dependabot[bot] opened a new pull request, #26:
URL: https://github.com/apache/beam-starter-python/pull/26

   Bumps [apache-beam](https://github.com/apache/beam) from 2.51.0 to 2.52.0.
   <details>
   <summary>Release notes</summary>
   <p><em>Sourced from <a 
href="https://github.com/apache/beam/releases";>apache-beam's 
releases</a>.</em></p>
   <blockquote>
   <h2>Beam 2.52.0 release</h2>
   <p>We are happy to present the new 2.52.0 release of Beam.
   This release includes both improvements and new functionality.
   See the <a 
href="https://github.com/apache/beam/blob/HEAD/get-started/downloads/#2520-2023-11-17";>download
 page</a> for this release.</p>
   <!-- raw HTML omitted -->
   <p>For more information on changes in 2.52.0, check out the <a 
href="https://github.com/apache/beam/milestone/16";>detailed release 
notes</a>.</p>
   <h2>Highlights</h2>
   <ul>
   <li>Previously deprecated Avro-dependent code (Beam Release 2.46.0) has been 
finally removed from Java SDK &quot;core&quot; package.
   Please, use <code>beam-sdks-java-extensions-avro</code> instead. This will 
allow to easily update Avro version in user code without
   potential breaking changes in Beam &quot;core&quot; since the Beam Avro 
extension already supports the latest Avro versions and
   should handle this. (<a 
href="https://redirect.github.com/apache/beam/issues/25252";>#25252</a>).</li>
   <li>Publishing Java 21 SDK container images now supported as part of Apache 
Beam release process. (<a 
href="https://redirect.github.com/apache/beam/issues/28120";>#28120</a>)
   <ul>
   <li>Direct Runner and Dataflow Runner support running pipelines on Java21 
(experimental until tests fully setup). For other runners (Flink, Spark, Samza, 
etc) support status depend on runner projects.</li>
   </ul>
   </li>
   </ul>
   <h2>New Features / Improvements</h2>
   <ul>
   <li>Add <code>UseDataStreamForBatch</code> pipeline option to the Flink 
runner. When it is set to true, Flink runner will run batch
   jobs using the DataStream API. By default the option is set to false, so the 
batch jobs are still executed
   using the DataSet API.</li>
   <li><code>upload_graph</code> as one of the Experiments options for 
DataflowRunner is no longer required when the graph is larger than 10MB for 
Java SDK (<a 
href="https://redirect.github.com/apache/beam/pull/28621";>PR#28621</a>.</li>
   <li>state amd side input cache has been enabled to a default of 100 MB. Use 
<code>--max_cache_memory_usage_mb=X</code> to provide cache size for the user 
state API and side inputs. (Python) (<a 
href="https://redirect.github.com/apache/beam/issues/28770";>#28770</a>).</li>
   <li>Beam YAML stable release. Beam pipelines can now be written using YAML 
and leverage the Beam YAML framework which includes a preliminary set of IO's 
and turnkey transforms. More information can be found in the YAML root folder 
and in the <a 
href="https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/README.md";>README</a>.</li>
   </ul>
   <h2>Breaking Changes</h2>
   <ul>
   <li><code>org.apache.beam.sdk.io.CountingSource.CounterMark</code> uses 
custom <code>CounterMarkCoder</code> as a default coder since all Avro-dependent
   classes finally moved to <code>extensions/avro</code>. In case if it's still 
