SDK Version Support Status

Warning: Cloud Dataflow SDK 1.x for Java is unsupported as of October 16, 2018. See Migrating from Cloud Dataflow SDK 1.x for Java for migration guidance.

SDK Decommission Notice: The following SDK versions will be decommissioned in late 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.

• Apache Beam SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Apache Beam SDK for Python, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Python, 2.0.0 to 2.4.0 (inclusive)

Previously, the date planned for this decommissioning was March 25, 2019, but in response to customer requests, we are extending this timeline. The new end date has yet to be finalized but is expected to happen in 2019. When decommissioning happens, you will no longer be able to submit new Cloud Dataflow jobs or update running Cloud Dataflow jobs that use the decommissioned SDKs. In addition, existing streaming jobs that use these SDK versions may fail.

Cloud Dataflow SDK Deprecation Notice: The Cloud Dataflow SDK 2.5.0 is the last Cloud Dataflow SDK release that is separate from the Apache Beam SDK releases. The Cloud Dataflow service supports official Apache Beam SDK releases as documented in the SDK version support status page.

This page lists the support status for Apache Beam and Cloud Dataflow SDK releases:

• Apache Beam 2.x SDKs
• Cloud Dataflow 2.x SDKs
• Cloud Dataflow 1.x SDKs

Apache Beam 2.x SDKs

SDK Decommission Notice: The following SDK versions will be decommissioned in late 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.

• Apache Beam SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Apache Beam SDK for Python, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Python, 2.0.0 to 2.4.0 (inclusive)

Previously, the date planned for this decommissioning was March 25, 2019, but in response to customer requests, we are extending this timeline. The new end date has yet to be finalized but is expected to happen in 2019. When decommissioning happens, you will no longer be able to submit new Cloud Dataflow jobs or update running Cloud Dataflow jobs that use the decommissioned SDKs. In addition, existing streaming jobs that use these SDK versions may fail.

Apache Beam is an open source, community-led project. Google is part of the community, but we do not own the project or control the release process. We might open bugs or submit patches to the Apache Beam codebase on behalf of Cloud Dataflow customers, but we cannot create hotfixes or official releases of Apache Beam on demand.

However, the Apache Beam community designates specific releases as long term support (LTS) releases. LTS releases receive patches to fix major issues for a designated period of time. See the Apache Beam policies page for more details about release policies.

Note: Development SDK versions (marked as -SNAPSHOT for Java and .dev for Python) are unsupported.

The following tables contains the support status for the Apache Beam 2.x SDKs:

Java

Cloud Dataflow supports specific Apache Beam SDK components for the SDK releases listed below. These components have been tested thoroughly with Cloud Dataflow. Experimental features are not supported.

See the Apache Beam release notes for change information.

