We are happy to present the new 2.76.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.76.0, check out the detailed release notes.

Highlights

I/Os

• Upgraded Iceberg dependency to 1.11.0 (Java) (#38925).
• Add ArrowFlight IO (Java) (#20116).
• (Python) JmsIO (IBM MQ, ActiveMQ, and other providers) is now supported in Python via cross-language (#30716).
• Added a full Iceberg batch and streaming changelog source (CDC) (#38831)
• Added a Delta Lake batch changelog source (CDC) (#39492)

New Features / Improvements

• Added GroupIntoBatches transform and the standard
  beam:coder:sharded_key:v1 coder to the Go SDK, along with
  beam.Coder.IsDeterministic, beam.PCollection.WindowingStrategy,
  and coder.RegisterDeterministicCoder for opt-in deterministic
  custom coders (Go) (#19868).
• TriggerStateMachineRunner changes from BitSetCoder to SentinelBitSetCoder to
  encode finished bitset. SentinelBitSetCoder and BitSetCoder are state
  compatible. Both coders can decode encoded bytes from the other coder
  (#38139).
• (Python) Removed the envoy-data-plane (and transitive betterproto) dependency; EnvoyRateLimiter now uses a small vendored protobuf definition instead, resolving dependency conflicts for downstream projects (#37854).
• (Java) Supported acknowledge mode for JmsIO (#39253).
• (Python) Staged files directory is now automatically added to sys.path on the Python SDK worker at startup. This makes Python files provided via the '--files_to_stage' pipeline option importable in the pipeline code and makes it easier to initialize Python SDK harness at startup via the --beam_plugins pipeline option. For more information, see the Staging Individual Files section of the dependency management docs. This behavior can be disabled by passing the '--experiments=no_staged_dir_in_sys_path' pipeline option (#39431).
• (Python) Added equal_to_approx, an assert_that matcher that compares numeric pipeline outputs with a configurable tolerance (#18028).
• (Python) Timestamp now supports variable subsecond precision, up to nanoseconds. The portable
  beam:logical_type:timestamp:v1 logical type now maps to Python's Timestamp (#39344).
• (Python) Added UnboundedSource, an interface for reading an infinite stream of records with checkpointing, watermark reporting, and bundle finalization. Read one with beam.io.Read
  (#19137).
• (Python) Added Watch, a transform that polls a growing set of outputs for each input element, deduplicates outputs across poll rounds, and stops per a user-supplied termination condition
  (#21521).
• (Python) Added support to analyze core dumps created after python worker segmentation faults with pystack (or gdb if installed) using the --profiler_agent=coredump pipeline option. (#39484).
• (Python) Added Sample.Any, the Python equivalent of Java's Sample.any, which returns up to n arbitrary elements from a PCollection (#18552).
• (Java) Added per-element OpenTelemetry trace propagation across stages in the Dataflow Streaming Runner. Enable it with --experiments=enable_otel_defaults,element_metadata_supported,disable_portable_worker. Cloud Trace incurs additional cost. (#33176)
• (Java) Added OpenTelemetry header propagation support for both reads and writes in KafkaIO and PubSubIO. (#33176)
• (Java) Added OpenTelemetry tracing support for SpannerIO change streams (#33176)

Breaking Changes

• (Python) Removed google-perftools from the SDK container images. Users who wish to use --profiler_agent=tcmalloc should install google-perftools APT package in their custom container images separately (#39323).

• [IcebergIO] Reading a timestamptz column will now return a Timestamp.MICROS Beam logical type to preserve
  microseconds (the old Beam Schema.FieldType#DATETIME primitive type truncates past milliseconds). This may break
  the following use cases when a timestamptz column is present:

  • Existing streaming read pipelines.
  • Managed Iceberg batch reads when upgraded from an older SDK.
  • Python reads.

  Use pipeline option --updateCompatibilityVersion=2.75.0 (or any older version) to keep the old behavior (#39344).

• DoFn.process returning a str, bytes, or dict (instead of an iterable wrapping one) now raises a TypeError rather than silently iterating per-character/byte/key (Python) (#18712).

• (Java) Added DRAINING and DRAINED states to PipelineResult, including runner state mappings and Dataflow update handling (#39020).

• (Python) Typehints of dataclass fields are honored during type inferences. To restore the behavior of fallback-to-any,
  use pipeline option --exclude_infer_dataclass_field_type (#38797).
  However fixing forward is recommended.

• (Java) IcebergIO and projects that use it must now be built with Java 17 or later as a result of Iceberg 1.11.0 upgrade (#38925).

