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* split hdfs into extra (#36773)
* split hdfs into extra
* CHANGES
* tox
* try/catch
* test fixes
* add to coverage tasks
* Update CHANGES to mention extras changes (#36875)
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@@ -81,7 +81,7 @@ Now Beam has full support for Milvus integration including Milvus enrichment and
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## Breaking Changes
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*X behavior was changed ([#X](https://github.com/apache/beam/issues/X)).
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*(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](https://github.com/apache/beam/issues/34554)).
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## Deprecations
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- This change only affects pipelines that explicitly use the `pickle_library=dill` pipeline option.
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- 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.
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- 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.
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- Submission environment: Install the dill extra in your local environment `pip install apache-beam[gcpdill]`.
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- Submission environment: Install the dill extra in your local environment `pip install apache-beam[gcp,dill]`.
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- Runtime (worker) environment: Your action depends on how you manage your worker's environment.
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- If using default containers or custom containers with the official Beam base image e.g. `FROM apache/beam_python3.10_sdk:2.69.0`
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- Add `dill==0.3.1.1` to your worker's requirements file (e.g., requirements.txt)
@@ -137,6 +137,9 @@ Now Beam has full support for Milvus integration including Milvus enrichment and
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* (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](https://github.com/apache/beam/pull/36345)).
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* (Python) Fixed transform naming conflict when executing DataTransform on a dictionary of PColls ([#30445](https://github.com/apache/beam/issues/30445)).
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This may break update compatibility if you don't provide a `--transform_name_mapping`.
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* (Python) Split some extras out from the core Beam package. ([#30445](https://github.com/apache/beam/issues/30445)).
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- If you use Enrichment with redis, Hadoop FileSystem, TFRecord, or some other packages, you may need to install some extras.
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- To retain identical behavior to before, instead of `pip install apache-beam`, use `pip install apache-beam[hadoop,gcp,interactive,redis,test,tfrecord]`.
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* Removed deprecated Hadoop versions (2.10.2 and 3.2.4) that are no longer supported for [Iceberg](https://github.com/apache/iceberg/issues/10940) from IcebergIO ([#36282](https://github.com/apache/beam/issues/36282)).
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* (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](https://github.com/apache/beam/issues/36387)).
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* Minimum Go version for Beam Go updated to 1.25.2 ([#36461](https://github.com/apache/beam/issues/36461)).
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