SDK version(s)	Status	Supported components	Details
2.13.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on June 6, 2020. This release adds experimental support for JDK 9 or above. See the Apache Beam issue tracker for more information.
2.12.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on April 25, 2020. Known issues: The Cloud Dataflow runner has an incorrect logging configuration that might cause all logs to be missing. To work around this issue, add slf4j-jdk14 to your runtime dependencies.
2.11.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on March 1, 2020. Known issues: The Cloud Dataflow runner has an incorrect logging configuration that might cause all logs to be missing. To work around this issue, add slf4j-jdk14 to your runtime dependencies.
2.10.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on February 11, 2020. Known issues: SDK 2.10.0 depends on gcsio client library version 1.9.13, which has known issues: Reading side inputs can result in sending a large number of requests to Cloud Storage. As a result, Cloud Dataflow jobs can fail with HTTP 429 errors from Cloud Storage. Apache Beam ParquetIO fails when reading files from Cloud Storage. To work around these issues, either upgrade to SDK 2.11.0, or override the gcsio client library version to 1.9.16 or later. The Cloud Dataflow runner has an incorrect logging configuration that might cause all logs to be missing. To work around this issue, add slf4j-jdk14 to your runtime dependencies.
2.9.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on December 13, 2019. Known issues: Users enabling the Streaming Engine (Beta) experiment should not upgrade to SDK 2.9.0 due to a known issue. If you choose to use SDK 2.9.0, you must also set the enable_conscrypt_security_provider experimental flag to enable Conscrypt, which has known stability issues. In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.8.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on October 25, 2019. Known issues: Pipelines might become stuck due to an issue with the Conscrypt library. If you see errors in Stackdriver logging with stack traces that include Conscrypt related calls, you might be affected by this issue. To resolve the issue, upgrade to SDK 2.9.0 or higher. In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.7.0 LTS	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	Apache Beam SDK 2.7.0 is a long term support (LTS) release and will receive patches until May 16, 2019. This version will be deprecated on October 3, 2019. Known issues: Pipelines might become stuck due to an issue with the Conscrypt library. If you see errors in Stackdriver logging with stack traces that include Conscrypt related calls, you might be affected by this issue. To resolve the issue, upgrade to SDK 2.9.0 or higher. In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.6.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on August 8, 2019. Known issues: Pipelines might become stuck due to an issue with the Conscrypt library. If you see errors in Stackdriver logging with stack traces that include Conscrypt related calls, you might be affected by this issue. To resolve the issue, upgrade to SDK 2.9.0 or higher. In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.5.0	Supported	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management org.apache.beam:beam-sdks-java-io-kafka	This version will be deprecated on June 6, 2019. Known issues: Pipelines might become stuck due to an issue with the Conscrypt library. If you see errors in Stackdriver logging with stack traces that include Conscrypt related calls, you might be affected by this issue. To resolve the issue, upgrade to SDK 2.9.0 or higher. In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.4.0	Deprecated	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management	Deprecated as of March 20, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.3.0	Deprecated	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management	Deprecated as of January 30, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.2.0	Deprecated	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management	Deprecated as of December 2, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.1.0	Deprecated	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management	Deprecated as of August 23, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.0.0	Deprecated	org.apache.beam:beam-sdks-java-core org.apache.beam:beam-sdks-java-io-google-cloud-platform org.apache.beam:beam-sdks-java-extensions-google-cloud-platform-core org.apache.beam:beam-sdks-java-extensions-protobuf org.apache.beam:beam-runners-direct-java org.apache.beam:beam-runners-google-cloud-dataflow-java org.apache.beam:beam-model-pipeline org.apache.beam:beam-runners-core-construction-java org.apache.beam:beam-model-job-management	Deprecated as of May 17, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Apache Beam Java SDKs 2.9.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.

Python

SDK version(s)	Status	Details
2.13.0	Supported	This version will be deprecated on June 6, 2020.
2.12.0	Supported	This version will be deprecated on April 25, 2020.
2.11.0	Supported	This version will be deprecated on March 1, 2020.
2.10.0	Supported	This version will be deprecated on February 11, 2020.
2.9.0	Supported	This version will be deprecated on December 13, 2019.
2.8.0	Supported	This version will be deprecated on October 25, 2019.
2.7.0 LTS	Supported	2.7.0 is a long term support (LTS) release and will receive patches until May 16, 2019. This version will be deprecated on October 3, 2019.
2.6.0	Supported	This version will be deprecated on August 8, 2019.
2.5.0	Supported	This version will be deprecated on June 6, 2019.
2.4.0	Deprecated	Deprecated as of March 20, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.3.0	Deprecated	Deprecated as of January 30, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.2.0	Deprecated	Deprecated as of December 2, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.1.1 2.1.0	Deprecated	Deprecated as of August 23, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.0.0	Deprecated	Deprecated as of May 17, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.

Cloud Dataflow 2.x SDKs

SDK Decommission Notice: The following SDK versions will be decommissioned in late 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.

• Apache Beam SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Apache Beam SDK for Python, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Java, versions 2.0.0 to 2.4.0 (inclusive)
• Cloud Dataflow SDK for Python, 2.0.0 to 2.4.0 (inclusive)

Previously, the date planned for this decommissioning was March 25, 2019, but in response to customer requests, we are extending this timeline. The new end date has yet to be finalized but is expected to happen in 2019. When decommissioning happens, you will no longer be able to submit new Cloud Dataflow jobs or update running Cloud Dataflow jobs that use the decommissioned SDKs. In addition, existing streaming jobs that use these SDK versions may fail.

