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https://issues.apache.org/jira/browse/FLINK-23905?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17402729#comment-17402729
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huntercc edited comment on FLINK-23905 at 8/23/21, 9:53 AM:
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Thanks for your reply and practical advice, [~trohrmann]. In fact, we have 
adopted a similar method by configuring the yarn.ship-files parameter, which 
greatly shortens the time spent in this step. I'm worried that there will be 
dependency conflicts in this way, especially when we use the yarn session mode. 
I venture to suppose that it would be better if this part of the work could be 
transparent to users.


was (Author: huntercc):
Thanks your reply and practical advice, [~trohrmann]. In fact, we have adopted 
a similar method by configuring the yarn.ship-files parameter, which greatly 
shortens the time spent in this step. I'm worried that there will be dependency 
conflicts in this way, especially when we use the yarn session mode. I venture 
to suppose that it would be better if this part of the work could be 
transparent to users.

> Reduce the load on JobManager when submitting large-scale job with a big user 
> jar
> ---------------------------------------------------------------------------------
>
>                 Key: FLINK-23905
>                 URL: https://issues.apache.org/jira/browse/FLINK-23905
>             Project: Flink
>          Issue Type: Improvement
>          Components: Runtime / Coordination
>            Reporter: huntercc
>            Priority: Major
>
> As described in FLINK-20612 and FLINK-21731, there are some time-consuming 
> steps in the job startup phase. Recently, we found that when submitting a 
> large-scale job with a large user jar, the time spent on changing the status 
> of a task from deploying to running accounts for a high proportion of the 
> total time-consuming.
> In the task initialization stage, the user jar needs to be pulled from the 
> JobManager through BlobService. JobManager has to allocate a lot of computing 
> power to distribute the files, which leads to a heavy load in the start-up 
> stage. More generally, JobManager fails to respond to the RPC request sent by 
> the TaskManager side in time due to high load, causing some timeout 
> exceptions, such as akka timeout exception, which leads to job restart and 
> further prolongs the start-up time of the job.



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