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Bump beam.version from 2.61.0 to 2.64.0 #977

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Bumps beam.version from 2.61.0 to 2.64.0.
Updates org.apache.beam:beam-sdks-java-bom from 2.61.0 to 2.64.0

Release notes

Sourced from org.apache.beam:beam-sdks-java-bom's releases.

Beam 2.64.0 release

We are happy to present the new 2.64.0 release of Beam. This release includes both improvements and new functionality. See the download page for this release.

For more information on changes in 2.64.0, check out the detailed release notes.

Highlights

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).

... (truncated)

Changelog

Sourced from org.apache.beam:beam-sdks-java-bom's changelog.

[2.64.0] - 2025-03-31

Highlights

  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • New highly anticipated feature X added to Python SDK (#X).
  • New highly anticipated feature Y added to Java SDK (#Y).

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • [YAML] Beam YAML UDFs (such as those used in MapToFields) can now have declared dependencies (e.g. pypi packages for Python, or extra jars for Java).
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).
  • (Java) Fix BigQuery Storage Write compatibility with Avro 1.8 (#34281).
  • Fixed checkpoint recovery and streaming behavior in Spark Classic and Portable runner's Flatten transform by replacing queueStream with SingleEmitInputDStream (#34080, #18144, #20426)
  • (Java) Fixed Read caching of UnboundedReader objects to effectively cache across multiple DoFns and avoid checkpointing unstarted reader. #34146 #33901

Known Issues

  • (Java) Current version of protobuf has a bug leading to incompatibilities with clients using older versions of Protobuf (example issue). This issue has been seen in SpannerIO in particular. Tracked in #34452.
  • (Java) When constructing SpannerConfig for SpannerIO, calling withHost with a null or empty host will now result in a Null Pointer Exception (java.lang.NullPointerException: Cannot invoke "java.lang.CharSequence.length()" because "this.text" is null). See GoogleCloudPlatform/DataflowTemplates#34489 for context.

[2.63.0] - 2025-02-18

I/Os

  • Support gcs-connector 3.x+ in GcsUtil (#33368)

... (truncated)

Commits

Updates org.apache.beam:beam-sdks-java-core from 2.61.0 to 2.64.0

Release notes

Sourced from org.apache.beam:beam-sdks-java-core's releases.

Beam 2.64.0 release

We are happy to present the new 2.64.0 release of Beam. This release includes both improvements and new functionality. See the download page for this release.

For more information on changes in 2.64.0, check out the detailed release notes.

Highlights

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).

... (truncated)

Changelog

Sourced from org.apache.beam:beam-sdks-java-core's changelog.

[2.64.0] - 2025-03-31

Highlights

  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • New highly anticipated feature X added to Python SDK (#X).
  • New highly anticipated feature Y added to Java SDK (#Y).

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • [YAML] Beam YAML UDFs (such as those used in MapToFields) can now have declared dependencies (e.g. pypi packages for Python, or extra jars for Java).
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).
  • (Java) Fix BigQuery Storage Write compatibility with Avro 1.8 (#34281).
  • Fixed checkpoint recovery and streaming behavior in Spark Classic and Portable runner's Flatten transform by replacing queueStream with SingleEmitInputDStream (#34080, #18144, #20426)
  • (Java) Fixed Read caching of UnboundedReader objects to effectively cache across multiple DoFns and avoid checkpointing unstarted reader. #34146 #33901

Known Issues

  • (Java) Current version of protobuf has a bug leading to incompatibilities with clients using older versions of Protobuf (example issue). This issue has been seen in SpannerIO in particular. Tracked in #34452.
  • (Java) When constructing SpannerConfig for SpannerIO, calling withHost with a null or empty host will now result in a Null Pointer Exception (java.lang.NullPointerException: Cannot invoke "java.lang.CharSequence.length()" because "this.text" is null). See GoogleCloudPlatform/DataflowTemplates#34489 for context.

[2.63.0] - 2025-02-18

I/Os

  • Support gcs-connector 3.x+ in GcsUtil (#33368)

... (truncated)

Commits

Updates org.apache.beam:beam-runners-direct-java from 2.61.0 to 2.64.0

Release notes

Sourced from org.apache.beam:beam-runners-direct-java's releases.

