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https://issues.apache.org/jira/browse/YARN-10324?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17349124#comment-17349124
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Qi Zhu commented on YARN-10324:
-------------------------------

[~yaoguangdong] I'm not sure if you removed the original 003, and resubmitted 
it ?

Waiting for the jenkins now, if it not triggered some hours later, you should 
attached it again to trigger.

> Fetch data from NodeManager may case read timeout when disk is busy
> -------------------------------------------------------------------
>
>                 Key: YARN-10324
>                 URL: https://issues.apache.org/jira/browse/YARN-10324
>             Project: Hadoop YARN
>          Issue Type: Improvement
>          Components: auxservices
>    Affects Versions: 2.7.0, 3.2.1
>            Reporter: Yao Guangdong
>            Assignee: Yao Guangdong
>            Priority: Minor
>              Labels: patch
>         Attachments: YARN-10324.001.patch, YARN-10324.002.patch, 
> YARN-10324.003.patch, image-2021-05-21-17-48-03-476.png
>
>
>  With the cluster size become more and more big.The cost  time on Reduce 
> fetch Map's result from NodeManager become more and more long.We often see 
> the WARN logs in the reduce's logs as follow.
> {quote}2020-06-19 15:43:15,522 WARN [fetcher#8] 
> org.apache.hadoop.mapreduce.task.reduce.Fetcher: Failed to connect to 
> TX-196-168-211.com:13562 with 5 map outputs
> java.net.SocketTimeoutException: Read timed out
> at java.net.SocketInputStream.socketRead0(Native Method)
> at java.net.SocketInputStream.socketRead(SocketInputStream.java:116)
> at java.net.SocketInputStream.read(SocketInputStream.java:171)
> at java.net.SocketInputStream.read(SocketInputStream.java:141)
> at java.io.BufferedInputStream.fill(BufferedInputStream.java:246)
> at java.io.BufferedInputStream.read1(BufferedInputStream.java:286)
> at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
> at sun.net.www.http.HttpClient.parseHTTPHeader(HttpClient.java:735)
> at sun.net.www.http.HttpClient.parseHTTP(HttpClient.java:678)
> at 
> sun.net.www.protocol.http.HttpURLConnection.getInputStream0(HttpURLConnection.java:1587)
> at 
> sun.net.www.protocol.http.HttpURLConnection.getInputStream(HttpURLConnection.java:1492)
> at java.net.HttpURLConnection.getResponseCode(HttpURLConnection.java:480)
> at 
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.verifyConnection(Fetcher.java:434)
> at 
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.setupConnectionsWithRetry(Fetcher.java:400)
> at 
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.openShuffleUrl(Fetcher.java:271)
> at 
> org.apache.hadoop.mapreduce.task.reduce.Fetcher.copyFromHost(Fetcher.java:330)
> at org.apache.hadoop.mapreduce.task.reduce.Fetcher.run(Fetcher.java:198)
> {quote}
>  We check the NodeManager server find that the disk IO util and connections 
> became very high when the read timeout happened.We analyze that if we have 
> 20,000 maps and 1,000 reduces which will make NodeManager generate 20 million 
> times IO stream operate in the shuffle phase.If the reduce fetch data size is 
> very small from map output files.Which make the disk IO util become very high 
> in big cluster.Then read timeout happened frequently.The application finished 
> time become longer.
> We find ShuffleHandler have IndexCache for cache file.out.index file.Then we 
> want to change the small IO to big IO which can reduce the small disk IO 
> times. So we try to cache all the small file data(file.out) in memory when 
> the first fetch request come.Then the others fetch request only need read 
> data from memory avoid disk IO operation.After we cache data to memory we 
> find the read timeout disappeared.
>  



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