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https://issues.apache.org/jira/browse/PIG-2779?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13422001#comment-13422001
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Bill Graham commented on PIG-2779:
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Jie, as part of this clean up it would be really useful to record the various 
parallelism values in the job conf for later analysis. I was thinking we 
capture defaultParallel, requestedParallelism and runtimeParallelism (which 
should == {{mapred.reduce.tasks}}, right). That way we can see later which 
values were set and which was used. It would be great to know whether 
parallelism was determined by a {{PARALLEL}} statement, via estimation, or via 
a default. This would be in addition to the following related params we 
currently capture:

{noformat}
pig.exec.reducers.max
pig.exec.reducers.bytes.per.reducer
{noformat}

Do you want to add this to this issue or do you think we should we do this in a 
separate JIRA? 

I use IntelliJ and I've just set the syntax to match Apaches.
                
> Refactoring the code for setting number of reducers
> ---------------------------------------------------
>
>                 Key: PIG-2779
>                 URL: https://issues.apache.org/jira/browse/PIG-2779
>             Project: Pig
>          Issue Type: Bug
>            Reporter: Jie Li
>            Assignee: Jie Li
>             Fix For: 0.11
>
>         Attachments: PIG-2779.0.patch, PIG-2779.1.patch, PIG-2779.2.patch, 
> TestNumberOfReducers.java, TestNumberOfReducers.java
>
>
> As PIG-2652 observed, currently the code for setting number of reducers is a 
> little messy. MapReduceOper.requestedParallelism seems being misused in some 
> plases, and now we support runtime estimation of #reducer which further 
> complicates the problem.
> For example, if we specify parallel 1 for the order-by, the estimated 
> #reducer will be used. If we specify parallel 2 while it estimates 4, 
> order-by will fail due to "Illegal partition for Null". If we specify 
> parallel 4 while it estimates 2, then some reducers will have nothing to do. 

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