[jira] [Updated] (FLINK-8801) S3's eventual consistent read-after-write may fail yarn deployment of resources to S3

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-8801?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

ASF GitHub Bot updated FLINK-8801:
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    Labels: pull-request-available  (was: )

> S3's eventual consistent read-after-write may fail yarn deployment of resources to S3
> -------------------------------------------------------------------------------------
>
>                 Key: FLINK-8801
>                 URL: https://issues.apache.org/jira/browse/FLINK-8801
>             Project: Flink
>          Issue Type: Bug
>          Components: Deployment / YARN, FileSystems, Runtime / Coordination
>    Affects Versions: 1.4.0, 1.5.0
>            Reporter: Nico Kruber
>            Assignee: Nico Kruber
>            Priority: Blocker
>              Labels: pull-request-available
>             Fix For: 1.4.3, 1.5.0
>
>
> According to https://docs.aws.amazon.com/AmazonS3/latest/dev/Introduction.html#ConsistencyModel:
> {quote}
> Amazon S3 provides read-after-write consistency for PUTS of new objects in your S3 bucket in all regions with one caveat. The caveat is that if you make a HEAD or GET request to the key name (to find if the object exists) before creating the object, Amazon S3 provides eventual consistency for read-after-write.
> {quote}
> Some S3 file system implementations may actually execute such a request for the about-to-write object and thus the read-after-write is only eventually consistent. {{org.apache.flink.yarn.Utils#setupLocalResource()}} currently relies on a consistent read-after-write since it accesses the remote resource to get file size and modification timestamp. Since there we have access to the local resource, we can use the data from there instead and circumvent the problem.



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