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From "Xiaochuan Yu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (YARN-1440) Yarn aggregated logs are difficult for external tools to understand
Date Sun, 22 Oct 2017 21:21:03 GMT

    [ https://issues.apache.org/jira/browse/YARN-1440?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16214458#comment-16214458
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Xiaochuan Yu commented on YARN-1440:
------------------------------------

Is there any updates on this?
Does the "many small files" performance problem apply to S3 and NFS?
The proposed simple raw file structure would be ideal for my use case at least.
Maybe make it optional? Users can choose to either have the simple raw file structure or the
current behaviour.

> Yarn aggregated logs are difficult for external tools to understand
> -------------------------------------------------------------------
>
>                 Key: YARN-1440
>                 URL: https://issues.apache.org/jira/browse/YARN-1440
>             Project: Hadoop YARN
>          Issue Type: Sub-task
>            Reporter: ledion bitincka
>              Labels: log-aggregation, logs, tfile, yarn
>
> The log aggregation feature in Yarn is awesome! However, the file type and format in
which the log files are aggregated into (TFile) should either be much simpler or be made pluggable.
The current TFile format forces anyone who wants to see the files to either 
> a) use the web UI
> b) use the CLI tools (yarn logs)  or 
> c) write custom code to read the files 
> My suggestion would be to simplify the log collection by collecting and writing the raw
log files into a directory structure as follows: 
> {noformat}
> /{log-collection-dir}/{app-id}/{container-id}/{log-file-name} 
> {noformat}
> This way the application developers can (re)use a much wider array of tools to process
the logs. 
> For the readers who are not familiar with logs and their format you can find more info
the following two blog posts:
> http://hortonworks.com/blog/simplifying-user-logs-management-and-access-in-yarn/
> http://blogs.splunk.com/2013/11/18/hadoop-2-0-rant/



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