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[hotfix][docs] Fix incorrect HashMapStateBackend recommendations #28094

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[hotfix][docs] Fix incorrect HashMapStateBackend recommendations #28094

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[hotfix][docs] Fix incorrect HashMapStateBackend recommendations
Dennis-Mircea May 3, 2026
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[hotfix][docs] Address PR comment
Dennis-Mircea May 4, 2026
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[hotfix][docs] Address review comments
Dennis-Mircea May 9, 2026
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4 changes: 2 additions & 2 deletions docs/content.zh/docs/ops/state/state_backends.md
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Expand Up @@ -58,8 +58,8 @@ Flink 内置了以下这些开箱即用的 state backends ：

HashMapStateBackend 的适用场景：

- 有较大 state，较长 window 和较大 key/value 状态的 Job。
- 所有的高可用场景。
- 状态可以完全放入 TaskManager JVM 堆内存的 Job，需要快速的、基于内存的状态访问。
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- 对延迟敏感、希望避免每次状态访问都进行序列化/反序列化开销的 Job。

建议同时将 [managed memory]({{< ref "docs/deployment/memory/mem_setup_tm" >}}#managed-memory) 设为0，以保证将最大限度的内存分配给 JVM 上的用户代码。

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4 changes: 2 additions & 2 deletions docs/content/docs/ops/state/state_backends.md
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Expand Up @@ -55,8 +55,8 @@ that store the values, triggers, etc.

The HashMapStateBackend is encouraged for:

- Jobs with large state, long windows, large key/value states.
- All high-availability setups.
- Jobs whose state fits comfortably in the JVM heap of the TaskManagers, where fast, in-memory state access is the priority.
- Jobs with low-latency requirements that benefit from avoiding de-/serialization on every state access.
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It is also recommended to set [managed memory]({{< ref "docs/deployment/memory/mem_setup_tm" >}}#managed-memory) to zero.
This will ensure that the maximum amount of memory is allocated for user code on the JVM.
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