Cloud Dataflow SDK Deprecation Notice: The Cloud Dataflow SDK 2.5.0 is the last Cloud Dataflow SDK release that is separate from the Apache Beam SDK releases. The Cloud Dataflow service supports official Apache Beam SDK releases as documented in the SDK version support status page.

Note: Development SDK versions (marked as -SNAPSHOT for Java and .dev for Python) are unsupported.

The following tables contains the support status for the Cloud Dataflow 2.x SDKs:

Java

See the Cloud Dataflow SDK 2.x for Java release notes for change information.

SDK version(s)	Status	Details
2.5.0	Supported	This version will be deprecated on June 6, 2019. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.4.0	Deprecated	Deprecated as of March 20, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.3.0	Deprecated	Deprecated as of January 30, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.2.0	Deprecated	Deprecated as of December 2, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.1.0	Deprecated	Deprecated as of August 23, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.0.0	Deprecated	Deprecated as of May 17, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.
2.0.0-beta3 2.0.0-beta2 2.0.0-beta1	Decommissioned	Decommissioned as of February 28, 2018. Known issue: In a specific case, users of Cloud Dataflow Java SDKs 2.5.0 and earlier might experience data duplication when reading files from Cloud Storage. Duplication might occur when all of the following conditions are true: You are reading files with the content-encoding set to gzip, and the files are dynamically decompressive transcoded by Cloud Storage. The file size (decompressed) is larger than 2.14 GB. The input stream runs into an error (and is recreated) after 2.14 GB is read. As a workaround, do not set the content-encoding header, and store compressed files in Cloud Storage with the proper extension (for example, gz for gzip). For existing files, you can update the content-encoding header and file name with the gsutil tool.

Python

See the Cloud Dataflow SDK 2.x for Python release notes for change information.

SDK version(s)	Status	Details
2.5.0	Supported	This version will be deprecated on June 6, 2019.
2.4.0	Deprecated	Deprecated as of March 20, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.3.0	Deprecated	Deprecated as of January 30, 2019. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.2.0	Deprecated	Deprecated as of December 2, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints.
2.1.1	Deprecated	Deprecated as of August 23, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. Fixes a compatibility issue with the Python six package. See the release notes for more information.
2.1.0	Deprecated	Deprecated as of August 23, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. This release has a compatibility issue with the Python six 1.11.0 package. See the Release Notes for more information.
2.0.0	Deprecated	Deprecated as of May 17, 2018. This version will be decommissioned later in 2019 due to the discontinuation of support for JSON-RPC and Global HTTP Batch Endpoints. This release has a compatibility issue with the Python six 1.11.0 package. See the Release Notes for more information.
0.6.0 0.5.5 0.5.1 0.4.4 0.4.3 0.4.2 0.4.1 0.4.0	Decommissioned	Decommissioned as of January 29, 2018.
0.2.7 and earlier versions	Decommissioned	Decommissioned as of March 23, 2017.

Cloud Dataflow 1.x SDKs

Warning: Cloud Dataflow SDK 1.x for Java is unsupported as of October 16, 2018. See Migrating from Cloud Dataflow SDK 1.x for Java for migration guidance.

The following table contains the support status for the Cloud Dataflow 1.x SDKs for Java. See the Cloud Dataflow SDK 1.x for Java release notes for change information.

SDK version(s)	Status	Details
1.9.1 1.9.0	Unsupported	Unsupported as of October 16, 2018.
1.8.1 1.8.0	Unsupported	Unsupported as of April 9, 2018.
1.7.0	Unsupported	Unsupported as of March 12, 2018.
1.6.1 1.6.0	Unsupported	Unsupported as of January 22, 2018.
1.5.1 1.5.0 1.4.0 1.3.0	Unsupported	Unsupported as of October 1, 2017.
1.2.1 1.2.0 1.1.0 1.0.0	Unsupported	Unsupported as of February 26, 2017.
Pre-1.0.0 (including 0.4.* and 0.3.*)	Unsupported