What this PR does / why we need it

• Adds an initial Apache Flink compute engine backed by PyFlink Table API.
• Implements Feast compute DAG nodes for source reads, joins, filters, aggregations, dedupe, transformations, validation, and output writes.
• Registers the flink.engine batch engine and mode="flink" transformation mode.
• Adds docs/navigation for configuring the Flink engine and documents the current PyFlink/PyArrow install constraint.
• Adds focused unit coverage for Flink DAG behavior, SQL-string entity_df, pandas entity_df, strict native source retrieval, TTL interval rendering, and Flink-specific PyArrow dependency metadata.

Feast has a pluggable compute engine abstraction, but does not currently include a Flink implementation. This PR adds a Flink/PyFlink backend so users can run Feast batch materialization and historical retrieval through Flink's Table API while preserving Feast's existing DAG execution model.

Which issue(s) this PR fixes

None filed.

Does this PR introduce a user-facing change

Yes.

Users can configure batch_engine.type: flink.engine and use mode="flink" transformations on BatchFeatureView. Flink transformations receive and return PyFlink table objects. Source reads require offline-store retrieval jobs that expose to_flink_table(table_env); Arrow/pandas-only retrieval jobs are rejected instead of silently falling back.

The Flink extra must currently be installed with uv sync --extra flink --no-dev from a source checkout because PyFlink requires pyarrow<21, while default Feast installs keep pyarrow>=21.

Release note

Add an Apache Flink compute engine backed by PyFlink Table API for batch materialization and historical retrieval.

Testing

• uv lock
• uv run ruff check sdk/python/feast/batch_feature_view.py sdk/python/feast/infra/compute_engines/flink sdk/python/feast/transformation/flink_transformation.py sdk/python/tests/unit/infra/compute_engines/flink/test_flink_compute_engine.py
• uv run bash -c "cd sdk/python && mypy feast/batch_feature_view.py feast/infra/compute_engines/flink/compute.py feast/infra/compute_engines/flink/feature_builder.py feast/infra/compute_engines/flink/job.py feast/infra/compute_engines/flink/nodes.py feast/infra/compute_engines/flink/utils.py feast/transformation/flink_transformation.py tests/unit/infra/compute_engines/flink/test_flink_compute_engine.py --follow-imports=skip --check-untyped-defs"
• uv run python -m pytest sdk/python/tests/unit/infra/compute_engines/flink/test_flink_compute_engine.py -v
• Temp source checkout: uv sync --extra flink --no-dev
• Real PyFlink smoke: PYFLINK_NATIVE_SOURCE_SMOKE_OK pyarrow=16.1.0 pyflink=2.2.1

Note: pip install -e '.[flink]' cannot currently resolve the Flink extra because pip evaluates Feast's default pyarrow>=21 requirement together with PyFlink's pyarrow<21 requirement. The docs now point to the uv source-checkout install path that was verified above.