[Java IO] Add ArrowFlight IO connector

[bvolpato]

Summary

Add a new I/O connector for Apache Arrow Flight, enabling high-performance data transfer over gRPC using the Arrow columnar format. Arrow Flight avoids serialization/deserialization overhead and can achieve 10-50x faster data transfer compared to JDBC/ODBC.

Fixes #20116

Changes

• ArrowFlightIO.Read — BoundedSource-based read transform that fetches Arrow Flight schemas via getInfo, splits work by FlightEndpoint, and converts record batches to Beam Row using the existing ArrowConversion extension.
• ArrowFlightIO.Write — DoFn-based write transform that buffers Beam Rows into configurable batches, converts them to Arrow vectors, and streams them to a Flight server via doPut.
• Endpoint-level split parallelism — each FlightEndpoint returned by the server becomes a separate sub-source for parallel reads.
• Bearer token authentication — optional token support via withToken().
• Build integration — registered flight-core and flight-sql artifacts in BeamModulePlugin.groovy; added the :sdks:java:io:arrow-flight module to settings.gradle.kts.
• Documentation — added ArrowFlightIO to CHANGES.md (2.73.0) and the built-in connectors table in connectors.md.

Testing

Tests use a real in-process FlightServer with a TestFlightProducer:

• testRead() — starts a Flight server serving two rows, reads them with ArrowFlightIO.read(), and asserts the output via PAssert.
• testWrite() — writes two rows with ArrowFlightIO.write() and verifies the producer received exactly 2 records.

Both tests run the full pipeline end-to-end using TestPipeline and the DirectRunner.

Did this cause any problems?

Rollback/revert this commit and redeploy the service.

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[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request introduces a new Java I/O connector for Apache Arrow Flight, significantly enhancing data transfer capabilities within Beam pipelines. The connector leverages Arrow Flight's high-performance RPC framework to facilitate efficient reading from and writing to Arrow Flight servers, minimizing serialization overhead and enabling faster data movement. This integration expands Beam's ecosystem by providing a robust solution for interacting with various Arrow Flight-compatible data systems.

Highlights

• ArrowFlightIO.Read: Implemented a BoundedSource-based read transform that fetches Arrow Flight schemas, splits work by FlightEndpoint, and converts record batches to Beam Rows using the existing ArrowConversion extension.
• ArrowFlightIO.Write: Developed a DoFn-based write transform that buffers Beam Rows into configurable batches, converts them to Arrow vectors, and streams them to a Flight server via doPut.
• Endpoint-level Split Parallelism: Enabled each FlightEndpoint returned by the server to become a separate sub-source for parallel reads, enhancing data ingestion efficiency.
• Bearer Token Authentication: Added optional support for bearer token authentication via withToken() for secure connections.
• Build Integration: Registered flight-core and flight-sql artifacts in BeamModulePlugin.groovy and added the new :sdks:java:io:arrow-flight module to settings.gradle.kts.
• Documentation: Updated CHANGES.md and the built-in connectors table in connectors.md to reflect the addition of the ArrowFlightIO connector.

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