Beam 2.64.0 release

We are happy to present the new 2.64.0 release of Beam. This release includes both improvements and new functionality. See the download page for this release.

For more information on changes in 2.64.0, check out the detailed release notes.

Highlights

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).

... (truncated)

Changelog

Sourced from org.apache.beam:beam-runners-direct-java's changelog.

[2.64.0] - 2025-03-31

Highlights

  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • New highly anticipated feature X added to Python SDK (#X).
  • New highly anticipated feature Y added to Java SDK (#Y).

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • [YAML] Beam YAML UDFs (such as those used in MapToFields) can now have declared dependencies (e.g. pypi packages for Python, or extra jars for Java).
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).
  • (Java) Fix BigQuery Storage Write compatibility with Avro 1.8 (#34281).
  • Fixed checkpoint recovery and streaming behavior in Spark Classic and Portable runner's Flatten transform by replacing queueStream with SingleEmitInputDStream (#34080, #18144, #20426)
  • (Java) Fixed Read caching of UnboundedReader objects to effectively cache across multiple DoFns and avoid checkpointing unstarted reader. #34146 #33901

Known Issues

  • (Java) Current version of protobuf has a bug leading to incompatibilities with clients using older versions of Protobuf (example issue). This issue has been seen in SpannerIO in particular. Tracked in #34452.
  • (Java) When constructing SpannerConfig for SpannerIO, calling withHost with a null or empty host will now result in a Null Pointer Exception (java.lang.NullPointerException: Cannot invoke "java.lang.CharSequence.length()" because "this.text" is null). See GoogleCloudPlatform/DataflowTemplates#34489 for context.

[2.63.0] - 2025-02-18

I/Os

  • Support gcs-connector 3.x+ in GcsUtil (#33368)

... (truncated)

Commits

Updates org.apache.beam:beam-runners-google-cloud-dataflow-java from 2.61.0 to 2.64.0

Release notes

Sourced from org.apache.beam:beam-runners-google-cloud-dataflow-java's releases.

Beam 2.64.0 release

We are happy to present the new 2.64.0 release of Beam. This release includes both improvements and new functionality. See the download page for this release.

For more information on changes in 2.64.0, check out the detailed release notes.

Highlights

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).

... (truncated)

Changelog

Sourced from org.apache.beam:beam-runners-google-cloud-dataflow-java's changelog.

[2.64.0] - 2025-03-31

Highlights

  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • New highly anticipated feature X added to Python SDK (#X).
  • New highly anticipated feature Y added to Java SDK (#Y).

I/Os

  • [Java] Use API compatible with both com.google.cloud.bigdataoss:util 2.x and 3.x in BatchLoads (#34105)
  • [IcebergIO] Added new CDC source for batch and streaming, available as Managed.ICEBERG_CDC (#33504)
  • [IcebergIO] Address edge case where bundle retry following a successful data commit results in data duplication (#34264)

New Features / Improvements

  • [Python] Support custom coders in Reshuffle (#29908, #33356).
  • [Java] Upgrade SLF4J to 2.0.16. Update default Spark version to 3.5.0. (#33574)
  • [Java] Support for --add-modules JVM option is added through a new pipeline option JdkAddRootModules. This allows extending the module graph with optional modules such as SDK incubator modules. Sample usage: <pipeline invocation> --jdkAddRootModules=jdk.incubator.vector (#30281).
  • Managed API for Java and Python supports key I/O connectors Iceberg, Kafka, and BigQuery.
  • [YAML] Beam YAML UDFs (such as those used in MapToFields) can now have declared dependencies (e.g. pypi packages for Python, or extra jars for Java).
  • Prism now supports event time triggers for most common cases. (#31438)
    • Prism does not yet support triggered side inputs, or triggers on merging windows (such as session windows).