Bugfixes

• Fixed unresolved runtime ValueProvider options being stringified in Python Dataflow Flex Templates (#39499).
• Fixed unbounded checkpoint state growth for splittable DoFns that self-checkpoint on the portable Flink runner (Java) (#27648).
• Improved Java pipeline performance by avoiding repeated DoFn type descriptor resolution when creating cached invokers (#39309).
• (Python) Fixed a memory leak in Python SDK caused by storing exceptions with potentially large stack frames in a cache (#39406).

Known Issues

• (Java) Projects using the Flink runner with Flink 2.1 or later alongside libraries requiring org.lz4:lz4-java (e.g., Kafka clients) may encounter a Gradle capability conflict, because Flink 2.1+ ships at.yawk.lz4:lz4-java which declares the same capability. To resolve, add a capabilitiesResolution rule to your build.gradle that selects at.yawk.lz4:lz4-java (#38947).

According to git shortlog, the following people contributed to the 2.76.0 release. Thank you to all contributors!

ADITYA RAJ, Abdelrahman Ibrahim, Ahmed Abualsaud, Alexander Kolb, Amar3tto, Andrew Crites, Arun Pandian, Aryankn29, Atharva Moroney, Avi Kondareddy, Bruno Volpato, Chamikara Jayalath, Chris Qiu, Claire McGinty, Danny McCormick, Derrick Williams, Elia Liu, Florian TREHAUT, Guflly, HansMarcus01, Ian Liao, Ivy Xu, Jack McCluskey, KRITI MITTAL, Kenneth Knowles, Lalit Yadav, Manvith Panyam, Minh Vu, Nikita Grover, PRADDZY, Peter Tran, Radosław Stankiewicz, Ryan Wigglesworth, Shahar Epstein, Shunping Huang, SreeramaYeshwanthGowd, Steven van Rossum, Tarun Annapareddy, Tejas Iyer, Tobias Kaymak, Tomasz Wojdat, Utkarsh Parekh, Venkata Bharath Malapati, Vitaly Terentyev, Yi Hu, ZIHAN DAI, aibrahiim, akshayjadiyanv, atognolas, claudevdm, janaom, jayjayakumar, raman118, shunping, tvalentyn

We are happy to present the new 2.75.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.75.0, check out the detailed release notes.

Highlights

• Python SDK now supports memory profiling with Memray (#38853).
• (Python) Added Qdrant VectorDatabaseWriteConfig implementation (#38141).

I/Os

• Support for reading from Delta Lake added (Java) (#38551).
• ClickHouseIO: support writing DateTime64(precision[, 'timezone']) columns with sub-second precision (Java) (#38466).
• Upgraded IO Expansion Service to Java 17 (#38974).

New Features / Improvements

• Dataflow Runner v2 has been renamed to Dataflow Portable Runner. Please refer to Dataflow public documentation on when to enable Portable Runner.(#39000).
• (Java) Enabled state tag encoding v2 by default for new Dataflow Streaming Engine jobs. It can be disabled by passing --experiments=disable_streaming_engine_state_tag_encoding_v2 or --updateCompatibilityVersion=2.74.0 pipeline option. Note that the tag encoding version cannot change during a job update. Jobs using tag encoding v2 (enabled by default for new jobs on 2.75.0+) cannot be downgraded to Beam versions prior to 2.73.0, as only versions 2.73.0 and later support tag encoding v2. (#38705).
• (Python) Added instrumentation to support off-the-shelf profiling agents when launching Python SDK Harness (#38853).
• (Java) Added support to the FnApi Data stream protocol allowing runners to isolate bundles slowly processing input from other bundles. (#39001).
• (YAML) Switched js2py library to Quickjs (#38473).
• (YAML) Added HuggingFaceModelHandler for YAML usage (#38696).
• (YAML) Added WriteToMongoDB transform (#38376).
• (YAML) Added WriteToDatadog transform (#38362).
• (Java) Flink 2.1 and 2.2 support is added (#38947) (#38978); Flink 1.17 and 1.18 support is dropped.
• (Python) MqttIO is now supported in Python via cross-language (#21060).

Breaking Changes

• (Python) Typehints of dataclass fields are honored during type inferences. To restore the behavior of fallback-to-any,
  use pipeline option --exclude_infer_dataclass_field_type (#38797).
  However fixing forward is recommended.

Bugfixes

• Fixed GCS filesystem glob matching to correctly handle / in object names and support ** for recursive matching (Go) (#38059).
• Fixed BigQueryEnrichmentHandler batch mode dropping earlier requests when multiple requests share the same enrichment key (Python) (#38035).
• Fixed IcebergIO writing manifest column bounds padded with trailing 0x00 bytes, which broke equality predicate pushdown in some query engines (Java) (#38580).

