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https://issues.apache.org/jira/browse/FLINK-9061?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16530389#comment-16530389
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Jamie Grier commented on FLINK-9061:
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[~ind_rc] Initial changes look good. Are you going to try to get this into 1.6?
> add entropy to s3 path for better scalability
> ---------------------------------------------
>
> Key: FLINK-9061
> URL: https://issues.apache.org/jira/browse/FLINK-9061
> Project: Flink
> Issue Type: Bug
> Components: FileSystem, State Backends, Checkpointing
> Affects Versions: 1.5.0, 1.4.2
> Reporter: Jamie Grier
> Assignee: Indrajit Roychoudhury
> Priority: Critical
>
> I think we need to modify the way we write checkpoints to S3 for high-scale
> jobs (those with many total tasks). The issue is that we are writing all the
> checkpoint data under a common key prefix. This is the worst case scenario
> for S3 performance since the key is used as a partition key.
>
> In the worst case checkpoints fail with a 500 status code coming back from S3
> and an internal error type of TooBusyException.
>
> One possible solution would be to add a hook in the Flink filesystem code
> that allows me to "rewrite" paths. For example say I have the checkpoint
> directory set to:
>
> s3://bucket/flink/checkpoints
>
> I would hook that and rewrite that path to:
>
> s3://bucket/[HASH]/flink/checkpoints, where HASH is the hash of the original
> path
>
> This would distribute the checkpoint write load around the S3 cluster evenly.
>
> For reference:
> https://aws.amazon.com/premiumsupport/knowledge-center/s3-bucket-performance-improve/
>
> Any other people hit this issue? Any other ideas for solutions? This is a
> pretty serious problem for people trying to checkpoint to S3.
>
> -Jamie
>
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