
+ -Pnexmark.runner=":runners:spark:2" \
-Pnexmark.args="
--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"
</code></pre><p>Streaming Mode:</p><pre><code>./gradlew
:sdks:java:testing:nexmark:run \
- -Pnexmark.runner=":runners:spark" \
+ -Pnexmark.runner=":runners:spark:2" \
-Pnexmark.args="
--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
