nzw921rx opened a new issue, #12059:
URL: https://github.com/apache/seatunnel/issues/12059

   ## Description
   
   This is a focused investigation and improvement task for the throughput 
variance observed in the intermediate queue benchmarks.
   
   It is not a performance regression report and does not attempt to compare 
the performance of Java 8 with Java 11.
   
   The benchmark results show noticeable sample-to-sample variance within 
individual runs:
   
   | Benchmark | Java 8 Error / CV | Java 11 Error / CV |
   | --- | ---: | ---: |
   | `blockingQueueRecordHandoff` | 10.76% / 10.06% | 9.95% / 9.31% |
   | `disruptorRecordHandoff` | 22.46% / 21.01% | 18.35% / 17.16% |
   
   Benchmark run:
   
   https://github.com/apache/seatunnel/actions/runs/33723940255
   
   Other benchmarks executed by the same workflow were substantially more 
stable. The intermediate queue results are therefore worth investigating to 
determine whether the variance comes from the benchmark fixture, queue 
implementation, thread scheduling, or execution environment.
   
   The goals of this issue are to:
   
   1. Identify and explain the source of the throughput variance.
   2. Improve the benchmark fixture or methodology if it causes the instability.
   3. Optimize the production queue path if profiling confirms an 
implementation bottleneck.
   4. Preserve the correctness and lifecycle behavior of both queue 
implementations.
   
   ## Relevant benchmarks
   
   ```text
   IntermediateQueueBenchmark.blockingQueueRecordHandoff
   IntermediateQueueBenchmark.disruptorRecordHandoff
   ```
   
   ## Profiling tools
   
   For an overview of the Zeta benchmark suite and usage, see the [SeaTunnel 
Zeta Benchmark Guide](https://seatunnel.apache.org/docs/engines/zeta/benchmark).
   
   SeaTunnel provides the `Benchmarks Diagnostics` workflow for running one 
exact benchmark method with CPU, wall-clock, lock, GC, or JFR profiling:
   
   
https://github.com/apache/seatunnel/actions/workflows/benchmarks_diagnostics.yml
   
   The benchmark can also be run directly from the GitHub Actions page by 
selecting **Benchmarks Diagnostics**, clicking **Run workflow**, and providing 
the target branch, tag, commit SHA, or trusted PR number together with the 
exact benchmark method.
   
   ## Local profiling
   
   Build the benchmark module:
   
   ```bash
   ./mvnw -Pbenchmark -pl seatunnel-benchmarks -am -DskipTests package
   ```
   
   Run a profiler locally:
   
   ```bash
   bash tools/benchmarks/profile_benchmarks.sh profile cpu \
     --repository . \
     --benchmark 'IntermediateQueueBenchmark.disruptorRecordHandoff$'
   ```
   
   Replace `cpu` with `wall`, `lock`, or `gc` as needed. The same command can 
be used for:
   
   ```text
   IntermediateQueueBenchmark.blockingQueueRecordHandoff$
   ```
   
   Capture a JFR recording:
   
   ```bash
   bash tools/benchmarks/profile_benchmarks.sh capture jfr \
     --repository . \
     --benchmark 'IntermediateQueueBenchmark.disruptorRecordHandoff$'
   ```
   
   CPU, wall-clock, and lock profiling require `ASYNC_PROFILER_HOME`. The 
GitHub Actions workflow installs the required profiler automatically.
   
   ## Expected outcome
   
   This issue should result in both root-cause analysis and a focused 
improvement:
   
   - Identify and explain the primary source of the benchmark variance.
   - Improve the benchmark when the fixture or methodology is responsible.
   - Optimize the production queue path when an implementation problem is 
confirmed.
   - Provide before-and-after results collected with the same JDK, runner, 
benchmark arguments, and queue parameters.
   - Compare both throughput and variance before and after the change.
   - Add appropriate tests and confirm that queue correctness remains unchanged.
   
   The implementation should focus on the confirmed source and avoid unrelated 
queue refactoring.
   


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