Known Issues

• (Java) Projects using the Flink runner with Flink 2.1 or later alongside libraries requiring org.lz4:lz4-java (e.g., Kafka clients) may encounter a Gradle capability conflict, because Flink 2.1+ ships at.yawk.lz4:lz4-java which declares the same capability. To resolve, add a capabilitiesResolution rule to your build.gradle that selects at.yawk.lz4:lz4-java (#38947).

According to git shortlog, the following people contributed to the 2.75.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Akshat, Andrew Crites, Andrew Kabas, Anurag Pappula, Arpit Jain, Arun Pandian, Atharv, Chamikara Jayalath, Danny McCormick, Deji Ibrahim, Derrick Williams, Drew Stevens, Durgaprasad M L, Elia Liu, Enzo Maruffa Moreira, Ganesh Sivakumar, Goutam Adwant, HansMarcus01, Jack McCluskey, Joe Santos, Kenneth Knowles, Lalit Yadav, Liam Miller-Cushon, Maciej Szwaja, Manan Mangal, Michael Gruschke, Nikita Grover, Radek Stankiewicz, Radosław Stankiewicz, Reuven Lax, RuiLong J., Sachin Ranjalkar, Sagnik Ghosh, Sam Whittle, Shunping Huang, Subramanya V, Tarun Annapareddy, Tobias Kaymak, TongruiLi, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, aaaZayne, claudevdm, ddebowczyk92, innuendo, kellen, parveensania, tejasiyer-dev

We are happy to present the new 2.74.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.74.0, check out the detailed release notes.

Highlights

• Spark 4 runner support for Java SDK (#38255).

I/Os

• IcebergIO: support declaring a table's sort order on dynamic table creation via the new sort_fields config (#38269).
• IcebergIO: support writing with hash distribution mode, and with autosharding (#38061).

New Features / Improvements

• Capability introduces an indicator for aggregations and timers firing during a pipeline drain, allowing users and sinks to recognize and appropriately handle potentially incomplete or partial data (#36884).
• Added support for setting disk provisioned IOPS and throughput in Dataflow runner via --diskProvisionedIops and --diskProvisionedThroughputMibps pipeline options (Java/Go/Python) (#38349).
• TriggerStateMachineRunner changes from BitSetCoder to SentinelBitSetCoder to
  encode finished bitset. SentinelBitSetCoder and BitSetCoder are state
  compatible. Both coders can decode encoded bytes from the other coder
  (#38139).
• (Python) Added type alias for with_exception_handling to be used for typehints. (#38173).
• (Java) BatchElements transform for Java SDK (#38369)
• Added plugin mechanism to support different Lineage implementations (Java) (#36790).
• (Python) Supported Python user type in Beam SQL. For example, SQL statements like SELECT some_field from PCOLLECTION can now operate a PCollection of Beam Row containing pickable Python user type (#20738).
• (Python) Introduced beam.coders.registry.register_row as preferred API to register a named tuple or dataclass with a Beam Row. At pipelne runtime, the original type associated with the registered row are preserved across the serialization boundary (#38108).

Breaking Changes

• (Python) Made Beartype the default fallback type checking tool. This can be disabled with the --disable_beartype pipeline option. (#38275)

Deprecations

• Dropped Java 8 support (#31678).
• Removed Samza Runner support (#35448).

Bugfixes

• Fixed BigQueryEnrichmentHandler batch mode dropping earlier requests when multiple requests share the same enrichment key (Python) (#38035).
• Added max_batch_duration_secs passthrough support in Python Enrichment BigQuery and CloudSQL handlers so batching duration can be forwarded to BatchElements (#38243).

According to git shortlog, the following people contributed to the 2.74.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Andrew Crites, Andrew Kabas, Arran Cudbard-Bell, Arun Pandian, Asish Kumar, Bentsi Leviav, Blake Jones, Bruno Volpato, Chris Jordan, Danny McCormick, Deji Ibrahim, Derrick Williams, Elia LIU, Ganesh Sivakumar, Jack McCluskey, Kenneth Knowles, Lalit Yadav, M Junaid Shaukat, Matej Aleksandrov, Prabhnoor Singh, Radek Stankiewicz, Radosław Stankiewicz, Reuven Lax, RuiLong J., Sam Whittle, Shunping Huang, Subramanya V, Tarun Annapareddy, Tobias Kaymak, TongruiLi, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, ZIHAN DAI, apanich, bambadiouf1, chenxuesdu, claudevdm, harshadkhetpal, johnjcasey, parveensania, tianz101

We are happy to present the new 2.73.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.73.0, check out the detailed release notes.

