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https://issues.apache.org/jira/browse/PIG-3263?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Jakub Glapa updated PIG-3263:
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Summary: Resolving UDFs fails while using pig embedded code in Python when
using parallel execution (was: Resolving UDFs fails while using pig embedded
code in Python when job parallelism is used.)
> Resolving UDFs fails while using pig embedded code in Python when using
> parallel execution
> ------------------------------------------------------------------------------------------
>
> Key: PIG-3263
> URL: https://issues.apache.org/jira/browse/PIG-3263
> Project: Pig
> Issue Type: Bug
> Affects Versions: 0.10.0
> Environment: pig-0.10.1, hadoop 0.20.2
> Reporter: Jakub Glapa
> Attachments: stacktrace.txt
>
>
> I started using embedded Pig in Python scripts. I had a need to execute a pig
> script with slightly different set of parameters for each run.
> The job are quite small so taking advantage of the cluster and running them
> in parallel made sense for me.
> Here's a python code I've used. (I executed it like that: bin/pig run.py
> script.pig ):
> {code}
> from org.apache.pig.scripting import Pig
> import sys
> def main():
> SCRIPT_NAME = sys.argv[1]
> jobParamsSets = prepareParameterSets()
> NUM_OF_JOBS_TO_RUN_AT_ONCE = 5
> while len(jobParamsSets) != 0:
> batchParamSet = jobParamsSets[:NUM_OF_JOBS_TO_RUN_AT_ONCE]
> del jobParamsSets[:NUM_OF_JOBS_TO_RUN_AT_ONCE]
> print 'batch to execute:', batchParamSet
> P = Pig.compileFromFile(SCRIPT_NAME)
> bound = P.bind(batchParamSet)
> stats = bound.run()
> for s in stats:
> print s.isSuccessful(), s.getDuration(), s.getReturnCode(),
> s.getErrorMessage()
> def prepareParameterSets():
> # loads properties from files and creates multiple sets of parameters
> {code}
> With {{NUM_OF_JOBS_TO_RUN_AT_ONCE}} variable I'm able to control the
> parallelism.
> I can have up to 150 parameter sets so that means 150 pig executions.
> Everything seemed to work just fine but I started noticing single failures
> for some job executions.
> It happens occasionally. 0-5 executions fail out of 150 for example. Always
> with the same kind of error.
> {code}
> 2013-02-14 16:25:04,575 [main] ERROR org.apache.pig.scripting.BoundScript -
> Pig pipeline failed to complete
> java.util.concurrent.ExecutionException:
> org.apache.pig.impl.logicalLayer.FrontendException: ERROR 1000: Error during
> parsing. Could not resolve my.pig.udf.OrderQueryTokens using imports: [,
> org.apache.pig.builtin., org.apache.pig.impl.builtin.]
> ...
> {code}
> Full stacktrace attached.
> I'm using many UDFs so the name of the UDF in the exception is changing.
> I suspect there is a threading issue somewhere.
> My best guess is that org.apache.pig.impl.PigContext.resolveClassName is not
> thread safe and when multiple threads are trying to resolve a UDF class
> something goes wrong.
> I've tried a couple of tricks hoping that maybe it would help. What I did is
> that to my knowledge there are 3 ways in how you can register your jars with
> udfs.
> # in pig script ( REGISTER lib/*.jar;)
> # in python Pig.registerJar("/lib/*.jar")
> # command line param for pig command, $PIGDIR/bin/pig
> -Dpig.additional.jars=lib/*.jar
> Initially the 1) option was used. I was thinking that maybe if I register the
> jars globally right at the beginning with the option 3) I could go around the
> bug. Well it seems the problem dropped but didn't go away fully and still
> appears from time to time.
> The problem is that I cannot provide an reproducible use case. My process is
> quite complicated and presenting it here seems infeasible. I've tried to
> strip down my scripts and have something quick and simple to present. I've
> run that with like 1000 parameter sets with parallelism set to 10 or 20 and
> it sadly never occurred.
> PS.
> With pig-0.10.1 I had to substitute the distributed jython dependency with a
> standalone version. Otherwise I wasn't able to use python standard modules.
> I couldn't try if this bug still exists in pig-0.11.0 as the version is
> incompatible with hadoo 0.20. pig-0.11.1 has not been released yet.
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