Breaking Changes

  • [Python] Reshuffle now correctly respects user-specified type hints, fixing a previous bug where it might use FastPrimitivesCoder wrongly. This change could break pipelines with incorrect type hints in Reshuffle. If you have issues after upgrading, temporarily set update_compatibility_version to a previous Beam version to use the old behavior. The recommended solution is to fix the type hints in your code. (#33932)
  • [Java] SparkReceiver 2 has been moved to SparkReceiver 3 that supports Spark 3.x. (#33574)
  • [Python] Correct parsing of collections.abc.Sequence type hints was added, which can lead to pipelines failing type hint checks that were previously passing erroneously. These issues will be most commonly seen trying to consume a PCollection with a Sequence type hint after a GroupByKey or a CoGroupByKey. (#33999.

Bugfixes

  • (Python) Fixed occasional pipeline stuckness that was affecting Python 3.11 users (#33966).
  • (Java) Fixed TIME field encodings for BigQuery Storage API writes on GenericRecords (#34059).
  • (Java) Fixed a race condition in JdbcIO which could cause hangs trying to acquire a connection (#34058).
  • (Java) Fix BigQuery Storage Write compatibility with Avro 1.8 (#34281).
  • Fixed checkpoint recovery and streaming behavior in Spark Classic and Portable runner's Flatten transform by replacing queueStream with SingleEmitInputDStream (#34080, #18144, #20426)
  • (Java) Fixed Read caching of UnboundedReader objects to effectively cache across multiple DoFns and avoid checkpointing unstarted reader. #34146 #33901

Known Issues

  • (Java) Current version of protobuf has a bug leading to incompatibilities with clients using older versions of Protobuf (example issue). This issue has been seen in SpannerIO in particular. Tracked in #34452.
  • (Java) When constructing SpannerConfig for SpannerIO, calling withHost with a null or empty host will now result in a Null Pointer Exception (java.lang.NullPointerException: Cannot invoke "java.lang.CharSequence.length()" because "this.text" is null). See GoogleCloudPlatform/DataflowTemplates#34489 for context.

[2.63.0] - 2025-02-18

I/Os

  • Support gcs-connector 3.x+ in GcsUtil (#33368)

... (truncated)

Commits

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@dependabot
Bump beam.version from 2.61.0 to 2.64.0
22c1ac7 
Bumps `beam.version` from 2.61.0 to 2.64.0.

Updates `org.apache.beam:beam-sdks-java-bom` from 2.61.0 to 2.64.0
- [Release notes](https://github.com/apache/beam/releases)
- [Changelog](https://github.com/apache/beam/blob/master/CHANGES.md)
- [Commits](apache/beam@v2.61.0...v2.64.0)

Updates `org.apache.beam:beam-sdks-java-core` from 2.61.0 to 2.64.0
- [Release notes](https://github.com/apache/beam/releases)
- [Changelog](https://github.com/apache/beam/blob/master/CHANGES.md)
- [Commits](apache/beam@v2.61.0...v2.64.0)

Updates `org.apache.beam:beam-runners-direct-java` from 2.61.0 to 2.64.0
- [Release notes](https://github.com/apache/beam/releases)
- [Changelog](https://github.com/apache/beam/blob/master/CHANGES.md)
- [Commits](apache/beam@v2.61.0...v2.64.0)

Updates `org.apache.beam:beam-runners-google-cloud-dataflow-java` from 2.61.0 to 2.64.0
- [Release notes](https://github.com/apache/beam/releases)
- [Changelog](https://github.com/apache/beam/blob/master/CHANGES.md)
- [Commits](apache/beam@v2.61.0...v2.64.0)

---
updated-dependencies:
- dependency-name: org.apache.beam:beam-sdks-java-bom
  dependency-version: 2.64.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
- dependency-name: org.apache.beam:beam-sdks-java-core
  dependency-version: 2.64.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
- dependency-name: org.apache.beam:beam-runners-direct-java
  dependency-version: 2.64.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
- dependency-name: org.apache.beam:beam-runners-google-cloud-dataflow-java
  dependency-version: 2.64.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

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@dependabot dependabot bot added dependencies Pull requests that update a dependency file java Pull requests that update java code labels Apr 1, 2025
@dependabot dependabot bot mentioned this pull request Apr 1, 2025
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