Highlights

I/Os

• DebeziumIO (Java): added OffsetRetainer interface and FileSystemOffsetRetainer implementation to persist and restore CDC offsets across pipeline restarts, and exposed withStartOffset / withOffsetRetainer on DebeziumIO.Read and the cross-language ReadBuilder (#28248).

New Features / Improvements

• (Python) Added BigQuery CDC streaming source (#37724)
• Added ADKAgentModelHandler for running Google Agent Development Kit (ADK) agents (Python) (#37917).
• (Python) Added exception chaining to preserve error context in CloudSQLEnrichmentHandler, processes utilities, and core transforms (#37422).
• (Python) Added a pipeline option --experiments=pip_no_build_isolation to disable build isolation when installing dependencies in the runtime environment (#37331).
• (Go) Added OrderedListState support to the Go SDK stateful DoFn API (#37629).
• Added support for large pipeline options via a file (Python) (#37370).
• Supported infer schema from dataclass (Python) (#22085). Default coder for typehint-ed (or set with_output_type) for non-frozen dataclasses changed to RowCoder. To preserve the old behavior (fast primitive coder), explicitly register the type with FastPrimitiveCoder.
• Updates minimum Go version to 1.26.1 (#37897).
• (Python) Added image embedding support in apache_beam.ml.rag package (#37628).
• (Python) Added support for Python version 3.14 (#37247).

Breaking Changes

• The Python SDK container's boot.go now passes pipeline options through a file instead of the PIPELINE_OPTIONS environment variable. If a user pairs a new Python SDK container with an older SDK version (which does not support the file-based approach), the pipeline options will not be recognized and the pipeline will fail. Users must ensure their SDK and container versions are synchronized (#37370).
• Python DoFn.with_exception_handling now respects user DoFn typehints. This can break update compatibility if coders change. It can also break pipeline compilation if existing typehints are incorrect. To update safely sepcify the pipeline option --update_compatibility_version=2.72.0. To fix typehints replace any incorrect typehints that were previously ignored (#37590)

Bugfixes

• Fixed ProcessManager not reaping child processes, causing zombie process accumulation on long-running Flink deployments (Java) (#37930).

Security Fixes

• Fixed CVE-2023-46604 (CVSS 10.0) and CVE-2022-41678 by upgrading ActiveMQ from 5.14.5 to 5.19.2 (Java) (#37943).
• Fixed CVE-2024-1597, CVE-2022-31197, and CVE-2022-21724 by upgrading PostgreSQL JDBC Driver from 42.2.16 to 42.6.2 (Java) (#37942).

List of Contributors

According to git shortlog, the following people contributed to the 2.73.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Alex Malao, Alexander Nieuwenhuijse, Andres Tiko, Andrew Crites, Arun Pandian, Bentsi Leviav, Bruno Volpato, Chamikara Jayalath, Chandra Kiran Bolla, Danny McCormick, Deji Ibrahim, Derrick Williams, Elia LIU, Esmelealem, Hannes Gustafsson, Jack McCluskey, Joey Tran, Kenneth Knowles, M Junaid Shaukat, Mansi Singh, Matej Aleksandrov, Mathijs Deelen, Mattie Fu, Praneet Nadella, Radek Stankiewicz, Radosław Stankiewicz, Reuven Lax, RuiLong J., S. Veyrié, Sakthivel Subramanian, Sam Whittle, Shubham Thakur, Shunping Huang, Subramanya V, Tarun Annapareddy, Tobias Kaymak, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, ZIHAN DAI, claudevdm, kishorepola, parveensania

We are happy to present the new 2.72.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.72.0, check out the detailed release notes.

Highlights

• Flink 2.0 support (#36947).

I/Os

• Add Datadog IO support (Java) (#37318).
• Remove Pubsublite IO support, since service will be deprecated in March 2026. (#37375).
• (Java) ClickHouse - migrating from the legacy JDBC driver (v0.6.3) to ClickHouse Java Client v2 (v0.9.6). See the class documentation for migration guide (#37610).
• (Java) Upgraded GoogleAdsIO to use GoogleAdsIO API v23 (#37620).

New Features / Improvements

• (Python) Added exception chaining to preserve error context in CloudSQLEnrichmentHandler, processes utilities, and core transforms (#37422).
• (Python) Added a pipeline option --experiments=pip_no_build_isolation to disable build isolation when installing dependencies in the runtime environment (#37331).

Deprecations

• (Python) Removed previously deprecated list_prefix method for filesystem interfaces (#37587).

Bugfixes

• Fixed (Yaml) issue with validate compatible method (#37588).
• Fixed (Yaml) issue with Create transform dealing with different type elements (#37585).

Security Fixes

• Fixed CVE-2024-28397 by switching from js2py to pythonmonkey (Yaml) (#37560).