required to use <code>AvroCoder</code> for <code>CounterMark</code>, then,
   as a workaround, a copy of &quot;old&quot; <code>CountingSource</code> class 
should be placed into a project code and used directly
   (<a 
href="https://redirect.github.com/apache/beam/issues/25252";>#25252</a>).</li>
   <li>Renamed <code>host</code> to <code>firestoreHost</code> in 
<code>FirestoreOptions</code> to avoid potential conflict of command line 
arguments (Java) (<a 
href="https://redirect.github.com/apache/beam/pull/29201";>#29201</a>).</li>
   </ul>
   <h2>Bugfixes</h2>
   <ul>
   <li>Fixed &quot;Desired bundle size 0 bytes must be greater than 0&quot; in 
Java SDK's BigtableIO.BigtableSource when you have more cores than bytes to 
read (Java) <a 
href="https://redirect.github.com/apache/beam/issues/28793";>#28793</a>.</li>
   <li><code>watch_file_pattern</code> arg of the <a 
href="https://github.com/apache/beam/blob/104c10b3ee536a9a3ea52b4dbf62d86b669da5d9/sdks/python/apache_beam/ml/inference/base.py#L997";>RunInference</a>
 arg had no effect prior to 2.52.0. To use the behavior of arg 
<code>watch_file_pattern</code> prior to 2.52.0, follow the documentation at <a 
href="https://beam.apache.org/documentation/ml/side-input-updates/";>https://beam.apache.org/documentation/ml/side-input-updates/</a>
 and use <code>WatchFilePattern</code> PTransform as a SideInput. (<a 
href="https://redirect.github.com/apache/beam/pulls/28948";>#28948</a>)</li>
   <li><code>MLTransform</code> doesn't output artifacts such as min, max and 
quantiles. Instead, <code>MLTransform</code> will add a feature to output these 
artifacts as human readable format - <a 
href="https://redirect.github.com/apache/beam/issues/29017";>#29017</a>. For 
now, to use the artifacts such as min and max that were produced by the eariler 
<code>MLTransform</code>, use <code>read_artifact_location</code> of 
<code>MLTransform</code>, which reads artifacts that were produced earlier in a 
different <code>MLTransform</code> (<a 
href="https://redirect.github.com/apache/beam/pull/29016/";>#29016</a>)</li>
   <li>Fixed a memory leak, which affected some long-running Python pipelines: 
<a href="https://redirect.github.com/apache/beam/issues/28246";>#28246</a>.</li>
   </ul>
   <h2>Security Fixes</h2>
   <ul>
   <li>Fixed <a 
href="https://www.cve.org/CVERecord?id=CVE-2023-39325";>CVE-2023-39325</a> 
(Java/Python/Go) (<a 
href="https://redirect.github.com/apache/beam/issues/29118";>#29118</a>).</li>
   <li>Mitigated <a 
href="https://nvd.nist.gov/vuln/detail/CVE-2023-47248";>CVE-2023-47248</a>  
(Python) <a 
href="https://redirect.github.com/apache/beam/issues/29392";>#29392</a>.</li>
   </ul>
   <h2>List of Contributors</h2>
   <p>According to git shortlog, the following people contributed to the 2.52.0 
release. Thank you to all contributors!</p>
   <!-- raw HTML omitted -->
   </blockquote>
   <p>... (truncated)</p>
   </details>
   <details>
   <summary>Changelog</summary>
   <p><em>Sourced from <a 
href="https://github.com/apache/beam/blob/master/CHANGES.md";>apache-beam's 
changelog</a>.</em></p>
   <blockquote>
   <h1>[2.52.0] - 2023-11-17</h1>
   <h2>Highlights</h2>
   <ul>
   <li>Previously deprecated Avro-dependent code (Beam Release 2.46.0) has been 
finally removed from Java SDK &quot;core&quot; package.
