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IcerbergIO Load test and benchmarking#39270

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Amar3tto wants to merge 6 commits into
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icerbergio-benchmark
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IcerbergIO Load test and benchmarking#39270
Amar3tto wants to merge 6 commits into
masterfrom
icerbergio-benchmark

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@Amar3tto

@Amar3tto Amar3tto commented Jul 9, 2026

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Successful run: https://github.com/apache/beam/actions/runs/29006124448/job/86078012033
Read Dataflow Job: 2026-07-09_02_11_56-9909184907203270916
Write Dataflow Job: 2026-07-09_02_00_15-6048170378328054140

Changes:

  • Moved the next classes from it.gcp to it.common:
    • DefaultPipelineLauncher and AbstractPipelineLauncher
    • LoadTestBase
    • Resource managers and Artifact utils
  • Implemented Load test for IcebergIO Batch Read/Write
  • Added IcebergIO Looker diagrams with metrics to the website

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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 introduces comprehensive load testing and benchmarking for IcebergIO. It includes a significant refactoring of existing integration test utilities to promote code reuse by moving common components into a shared module. Additionally, it adds support for IcebergIO performance tracking on the project's website, providing visibility into read and write performance metrics.

Highlights

  • Refactoring: Moved common integration test utilities from the gcp module to a shared common module to improve code reuse.
  • Load Testing: Implemented new load tests for IcebergIO Batch Read and Write operations.
  • Documentation and Metrics: Added IcebergIO performance metrics to the project website, including new Looker diagrams for visualization.
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Ignored Files
  • Ignored by pattern: .github/workflows/** (1)
    • .github/workflows/beam_PostCommit_Java_IO_Performance_Tests.yml
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Code Review

This pull request introduces integration and performance tests for IcebergIO (IcebergIOLT), along with its corresponding Gradle tasks, website documentation, and Looker metrics configurations. Additionally, it reorganizes the integration testing framework by moving common test utilities (such as load/stress test base classes, artifact clients, and resource managers) from the GCP-specific module to a shared common module under the org.apache.beam.it.common package, updating dependencies and imports across several modules. Regarding the feedback, a performance issue was identified in the new IcebergIOLT test where a Random object is instantiated for every processed element, which can cause significant CPU and garbage collection overhead; it is recommended to reuse a single transient Random instance and update its seed instead.

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Comment on lines +281 to +306
private static class MapToIcebergFormat extends DoFn<Long, Row> {

private final int valueSizeBytes;

private MapToIcebergFormat(int valueSizeBytes) {
if (valueSizeBytes <= 0) {
throw new IllegalArgumentException("valueSizeBytes must be positive.");
}

this.valueSizeBytes = valueSizeBytes;
}

@ProcessElement
public void processElement(@Element Long index, OutputReceiver<Row> output) {

byte[] value = new byte[valueSizeBytes];

/*
* Using the row index as the seed makes retries deterministic. Random data also prevents
* compression from making the generated payload significantly smaller than configured.
*/
new Random(index).nextBytes(value);

output.output(Row.withSchema(ROW_SCHEMA).addValues(index, value).build());
}
}

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high

Instantiating a new Random(index) object inside processElement for every single element processed by the pipeline introduces significant CPU overhead and garbage collection pressure. This is especially problematic in load and performance tests where millions or billions of elements are processed, as it can skew the benchmark results.

Instead, declare a single transient Random field in the DoFn class, lazily initialize it, and reuse it by calling setSeed(index) for each element to maintain determinism.

  private static class MapToIcebergFormat extends DoFn<Long, Row> {

    private final int valueSizeBytes;
    private transient Random random;

    private MapToIcebergFormat(int valueSizeBytes) {
      if (valueSizeBytes <= 0) {
        throw new IllegalArgumentException("valueSizeBytes must be positive.");
      }

      this.valueSizeBytes = valueSizeBytes;
    }

    @ProcessElement
    public void processElement(@Element Long index, OutputReceiver<Row> output) {
      if (random == null) {
        random = new Random();
      }
      byte[] value = new byte[valueSizeBytes];

      /*
       * Using the row index as the seed makes retries deterministic. Random data also prevents
       * compression from making the generated payload significantly smaller than configured.
       */
      random.setSeed(index);
      random.nextBytes(value);

      output.output(Row.withSchema(ROW_SCHEMA).addValues(index, value).build());
    }
  }

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I think this is true - would you mind addressing this?

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Fixed

@damccorm damccorm left a comment

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Thanks - just had a couple of questions

* limitations under the License.
*/
package org.apache.beam.it.gcp.bigquery;
package org.apache.beam.it.common.bigquery;

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Why did we need to move all of these to common? Some of these do seem GCP specific

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I moved them so Kafka, Iceberg, and other non-GCP IO tests could reuse the load-test infrastructure without depending on the whole GCP test module. I agree some utilities are still GCP-specific, so keeping them in clearly named gcp or dataflow packages within common may be a better separation.

@@ -0,0 +1 @@
["This is a test artifact."] No newline at end of file

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How is this (and the similar file below) used?

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It is used in GcsResourceManagerTest. I removed the other two that were not used. Thanks!

Comment on lines +281 to +306
private static class MapToIcebergFormat extends DoFn<Long, Row> {

private final int valueSizeBytes;

private MapToIcebergFormat(int valueSizeBytes) {
if (valueSizeBytes <= 0) {
throw new IllegalArgumentException("valueSizeBytes must be positive.");
}

this.valueSizeBytes = valueSizeBytes;
}

@ProcessElement
public void processElement(@Element Long index, OutputReceiver<Row> output) {

byte[] value = new byte[valueSizeBytes];

/*
* Using the row index as the seed makes retries deterministic. Random data also prevents
* compression from making the generated payload significantly smaller than configured.
*/
new Random(index).nextBytes(value);

output.output(Row.withSchema(ROW_SCHEMA).addValues(index, value).build());
}
}

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I think this is true - would you mind addressing this?

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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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2 participants