List of Contributors

According to git shortlog, the following people contributed to the 2.72.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Andrew Crites, Arun Pandian, Ben Feinstein, Bentsi Leviav, Celeste Zeng, Danny McCormick, Danny Mccormick, Derrick Williams, Elia LIU, Ganesh, Jack McCluskey, Kenneth Knowles, Labesse Kévin, M Junaid Shaukat, Mansi Singh, Mattie Fu, Nayan Mathur, Pablo Estrada, Pirzada Ahmad Faraz, Radek Stankiewicz, Radosław Stankiewicz, Robert Bradshaw, Rohan Sah, RuiLong J., Sakthivel Subramanian, Sam Whittle, Shaheer Amjad, Shunping Huang, Steven van Rossum, Tarun Annapareddy, Tobias Kaymak, Valentyn Tymofieiev, Vitaly Terentyev, Yi Hu, XQ Hu, ZIHAN DAI, apanich, chenxuesdu, claudevdm, franzonia137

We are happy to present the new 2.71.0 release of Beam.
This release includes both improvements and new functionality.

For more information on changes in 2.71.0, check out the detailed release notes.

I/Os

• (Java) Elasticsearch 9 Support (#36491).
• (Java) Upgraded HCatalogIO to Hive 4.0.1 (#32189).

New Features / Improvements

• Support configuring Firestore database on ReadFn transforms (Java) (#36904).
• (Python) Inference args are now allowed in most model handlers, except where they are explicitly/intentionally disallowed (#37093).

Bugfixes

• Fixed FirestoreV1 Beam connectors allow configuring inconsistent project/database IDs between RPC requests and routing headers #36895 (Java) (#36895).
• Logical type and coder registry are saved for pipelines in the case of default pickler. This fixes a side effect of switching to cloudpickle as default pickler in Beam 2.65.0 (Python) (#35738).

Known Issues

For the most up to date list of known issues, see https://github.com/apache/beam/blob/master/CHANGES.md

List of Contributors

According to git shortlog, the following people contributed to the 2.71.0 release. Thank you to all contributors!

Abacn, Ahmed Abualsaud, Amar3tto, Andrew Crites, apanich, Arun, Arun Pandian, assaf127, Chamikara Jayalath, CherisPatelInfocusp, Cheskel Twersky, Claire McGinty, Claude, Danny Mccormick, dependabot[bot], Derrick Williams, Egbert van der Wal, Evan Galpin, Ganesh, github-actions[bot], hekk-kaori-maeda, Jack Dingilian, Jack McCluskey, JayajP, Jiang Zhu, Kenneth Knowles, liferoad, M Junaid Shaukat, Nayan Mathur, Noah Stapp, Paco Avila, Radek Stankiewicz, Radosław Stankiewicz, Robert Stupp, Sam Whittle, Shunping Huang, Steven van Rossum, Suvrat Acharya, Tarun Annapareddy, tvalentyn, Utkarsh Parekh, Vitaly Terentyev, Xiaochu Liu, Yala Huang Feng, Yi Hu, Yu Watanabe, zhan7236

We are happy to present the new 2.70.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.70.0, check out the detailed release notes.

Highlights

• Flink 1.20 support added (#32647).

New Features / Improvements

• Python examples added for Milvus search enrichment handler on Beam Website
  including jupyter notebook example (Python) (#36176).
• Milvus sink I/O connector added (Python) (#36702).
  Now Beam has full support for Milvus integration including Milvus enrichment and sink operations.

Breaking Changes

• (Python) Some Python dependencies have been split out into extras. To ensure all previously installed dependencies are installed, when installing Beam you can pip install apache-beam[gcp,interactive,yaml,redis,hadoop,tfrecord], though most users will not need all of these extras (#34554).

Deprecations

• (Python) Python 3.9 reached EOL in October 2025 and support for the language version has been removed. (#36665).

List of Contributors

According to git shortlog, the following people contributed to the 2.70.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Alex Chermenin, Andrew Crites, Arun Pandian, Celeste Zeng, Chamikara Jayalath, Chenzo, Claire McGinty, Danny McCormick, Derrick Williams, Dustin Rhodes, Enrique Calderon, Ian Liao, Jack McCluskey, Jessica Hsiao, Joey Tran, Karthik Talluri, Kenneth Knowles, Maciej Szwaja, Mehdi.D, Mohamed Awnallah, Praneet Nadella, Radek Stankiewicz, Radosław Stankiewicz, Reuven Lax, RuiLong J., S. Veyrié, Sam Whittle, Shunping Huang, Stephan Hoyer, Steven van Rossum, Tanu Sharma, Tarun Annapareddy, Tom Stepp, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, changliiu, claudevdm, fozzie15, kristynsmith, wolfchris-google

We are happy to present the new 2.69.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.69.0, check out the detailed release notes.