   Please, use <code>beam-sdks-java-extensions-avro</code> instead. This will 
allow to easily update Avro version in user code without
   potential breaking changes in Beam &quot;core&quot; since the Beam Avro 
extension already supports the latest Avro versions and
   should handle this. (<a 
href="https://redirect.github.com/apache/beam/issues/25252";>#25252</a>).</li>
   <li>Publishing Java 21 SDK container images now supported as part of Apache 
Beam release process. (<a 
href="https://redirect.github.com/apache/beam/issues/28120";>#28120</a>)
   <ul>
   <li>Direct Runner and Dataflow Runner support running pipelines on Java21 
(experimental until tests fully setup). For other runners (Flink, Spark, Samza, 
etc) support status depend on runner projects.</li>
   </ul>
   </li>
   </ul>
   <h2>New Features / Improvements</h2>
   <ul>
   <li>Add <code>UseDataStreamForBatch</code> pipeline option to the Flink 
runner. When it is set to true, Flink runner will run batch
   jobs using the DataStream API. By default the option is set to false, so the 
batch jobs are still executed
   using the DataSet API.</li>
   <li><code>upload_graph</code> as one of the Experiments options for 
DataflowRunner is no longer required when the graph is larger than 10MB for 
Java SDK (<a 
href="https://redirect.github.com/apache/beam/pull/28621";>PR#28621</a>.</li>
   <li>state amd side input cache has been enabled to a default of 100 MB. Use 
<code>--max_cache_memory_usage_mb=X</code> to provide cache size for the user 
state API and side inputs. (Python) (<a 
href="https://redirect.github.com/apache/beam/issues/28770";>#28770</a>).</li>
   <li>Beam YAML stable release. Beam pipelines can now be written using YAML 
and leverage the Beam YAML framework which includes a preliminary set of IO's 
and turnkey transforms. More information can be found in the YAML root folder 
and in the <a 
href="https://github.com/apache/beam/blob/master/sdks/python/apache_beam/yaml/README.md";>README</a>.</li>
   </ul>
   <h2>Breaking Changes</h2>
   <ul>
   <li><code>org.apache.beam.sdk.io.CountingSource.CounterMark</code> uses 
custom <code>CounterMarkCoder</code> as a default coder since all Avro-dependent
   classes finally moved to <code>extensions/avro</code>. In case if it's still 
required to use <code>AvroCoder</code> for <code>CounterMark</code>, then,
   as a workaround, a copy of &quot;old&quot; <code>CountingSource</code> class 
should be placed into a project code and used directly
   (<a 
href="https://redirect.github.com/apache/beam/issues/25252";>#25252</a>).</li>
   <li>Renamed <code>host</code> to <code>firestoreHost</code> in 
<code>FirestoreOptions</code> to avoid potential conflict of command line 
arguments (Java) (<a 
href="https://redirect.github.com/apache/beam/pull/29201";>#29201</a>).</li>
   </ul>
   <h2>Bugfixes</h2>
   <ul>
   <li>Fixed &quot;Desired bundle size 0 bytes must be greater than 0&quot; in 
Java SDK's BigtableIO.BigtableSource when you have more cores than bytes to 
read (Java) <a 
href="https://redirect.github.com/apache/beam/issues/28793";>#28793</a>.</li>
   <li><code>watch_file_pattern</code> arg of the <a 
href="https://github.com/apache/beam/blob/104c10b3ee536a9a3ea52b4dbf62d86b669da5d9/sdks/python/apache_beam/ml/inference/base.py#L997";>RunInference</a>
 arg had no effect prior to 2.52.0. To use the behavior of arg 
<code>watch_file_pattern</code> prior to 2.52.0, follow the documentation at <a 
href="https://beam.apache.org/documentation/ml/side-input-updates/";>https://beam.apache.org/documentation/ml/side-input-updates/</a>
 and use <code>WatchFilePattern</code> PTransform as a SideInput. (<a 
href="https://redirect.github.com/apache/beam/pulls/28948";>#28948</a>)</li>
   <li><code>MLTransform</code> doesn't output artifacts such as min, max and 
quantiles. Instead, <code>MLTransform</code> will add a feature to output these 
artifacts as human readable format - <a 
