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Date: Thu, 13 Dec 2012 19:30:13 +0000 (UTC)
From: "Josh Wills (JIRA)" <jira@apache.org>
To: crunch-dev@incubator.apache.org
Message-ID: <JIRA.12623763.1355412253398.2380.1355427013167@arcas>
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Subject: [jira] [Commented] (CRUNCH-132) Repeated runs result in duplicated
 output data
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    [ https://issues.apache.org/jira/browse/CRUNCH-132?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13531363#comment-13531363 ] 

Josh Wills commented on CRUNCH-132:
-----------------------------------

@Gabriel +1-- all three are valid options under different circumstances. I've never been totally sure what the API/impl for this should look like: should it live on Target? Should it be an option you can specify when creating a new Target? Should it be orthogonal to Target, since in some sense you could say that these options apply for any Path-related Target (although I'm not sure what makes sense for HBase targets.) Maybe something on Pipeline.write, with an option for setting a global default strategy for the Pipeline as a whole?

This would be a fair amount of work to do, so it would be good to have a loose consensus on the approach before we go down one of these paths.
                
> Repeated runs result in duplicated output data
> ----------------------------------------------
>
>                 Key: CRUNCH-132
>                 URL: https://issues.apache.org/jira/browse/CRUNCH-132
>             Project: Crunch
>          Issue Type: Bug
>    Affects Versions: 0.4.0
>            Reporter: Dave Beech
>
> Usually when you run a mapreduce job and the output directory already exists, the job fails (won't start). A Crunch job does run, but results in the output data being duplicated in the output directory with numbered files that follow on from the previous run. 
> Example
> Run 1, single reducer /output -> /output/part-r-00000
> Run 2, single reducer /output -> /output/part-r-00000, /output/part-r-00001
> I didn't realise I'd run my job twice, so when I looked in the directory it seemed that there had been 2 reducers and somehow the output had been generated twice, which was confusing. 
> I realise this may be by design, but it feels wrong to me. I'd prefer if the behaviour of a standard mapreduce job was preserved.  

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