[2/3] sdks/python: sink data with Milvus Search I/O connector

[mohamedawnallah]

Description

• Add Milvus Search Sink I/O Connector
• Unit Test Milvus Search Sink I/O Connector
• Integrate Test Milvus Search Sink I/O Connector
• Review & Address (can be) Flaky Test Cases
• Add Release Note for the new Milvus Search Sink I/O Connector Integration

Motivation and Context

Motivated by this comment #35708 (comment) for splitting the original PR into two one for refactoring and one for core integration. That way it would be relatively easier to review

Towards #35046.
Depends on #35708.
Next #35944.
Closes #36702.

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[gemini-code-assist]

Summary of Changes

Hello @mohamedawnallah, 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 Milvus Search Sink I/O connector for the Apache Beam Python SDK. This connector enables users to efficiently write data, including vector embeddings and associated metadata, to Milvus collections. The changes also involve significant refactoring of existing Milvus-related code, centralizing common utilities and test helpers to improve maintainability and support future Milvus integrations. This enhancement completes Beam's support for Milvus, providing a robust solution for both reading from and writing to Milvus vector databases.

Highlights

• Milvus Sink Connector: A new I/O connector for sinking data to Milvus vector databases has been added to the Python SDK.
• Comprehensive Testing: The new connector includes dedicated unit and integration tests to ensure its functionality and reliability.
• Refactored Milvus Utilities: Common Milvus-related helper functions, connection parameters, and test utilities have been centralized into new utils.py and test_utils.py modules for better organization and reusability.
• Enhanced Milvus Integration: With the addition of the sink connector, Apache Beam now offers full support for Milvus, covering both enrichment and data ingestion operations.

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[mohamedawnallah]

@damccorm – This PR is now ready for review after that PR merged #35708. All relevant tests are passing now in the CI

[damccorm]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces a Milvus sink I/O connector for the Python SDK, which is a great addition for users looking to integrate Apache Beam with Milvus for RAG pipelines. The implementation is well-structured, leveraging DoFn for batching and a context manager for resource management, which are good practices. The integration tests are comprehensive, covering various scenarios including error cases and idempotency, which ensures the connector's reliability.

I've provided a few suggestions to improve the code. One key point is to remove redundant client initialization logic that bypasses the retry mechanism. I've also pointed out a documentation mismatch and suggested simplifications in the test code for better clarity.

Overall, this is a solid contribution that significantly enhances Beam's capabilities for building RAG applications.

[mohamedawnallah]

All relevant CI tests are passing now

[damccorm]

Thanks!