href="https://redirect.github.com/apache/beam/issues/29017";>#29017</a>. For 
now, to use the artifacts such as min and max that were produced by the eariler 
<code>MLTransform</code>, use <code>read_artifact_location</code> of 
<code>MLTransform</code>, which reads artifacts that were produced earlier in a 
different <code>MLTransform</code> (<a 
href="https://redirect.github.com/apache/beam/pull/29016/";>#29016</a>)</li>
   <li>Fixed a memory leak, which affected some long-running Python pipelines: 
<a href="https://redirect.github.com/apache/beam/issues/28246";>#28246</a>.</li>
   </ul>
   <h2>Security Fixes</h2>
   <ul>
   <li>Fixed <a 
href="https://www.cve.org/CVERecord?id=CVE-2023-39325";>CVE-2023-39325</a> 
(Java/Python/Go) (<a 
href="https://redirect.github.com/apache/beam/issues/29118";>#29118</a>).</li>
   <li>Mitigated <a 
href="https://nvd.nist.gov/vuln/detail/CVE-2023-47248";>CVE-2023-47248</a>  
(Python) <a 
href="https://redirect.github.com/apache/beam/issues/29392";>#29392</a>.</li>
   </ul>
   </blockquote>
   </details>
   <details>
   <summary>Commits</summary>
   <ul>
   <li><a 
href="https://github.com/apache/beam/commit/7c8a99779bac68dfadbd7077fe6cbb76d26d04b1";><code>7c8a997</code></a>
 Set version for 2.52.0 RC5</li>
   <li><a 
href="https://github.com/apache/beam/commit/55e7d199a6e6c8475f13da9dc65f7c3c7dcb6441";><code>55e7d19</code></a>
 Mark Avro as provided in harness JAR (<a 
href="https://redirect.github.com/apache/beam/issues/29412";>#29412</a>) (<a 
href="https://redirect.github.com/apache/beam/issues/29415";>#29415</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/d9248c8ddd1588acfe2c643b8170cd72b63b0bbd";><code>d9248c8</code></a>
 Fix MongoDBIO ignore SSL KeyStore not initialized (<a 
href="https://redirect.github.com/apache/beam/issues/29403";>#29403</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/8b6ae4a4c351666deb4b49ecda8822c3e2f578b8";><code>8b6ae4a</code></a>
 Invoke pyarrow_hotfix to alleviate concerns due to CVE-2023-47248. (<a 
href="https://redirect.github.com/apache/beam/issues/29402";>#29402</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/0fdf404873636d24be50ae8360a08e4dddfae679";><code>0fdf404</code></a>
 Revert &quot;Support DatabaseID in Datastore beam connector (<a 
href="https://redirect.github.com/apache/beam/issues/27987";>#27987</a>)&quot; 
(<a href="https://redirect.github.com/apache/beam/issues/29318";>#29318</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/91238ee34f0e94cffff372c233a2b5b63fbbd97c";><code>91238ee</code></a>
 fix typo in workflow (<a 
href="https://redirect.github.com/apache/beam/issues/29300";>#29300</a>) (<a 
href="https://redirect.github.com/apache/beam/issues/29301";>#29301</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/5b5289c23b0020f191f9573e7c417d6d505f05c6";><code>5b5289c</code></a>
 Declare signMavenJavaPublication dependency on copyPom (<a 
href="https://redirect.github.com/apache/beam/issues/29298";>#29298</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/e008971bb8b512fb39f04ef568c2c8f4951adcd2";><code>e008971</code></a>
 [YAML] Fix PyPi caching for non-dev beam (<a 
href="https://redirect.github.com/apache/beam/issues/29292";>#29292</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/058c94738b5657d92e0f93ecba55077624e9cda9";><code>058c947</code></a>
 [YAML] fix renaming provider caching and YAML schema validation (<a 
href="https://redirect.github.com/apache/beam/issues/29290";>#29290</a>)</li>
   <li><a 
href="https://github.com/apache/beam/commit/0e8e54c29c4b4eef0220d88c2b198dbb5e748b72";><code>0e8e54c</code></a>
 [YAML] Fix error handling for KafkaSchemaTransforms (<a 
href="https://redirect.github.com/apache/beam/issues/29261";>#29261</a>) (<a 
href="https://redirect.github.com/apache/beam/issues/29289";>#29289</a>)</li>
   <li>Additional commits viewable in <a 
href="https://github.com/apache/beam/compare/v2.51.0...v2.52.0";>compare 
view</a></li>
   </ul>
   </details>
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