Highlights

• (Python) Add YAML Editor and Visualization Panel (#35772).
• (Java) Java 25 Support (#35772).

I/Os

• Upgraded Iceberg dependency to 1.10.0 (#36123).

New Features / Improvements

• Enhance JAXBCoder with XMLInputFactory support (Java) (#36446).
• Python examples added for CloudSQL enrichment handler on Beam website (Python) (#35473).
• Support for batch mode execution in WriteToPubSub transform added (Python) (#35990).
• Added official support for Python 3.13 (#34869).
• Added an optional output_schema verification to all YAML transforms (#35952).
• Support for encryption when using GroupByKey added, along with --gbek pipeline option to automatically replace all GroupByKey transforms (Java/Python) (#36214).

Breaking Changes

• (Python) dill is no longer a required, default dependency for Apache Beam (#21298).
  • This change only affects pipelines that explicitly use the pickle_library=dill pipeline option.
  • While dill==0.3.1.1 is still pre-installed on the official Beam SDK base images, it is no longer a direct dependency of the apache-beam Python package. This means it can be overridden by other dependencies in your environment.
  • If your pipeline uses pickle_library=dill, you must manually ensure dill==0.3.1.1 is installed in both your submission and runtime environments.
    • Submission environment: Install the dill extra in your local environment pip install apache-beam[gcpdill].
    • Runtime (worker) environment: Your action depends on how you manage your worker's environment.
      • If using default containers or custom containers with the official Beam base image e.g. FROM apache/beam_python3.10_sdk:2.69.0
        • Add dill==0.3.1.1 to your worker's requirements file (e.g., requirements.txt)
        • Pass this file to your pipeline using the --requirements_file requirements.txt pipeline option (For more details see managing Dataflow dependencies).
      • If custom containers with a non-Beam base image e.g. FROM python:3.9-slim
        • Install apache-beam with the dill extra in your docker file e.g. RUN pip install --no-cache-dir apache-beam[gcp,dill]
  • If there is a dill version mismatch between submission and runtime environments you might encounter unpickling errors like Can't get attribute '_create_code' on <module 'dill._dill' from....
  • If dill is not installed in the runtime environment you will see the error ImportError: Pipeline option pickle_library=dill is set, but dill is not installed...
  • Report any issues you encounter when using pickle_library=dill to the GitHub issue (#21298)
• (Python) Added a pickle_library=dill_unsafe pipeline option. This allows overriding dill==0.3.1.1 using dill as the pickle_library. Use with extreme caution. Other versions of dill has not been tested with Apache Beam (#21298).
• (Python) The deterministic fallback coder for complex types like NamedTuple, Enum, and dataclasses now normalizes filepaths for better determinism guarantees. This affects streaming pipelines updating from 2.68 to 2.69 that utilize this fallback coder. If your pipeline is affected, you may see a warning like: "Using fallback deterministic coder for type X...". To update safely sepcify the pipeline option --update_compatibility_version=2.68.0 (#36345).
• (Python) Fixed transform naming conflict when executing DataTransform on a dictionary of PColls (#30445).
  This may break update compatibility if you don't provide a --transform_name_mapping.
• Removed deprecated Hadoop versions (2.10.2 and 3.2.4) that are no longer supported for Iceberg from IcebergIO (#36282).
• (Go) Coder construction on SDK side is more faithful to the specs from runners without stripping length-prefix. This may break streaming pipeline update as the underlying coder could be changed (#36387).
• Minimum Go version for Beam Go updated to 1.25.2 (#36461).
• (Java) DoFn OutputReceiver now requires implementing a builder method as part of extended metadata support for elements (#34902).
• (Java) Removed ProcessContext outputWindowedValue introduced in 2.68 that allowed setting offset and record Id. Use OutputReceiver's builder to set those field ([#36523]#36523).

Bugfixes

• Fixed passing of pipeline options to x-lang transforms when called from the Java SDK (Java) (#36443).
• PulsarIO has now changed support status from incomplete to experimental. Both read and writes should now minimally
  function (un-partitioned topics, without schema support, timestamp ordered messages for read) (Java)
  (#36141).
• Fixed Spanner Change Stream reading stuck issue due to watermark of partition moving backwards (#36470).

List of Contributors

According to git shortlog, the following people contributed to the 2.69.0 release. Thank you to all contributors!

