[jira] [Commented] (TIKA-2643) Tika call hangs when processes a pdf on Cloudera Hadoop

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[jira] [Commented] (TIKA-2643) Tika call hangs when processes a pdf on Cloudera Hadoop

JIRA jira@apache.org

    [ https://issues.apache.org/jira/browse/TIKA-2643?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16477458#comment-16477458 ]

feng ye commented on TIKA-2643:
-------------------------------

Thanks Tim for looking into this!

I have no problem processing this file locally using Tika and as I stated I can even process it against Hortonworks cluster. This file is not that large and our tester pulled it from Tika test suite. In OOM case it would through an exception while in my case it just hangs without an error. So it must be a combination of Tika and Cloudera. Cloudera side would just say you clearly have a hang in third party code that they do not own. 

The tricky part is I cannot attach a debugger against this call within MapReduce job over the cluster. 

Could you offer some insights on what might cause the hang? 

> Tika call hangs when processes a pdf on Cloudera Hadoop
> -------------------------------------------------------
>
>                 Key: TIKA-2643
>                 URL: https://issues.apache.org/jira/browse/TIKA-2643
>             Project: Tika
>          Issue Type: Bug
>          Components: parser
>    Affects Versions: 1.17
>         Environment: Cloudera Hadoop 5.8
>            Reporter: feng ye
>            Priority: Blocker
>         Attachments: hang-stdout.txt, hang.zip, testJournalParser.pdf
>
>
> Tika.parseToString(InputStream) hangs when called within a MapReduce job to process a pdf file from Cloudera Hadoop 5.8 (observed on 5.4 too). It can process some other pdf files on the same cluster. I am attaching the file and the syslog as well as stdout logs. Interesting that the same file can be processed fine over a Hortonworks cluster. 
> This issue is a blocker for us to make our feature based on Tika available to Cloudera cluster, a major flavor of Hadoop, so your timely attention would be very much appreciated.



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