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https://issues.apache.org/jira/browse/FLINK-31089?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17693022#comment-17693022
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Yanfei Lei commented on FLINK-31089:
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Let me try to summarize this issue:
# Enable PinL0FilterAndIndexBlocksInCache or PinTopLevelIndexAndFilter,
disable TTL, will result in OOM
## PinTopLevelIndexAndFilter can significantly affect the performance.
## PinL0FilterAndIndexBlocksInCache will NOT affect the performance.
# Enable PinL0FilterAndIndexBlocksInCache or PinTopLevelIndexAndFilter, enable
TTL, the memory wouldn't keep growing.
## Due to https://issues.apache.org/jira/browse/FLINK-22957 , the TTL can't
take effect for the Rank operator in Flink 1.13.
Is the TTL set by "table.exec.state.ttl"? If the job is a DataStream job, maybe
you can set TTL for the rank operator via StateTtlConfig.
> pin L0 index in memory can lead to slow memory grow finally lead to memory
> beyond limit
> ---------------------------------------------------------------------------------------
>
> Key: FLINK-31089
> URL: https://issues.apache.org/jira/browse/FLINK-31089
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / State Backends
> Affects Versions: 1.16.1
> Reporter: xiaogang zhou
> Priority: Major
> Attachments: image-2023-02-15-20-26-58-604.png,
> image-2023-02-15-20-32-17-993.png, image-2023-02-17-16-48-59-535.png,
> l0pin_open.png
>
>
> with the setPinL0FilterAndIndexBlocksInCache true, we can see the pinned
> memory kept growing(in the pc blow from 48G-> 50G in about 5 hours). But if
> we switch it to false, we can see the pinned memory stay realtive static. In
> our environment, a lot of tasks restart due to memory over limit killed by k8s
> !image-2023-02-15-20-26-58-604.png|width=899,height=447!
>
> !image-2023-02-15-20-32-17-993.png|width=853,height=464!
> the two graphs are recorded in yesterday and today, which means the data
> stream number per second will not differ alot.
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