Abdelrahman Ibrahim, Ahmed Abualsaud, Andrew Crites, Arun Pandian, Bryan Dang, Chamikara Jayalath, Charles Nguyen, Chenzo, Clay Johnson, Danny McCormick, David A, Derrick Williams, Enrique Calderon, Hai Joey Tran, Ian Liao, Ian Mburu, Jack McCluskey, Jiang Zhu, Joey Tran, Kenneth Knowles, Kyle Stanley, Maciej Szwaja, Minbo Bae, Mohamed Awnallah, Radek Stankiewicz, Radosław Stankiewicz, Razvan Culea, Reuven Lax, Sagnik Ghosh, Sam Whittle, Shunping Huang, Steven van Rossum, Talat UYARER, Tanu Sharma, Tarun Annapareddy, Tom Stepp, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, Yilei, claudevdm, flpablo, fozzie15, johnjcasey, lim1t, parveensania, yashu

We are happy to present the new 2.68.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.68.0, check out the detailed release notes.

Highlights

• [Python] Prism runner now enabled by default for most Python pipelines using the direct runner (#34612). This may break some tests, see #34612 for details on how to handle issues.

I/Os

• Upgraded Iceberg dependency to 1.9.2 (#35981)

New Features / Improvements

• BigtableRead Connector for BeamYaml added with new Config Param (#35696)
• MongoDB Java driver upgraded from 3.12.11 to 5.5.0 with API refactoring and GridFS implementation updates (Java) (#35946).
• Introduced a dedicated module for JUnit-based testing support: sdks/java/testing/junit, which provides TestPipelineExtension for JUnit 5 while maintaining backward compatibility with existing JUnit 4 TestRule-based tests (Java) (#18733, #35688).
  • To use JUnit 5 with Beam tests, add a test-scoped dependency on org.apache.beam:beam-sdks-java-testing-junit.
• Google CloudSQL enrichment handler added (Python) (#34398).
  Beam now supports data enrichment capabilities using SQL databases, with built-in support for:
  • Managed PostgreSQL, MySQL, and Microsoft SQL Server instances on CloudSQL
  • Unmanaged SQL database instances not hosted on CloudSQL (e.g., self-hosted or on-premises databases)
• [Python] Added the ReactiveThrottler and ThrottlingSignaler classes to streamline throttling behavior in DoFns, expose throttling mechanisms for users (#35984)
• Added a pipeline option to specify the processing timeout for a single element by any PTransform (Java/Python/Go) (#35174).
  • When specified, the SDK harness automatically restarts if an element takes too long to process. Beam runner may then retry processing of the same work item.
  • Use the --element_processing_timeout_minutes option to reduce the chance of having stalled pipelines due to unexpected cases of slow processing, where slowness might not happen again if processing of the same element is retried.
• (Python) Adding GCP Spanner Change Stream support for Python (apache_beam.io.gcp.spanner) (#24103).

Breaking Changes

• Previously deprecated Beam ZetaSQL component has been removed (#34423).
  ZetaSQL users could migrate to Calcite SQL with BigQuery dialect enabled.
• Upgraded Beam vendored Calcite to 1.40.0 for Beam SQL (#35483), which
  improves support for BigQuery and other SQL dialects. Note: Minor behavior changes are observed such as output
  significant digits related to casting.
• (Python) The deterministic fallback coder for complex types like NamedTuple, Enum, and dataclasses now uses cloudpickle instead of dill. If your pipeline is affected, you may see a warning like: "Using fallback deterministic coder for type X...". You can revert to the previous behavior by using the pipeline option --update_compatibility_version=2.67.0 (35725). Report any pickling related issues to #34903
• (Python) Prism runner now enabled by default for most Python pipelines using the direct runner (#34612). This may break some tests, see #34612 for details on how to handle issues.
• Dropped Java 8 support for IO expansion-service. Cross-language pipelines using this expansion service will need a Java11+ runtime (#35981.

Deprecations

• Python SDK native SpannerIO (apache_beam/io/gcp/experimental/spannerio) is deprecated. Use cross-language wrapper
  (apache_beam/io/gcp/spanner) instead (Python) (#35860).
• Samza runner is deprecated and scheduled for removal in Beam 3.0 (#35448).
• Twister2 runner is deprecated and scheduled for removal in Beam 3.0 (#35905)).

Bugfixes

• (Python) Fixed Java YAML provider fails on Windows (#35617).
• Fixed BigQueryIO creating temporary datasets in wrong project when temp_dataset is specified with a different project than the pipeline project. For some jobs, temporary datasets will now be created in the correct project (Python) (#35813).
• (Go) Fix duplicates due to reads after blind writes to Bag State (#35869).
  • Earlier Go SDK versions can avoid the issue by not reading in the same call after a blind write.

List of Contributors

According to git shortlog, the following people contributed to the 2.68.0 release. Thank you to all contributors!

