Add nanosecond timestamp support for Storage write when writing GenericRecords and Beam Rows

[claudevdm]

This PR adds support for writing nanosecond-precision timestamps to BigQuery via the Storage Write API. BigQuery's TIMESTAMP type with precision 12 (picoseconds) can store timestamps with sub-microsecond precision.

Changes

1. Avro GenericRecord Support (AvroGenericRecordToStorageApiProto.java)

• Detects timestamp-nanos logical type
• Maps to BigQuery TIMESTAMP with timestampPrecision = 12
• Converts Long (nanoseconds since epoch) → TimestampPicos proto message {seconds, picoseconds}
• Properly handles nullable fields via UNION type propagation

2. Beam Row Support (BeamRowToStorageApiProto.java)

• Detects Timestamp.NANOS logical type (precision = 9)
• Maps to BigQuery TIMESTAMP with timestampPrecision = 12
• Converts java.time.Instant → TimestampPicos proto message {seconds, picoseconds}

3. BigQuery Avro Utils (BigQueryAvroUtils.java)

• Sets timestampPrecision = 12 when reading timestamp-nanos fields

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[gemini-code-assist]

Summary of Changes

Hello @claudevdm, 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 significantly enhances the BigQuery Storage Write API integration by introducing comprehensive support for nanosecond-precision timestamps. It enables users to accurately store and retrieve time-series data with sub-microsecond granularity when using both Avro GenericRecords and Beam Rows, aligning with BigQuery's TIMESTAMP type capabilities. The changes involve updating schema mapping logic and data conversion mechanisms to correctly handle nanosecond values, ensuring data integrity and precision.

Highlights

• Nanosecond Timestamp Support: Enabled writing nanosecond-precision timestamps to BigQuery via the Storage Write API.
• Avro GenericRecord Handling: Implemented detection of timestamp-nanos logical type, mapping it to BigQuery TIMESTAMP with precision 12, and converting Long (nanoseconds since epoch) to TimestampPicos proto messages.
• Beam Row Handling: Added support for Timestamp.NANOS logical type, mapping it to BigQuery TIMESTAMP with precision 12, and converting java.time.Instant to TimestampPicos proto messages.
• Schema Definition Updates: Ensured that BigQuery schema generation correctly sets timestampPrecision = 12 for nanosecond timestamp fields in both Avro and Beam schemas.
• Comprehensive Testing: Introduced new unit and integration tests to validate the correct serialization, deserialization, and end-to-end writing/reading of nanosecond timestamps for both Avro GenericRecords and Beam Rows.

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[claudevdm]

/gemini review

[gemini-code-assist]

Code Review

This pull request adds support for nanosecond-precision timestamps when writing to BigQuery using the Storage Write API, for both Avro GenericRecords and Beam Rows. The changes are well-implemented and include corresponding tests. I've provided a few suggestions to improve code clarity, reduce duplication, and enhance maintainability by using constants for magic numbers and refactoring some logic.

[claudevdm]

R: @Abacn

[claudevdm]

R: @damccorm

[claudevdm]

R: @ahmedabu98

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control. If you'd like to restart, comment assign set of reviewers

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control. If you'd like to restart, comment assign set of reviewers

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control. If you'd like to restart, comment assign set of reviewers

[damccorm]

/gemini review

[damccorm]

Thanks, this LGTM

[gemini-code-assist]

Code Review

This pull request adds support for nanosecond-precision timestamps for the BigQuery Storage Write API, for both Avro GenericRecords and Beam Rows. The changes are well-structured, covering schema conversion, data conversion, and comprehensive new tests. The logic for handling nanosecond timestamps, including negative timestamps, appears correct. I've made a few suggestions to improve code clarity and maintainability, mainly by replacing magic numbers with named constants and simplifying some arithmetic logic. Overall, this is a solid contribution.