[Bug]: Dataflow streaming on SDK 2.74+ (Windmill DirectPath on by default) causes frequent UnboundedSource reader invalidations, re-processing and CPU saturation
维护者通常 1 天内回复
评估
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 新手友好度
- 15/100
- Issue 类型
- 缺陷
- 描述清晰度
- 基本清楚
- 活跃度
- 活跃
- 技术栈
- google-cloud, java, kafka
调研方向
Start in StreamingDataflowWorker.onCompleteCommit, where a non-OK CommitStatus invalidates the reader and state cache without logging, and follow the cache-token check in acquireReader plus the FanOutStreamingEngineWorkerHarness DirectPath path. A first step is logging or counting the commit status, which the issue asks for. Done means that change is in place and the root cause of the cache-token mismatch or commit rejection is identified, which the issue leaves open.
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描述
What happened?
What happened?
Since Dataflow turns on Windmill DirectPath by default for Java SDK 2.74.0 and later, our streaming pipelines show frequent storms of reader invalidations. During these storms work is processed again and again without making progress. The same pipeline without DirectPath runs normally.
Setup
• Beam Java 2.77.0, Dataflow Runner, Streaming Engine, Runner v1 (not Runner v2).
• KafkaIO.read() using the legacy UnboundedSource path, so readers are cached in ReaderCache .
• 1 worker, stateful processing (keyed state).
• enable_windmill_service_direct_path is added automatically by the service; we didn't set it.
Symptoms (DirectPath on)
• Bursts in which every cached reader is closed with Asynchronously closing reader for … as it is no longer valid , several times within minutes.
• The same key is often invalidated twice about 2s apart. First acquireReader finds a cache-token mismatch, then onCompleteCommit sees a non-OK commit status and calls invalidateReader .
• Readers restart from the same source position repeatedly. In one 2-hour window, 492 of 1,118 reader starts resumed at an offset that had already been used, so progress was being discarded.
• During storms CPU sits at 97–100% and system lag grows from a few seconds to about 8 minutes. Input rate is normal, and committed state writes fall to about 40–60% of normal.
• No client-side commit errors or aborts are logged: no Aborting … commits , no Error occurred sending commits .
• Each invalidation closes and recreates the Kafka consumers, which led to a large spike in new broker connections.
Comparison ("no longer valid" reader closes)
- Same code, SDK 2.77.0, DirectPath on: 400 over ~2 days
- Same code, SDK 2.77.0, run side by side with
--experiments=disable_windmill_service_direct_path: 16 (startup plus one isolated event) - Earlier pipeline version on SDK 2.73.0 (no DirectPath): 11 over ~28h
- Same pipeline on SDK 2.77.0 with DirectPath, same 28h: 583
With DirectPath disabled there are no storms, no CPU saturation and no lag spikes.
With DirectPath disabled there are no storms, no CPU saturation and no lag spikes.
Observations and questions
- StreamingDataflowWorker.onCompleteCommit invalidates the reader and state cache on any non-OK CommitStatus without logging the status. This makes it very hard to diagnose. Could the status be logged, or counted in a metric?
- Is there a known issue with cache-token stability or commit rejections on the DirectPath / FanOutStreamingEngineWorkerHarness path in 2.74–2.77?
- Should DirectPath stay on by default while this is investigated?
Issue Priority
Priority: 2 (default / most bugs should be filed as P2)
Issue Components
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- Component: Hazelcast Jet Runner
- Component: Google Cloud Dataflow Runner
- 主要语言
- Java
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- 平均合并
- 2 天 12 小时
- 30 天内合并 PR
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环境准备
- 没有 Dockerfile 或 Docker Compose 文件
- 有 Pull Request 模板
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