Ahmed Abualsaud, Andrew Crites, Ashok Devireddy, Chamikara Jayalath, Charles Nguyen, Danny McCormick, Davda James, Derrick Williams, Diego Hernandez, Dip Patel, Dustin Rhodes, Enrique Calderon, Hai Joey Tran, Jack McCluskey, Kenneth Knowles, Keshav, Khorbaladze A., LEEKYE, Lanny Boarts, Mattie Fu, Minbo Bae, Mohamed Awnallah, Naireen Hussain, Nathaniel Young, Radosław Stankiewicz, Razvan Culea, Robert Bradshaw, Robert Burke, Sam Whittle, Shehab, Shingo Furuyama, Shunping Huang, Steven van Rossum, Suvrat Acharya, Svetak Sundhar, Tarun Annapareddy, Tom Stepp, Valentyn Tymofieiev, Vitaly Terentyev, XQ Hu, Yi Hu, apanich, arnavarora2004, claudevdm, flpablo, kristynsmith, shreyakhajanchi

We are happy to present the new 2.67.0 release of Beam.
This release includes both improvements and new functionality.
See the download page for this release.

For more information on changes in 2.67.0, check out the detailed release notes.

Highlights

I/Os

• Debezium IO upgraded to 3.1.1 requires Java 17 (Java) (#34747).
• Add support for streaming writes in IOBase (Python)
• Implement support for streaming writes in FileBasedSink (Python)
• Expose support for streaming writes in TextIO (Python)

New Features / Improvements

• Added support for Processing time Timer in the Spark Classic runner (#33633).
• Add pip-based install support for JupyterLab Sidepanel extension (#35397).
• [IcebergIO] Create tables with a specified table properties (#35496)
• Add support for comma-separated options in Python SDK (Python) (#35580).
  Python SDK now supports comma-separated values for experiments and dataflow_service_options,
  matching Java SDK behavior while maintaining backward compatibility.
• Milvus enrichment handler added (Python) (#35216).
  Beam now supports Milvus enrichment handler capabilities for vector, keyword,
  and hybrid search operations.
• [Beam SQL] Add support for DATABASEs, with an implementation for Iceberg (#35637)
• Respect BatchSize and MaxBufferingDuration when using JdbcIO.WriteWithResults. Previously, these settings were ignored (#35669).

Breaking Changes

• Go: The pubsubio.Read transform now accepts ReadOptions as a value type instead of a pointer, and requires exactly one of Topic or Subscription to be set (they are mutually exclusive). Additionally, the ReadOptions struct now includes a Topic field for specifying the topic directly, replacing the previous topic parameter in the Read function signature ([#35369])(#35369).
• SQL: The ParquetTable external table provider has changed its handling of the LOCATION property. To read from a directory, the path must now end with a trailing slash (e.g., LOCATION '/path/to/data/'). Previously, a trailing slash was not required. This change was made to enable support for glob patterns and single-file paths ([#35582])(#35582).

Bugfixes

• [YAML] Fixed handling of missing optional fields in JSON parsing (#35179).
• [Python] Fix WriteToBigQuery transform using CopyJob does not work with WRITE_TRUNCATE write disposition (#34247)
• [Python] Fixed dicomio tags mismatch in integration tests (#30760).
• [Java] Fixed spammy logging issues that affected versions 2.64.0 to 2.66.0.

Known Issues

• (#35666). YAML Flatten incorrectly drops fields when input PCollections' schema are different. This issue exists for all versions since 2.52.0.

List of Contributors

According to git shortlog, the following people contributed to the 2.66.0 release. Thank you to all contributors!

Aditya Shukla, Ahmed Abualsaud, Arun Pandian, Boris Li, Chamikara Jayalath, Charles Nguyen, Chenzo, Danny McCormick, David Adeniji, Derrick Williams, Dmytro Tsyliuryk, Dustin Rhodes, Enrique Calderon, Gottipati Gautam, Hai Joey Tran, Hunor Portik, Jack McCluskey, Kenneth Knowles, Khorbaladze A., Marcio Sugar, Minh Son Nguyen, Mohamed Awnallah, Nathaniel Young, Nhon Dinh, Quentin Sommer, Rafael Raposo, Rakesh Kumar, Razvan Culea, Reuven Lax, Robert Bradshaw, Sam Whittle, Shunping Huang, Steven van Rossum, Talat UYARER, Tanu Sharma, Tarun Annapareddy, Tobi Kaymak, Tobias Kaymak, Valentyn Tymofieiev, Veronica Wasson, Vitaly Terentyev, XQ Hu, Yi Hu, akashorabek, arnavarora2004, changliiu, claudevdm, fozzie15, mvhensbergen, twosom