[jira] [Commented] (PIG-2852) Old Hadoop API being used sometimes when running parellel in local mode

["Cheolsoo Park (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/PIG-2852?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13452429#comment-13452429 ] 

Cheolsoo Park commented on PIG-2852:
------------------------------------

I was able to narrow down the issue.

When running parellel in local mode, not every job.xml is created. As a result, some jobs end up with the default value of the "mapred.mapper.new-api" property and fail with the error. For example, when running 4 threads, job.xml files in a successful run and a failed run look as follows:

Successful run:
{code}
cheolsoo@localhost:/tmp/hadoop-cheolsoo/mapred/local $ls -1 localRunner/
job_local_0001.xml
job_local_0002.xml
job_local_0003.xml
job_local_0004.xml
tmp
{code}

Failed run:
{code}
cheolsoo@localhost:/tmp/hadoop-cheolsoo/mapred/local $ls -1 localRunner/
job_local_0003.xml
tmp
{code}

I am not sure yet whether this is a hadoop LocalJobRunner issue or a pig issue.
                
> Old Hadoop API being used sometimes when running parellel in local mode
> -----------------------------------------------------------------------
>
>                 Key: PIG-2852
>                 URL: https://issues.apache.org/jira/browse/PIG-2852
>             Project: Pig
>          Issue Type: Bug
>    Affects Versions: 0.9.2, 0.10.0
>         Environment: Hadoop 0.20.205.0
>            Reporter: Brian Tan
>         Attachments: 1.pig, 1.py, generate_1_txt.py
>
>
> When I run parallel jobs in local mode, I sometimes/randomly see the following error:
> java.lang.ClassCastException: org.apache.pig.backend.hadoop.executionengine.mapReduceLayer.PigSplit cannot be cast to org.apache.hadoop.mapred.InputSplit
>     at org.apache.hadoop.mapred.MapTask.runOldMapper(MapTask.java:413)
>     at org.apache.hadoop.mapred.MapTask.run(MapTask.java:373)
>     at org.apache.hadoop.mapred.LocalJobRunner$Job.run(LocalJobRunner.java:212)
> Note the method runOldMapper. Pig sets mapred.mapper.new-api to true in JobControlCompiler.java, so I'm not sure why this can happen (sometimes)
> Steps to reproduce:
> 1) Create a 10 million line large file '1.txt'
> fout = open('1.txt', 'w')
> for i in range(1000 * 1000 * 10):
>     fout.write('%s\n' % ('\t'.join(str(x) for x in range(10))))
> fout.close()
> 2) Create pig source '1.pig'
> data = load '1.txt' as (a1:int, a2:int, a3:int, a4:int, a5:int, a6:int, a7:int, a8:int, a9:int, a10:int);
> grouped = group data all;
> stats = foreach grouped generate '$METRIC' as metric, MIN(data.$METRIC) as min_value, MAX(data.$METRIC) as max_value;
> dump stats;
> 3) Create python controller '1.py'
> from org.apache.pig.scripting import Pig
> def runMultiple():
>     compiled = Pig.compileFromFile('1.pig')
>     params = [{'METRIC' : metric} for metric in ['a3', 'a5', 'a7']]
>     bound = compiled.bind(params)
>     results = bound.run()
>     for result in results:
>         if result.isSuccessful():
>             itr = result.result('stats').iterator()
>             print itr.next().getAll()
>         else:
>             print 'Failed'
> if __name__ == "__main__":
>     runMultiple()
> 4) pig -x local 1.py
> You may need to run it a few times to get the error (it's only in stderr output, not even in pig logs). The occurrence seems to be random (sometimes the parallel jobs can succeed). Maybe caused by multi-threading complexities?
> I tried pseudo distributed mode but haven't seen this error in that mode.
> This has never happened in non-parallel job execution.

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