[jira] [Resolved] (SPARK-38329) High I/O wait when Spark Structured Streaming checkpoint changed to EFS

["Sean R. Owen (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-38329?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean R. Owen resolved SPARK-38329.
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    Resolution: Not A Problem

> High I/O wait when Spark Structured Streaming checkpoint changed to EFS
> -----------------------------------------------------------------------
>
>                 Key: SPARK-38329
>                 URL: https://issues.apache.org/jira/browse/SPARK-38329
>             Project: Spark
>          Issue Type: Question
>          Components: EC2, Input/Output, PySpark, Structured Streaming
>    Affects Versions: 3.2.1
>            Reporter: Neven Jovic
>            Priority: Major
>         Attachments: Screenshot from 2022-02-25 14-16-11.png, q.png
>
>
> I'm currently running spark structured streaming application written in python(pyspark) where my source is kafka topic and sink i mongodb. I changed my checkpoint to Amazon EFS, which is distributed on all spark workers and after that I got increased I/o wait, averaging 8%
>  
> !Screenshot from 2022-02-25 14-16-11.png!
> Currently I have 6000 messages coming to kafka every second, and I get every once in a while a WARN message:
> {quote}22/02/25 13:12:31 WARN HDFSBackedStateStoreProvider: Error cleaning up files for HDFSStateStoreProvider[id = (op=0,part=90),dir = file:/mnt/efs_max_io/spark/state/0/90] java.lang.NumberFormatException: For input string: ""
> {quote}
> I'm not quite sure if that message has anything to do with high I/O wait and is this behavior expected, or something to be concerned about?
>  



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