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Fix BigQuery Storage Write API stream count for bounded writes#38776

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Akshatsharma2205:fix-bigquery-num-storage-api-streams-bounded
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Fix BigQuery Storage Write API stream count for bounded writes#38776
Akshatsharma2205 wants to merge 2 commits into
apache:masterfrom
Akshatsharma2205:fix-bigquery-num-storage-api-streams-bounded

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Summary

  • Apply configured Storage Write API stream counts to both bounded and unbounded BigQuery writes.
  • Keep triggering frequency and auto-sharding configuration limited to unbounded writes.
  • Update Java, Python, and website documentation to remove the streaming-only limitation for fixed stream counts.

Fixes #38770

Validation

  • Ran git diff --check successfully.
  • Attempted ./gradlew :sdks:java:io:google-cloud-platform:compileJava locally, but the build did not reach Java compilation because this was prepared from a sparse checkout missing Beam build plugin infrastructure.

Key Gradle error:

Plugin [id: 'org.apache.beam.module'] was not found

Java compilation did not start.


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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 expands the functionality of the BigQuery Storage Write API by allowing the number of write streams to be configured for bounded (batch) writes, in addition to the existing support for unbounded (streaming) writes. The changes ensure that stream count configurations are applied consistently across different pipeline types while maintaining existing constraints on triggering frequency and auto-sharding for streaming data.

Highlights

  • Storage Write API Stream Configuration: Enabled the use of configured Storage Write API stream counts for both bounded and unbounded BigQuery writes.
  • Documentation Updates: Updated Java, Python, and website documentation to clarify that fixed stream counts are now supported for both batch and streaming pipelines.
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Code Review

This pull request enables the use of fixed stream counts (numStreams) for both batch (bounded) and streaming (unbounded) pipelines in the BigQuery Storage Write API, updating the Java and Python SDKs as well as the documentation. The review feedback suggests validating that numStreams is non-negative to prevent silent configuration errors, and simplifying the conditional check once validation is in place.

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PCollection<Row> inputRows = input.getSinglePCollection();

BigQueryIO.Write<Row> write = createStorageWriteApiTransform(inputRows.getSchema());
int numStreams = configuration.getNumStreams() == null ? 0 : configuration.getNumStreams();
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medium

If configuration.getNumStreams() is configured with a negative value, it will be silently ignored and treated as 0 (which enables auto-sharding if unbounded, or default behavior if bounded). We should validate that numStreams is non-negative and throw an IllegalArgumentException if it is negative to prevent silent configuration errors.

      int numStreams = configuration.getNumStreams() == null ? 0 : configuration.getNumStreams();
      if (numStreams < 0) {
        throw new IllegalArgumentException("numStreams must be non-negative, but was: " + numStreams);
      }

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Thanks for the suggestion. I added validation for negative numStreams in BigQueryWriteConfiguration.validate() using the existing checkArgument style.

if (numStreams > 0) {
write = write.withNumStorageWriteApiStreams(numStreams);
} else if (autoSharding == null || autoSharding) {
if (numStreams <= 0 && (autoSharding == null || autoSharding)) {
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medium

Since numStreams is validated to be non-negative, we can simplify numStreams <= 0 to numStreams == 0 for better clarity.

Suggested change
if (numStreams <= 0 && (autoSharding == null || autoSharding)) {
if (numStreams == 0 && (autoSharding == null || autoSharding)) {

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Updated in the latest commit. Since numStreams is now validated to be non-negative, the auto-sharding condition uses numStreams == 0.

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github-actions Bot commented Jun 2, 2026

Checks are failing. Will not request review until checks are succeeding. If you'd like to override that behavior, comment assign set of reviewers

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The failing/cancelled checks appear unrelated to this PR. I checked the visible annotations and did not see failures mentioning the changed BigQuery files or docs. Several failures are in Python ML/anomaly/RAG tests or CI timeouts.

Could the failed/cancelled checks be rerun when convenient?

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[Bug]: Fix num_storage_api_streams for batch

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