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From "Till Rohrmann (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (FLINK-9061) add entropy to s3 path for better scalability
Date Tue, 29 May 2018 10:48:00 GMT

     [ https://issues.apache.org/jira/browse/FLINK-9061?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Till Rohrmann updated FLINK-9061:
---------------------------------
    Affects Version/s: 1.5.0

> 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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