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From "Costin Leau (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (PIG-4592) Pig 0.15 stopped working with Hadoop 1.x
Date Wed, 17 Jun 2015 17:16:01 GMT

    [ https://issues.apache.org/jira/browse/PIG-4592?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14590121#comment-14590121
] 

Costin Leau commented on PIG-4592:
----------------------------------

The latest artifact works for me. 
However, republishing a stable artifact is not a good practice since the previous binaries
have been already distributed and Maven & co won't download the new ones. As far as Maven
is concerned, once something is released, it is frozen (I wasn't even aware maven central
allows republication).
In my case I had to nuke Pig from my local repository - I expect others to face the same issue.
Doing a 0.15.1 release, even if it's binary the same, clarifies the situation and avoid any
confusion about when the jar was downloaded in my opinion,

> Pig 0.15 stopped working with Hadoop 1.x
> ----------------------------------------
>
>                 Key: PIG-4592
>                 URL: https://issues.apache.org/jira/browse/PIG-4592
>             Project: Pig
>          Issue Type: Bug
>          Components: build
>    Affects Versions: 0.15.0
>         Environment: Hadoop 1.x and pig.jar retrieved from Maven
>            Reporter: Costin Leau
>            Assignee: Daniel Dai
>            Priority: Blocker
>             Fix For: 0.15.0
>
>         Attachments: PIG-4592-1.patch
>
>
> It looks like the Maven jar for Pig 0.15 is built against Hadoop 1.x instead of Hadoop
2.x.
> Running Pig 0.15 against a Hadoop 1 environment (which works fine in 0.14) triggers a
storm of class not found exceptions for classes in Hadoop 2 (like org/apache/hadoop/mapreduce/task/JobContextImpl).
> The culprit seems to be the HadoopShim included in 0.15 which is different from 0.14
(and previous) - it's part of hadoop23 instead of hadoop20 package (whatever that means).
> As it stands right now, using Pig 0.15 from Maven (common case) with Hadoop 1.x is impossible.



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