[jira] [Commented] (PIG-3979) group all performance, garbage collection, and incremental aggregation

["Mona Chitnis (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/PIG-3979?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14015091#comment-14015091 ] 

Mona Chitnis commented on PIG-3979:
-----------------------------------

Thanks for this JIRA David. Can you attach just the diff patch so its easier to review the changes? you can use command {{git diff --no-prefix > PIG-3979-v1.patch}} in your local repository

> group all performance, garbage collection, and incremental aggregation
> ----------------------------------------------------------------------
>
>                 Key: PIG-3979
>                 URL: https://issues.apache.org/jira/browse/PIG-3979
>             Project: Pig
>          Issue Type: Improvement
>          Components: impl
>    Affects Versions: 0.12.0, 0.11.1
>            Reporter: David Dreyfus
>             Fix For: 0.13.0
>
>         Attachments: POPartialAgg.java
>
>
> I have a PIG statement similar to:
> summary = foreach (group data ALL) generate 
> COUNT(data.col1), SUM(data.col2), SUM(data.col2)
> , Moments(col3)
> , Moments(data.col4)
> There are a couple of hundred columns.
> I set the following:
> SET pig.exec.mapPartAgg true;
> SET pig.exec.mapPartAgg.minReduction 3;
> SET pig.cachedbag.memusage 0.05;
> I found that when I ran this on a JVM with insufficient memory, the process eventually timed out because of an infinite garbage collection loop.
> The problem was invariant to the memusage setting.
> I solved the problem by making changes to:
> org.apache.pig.backend.hadoop.executionengine.physicalLayer.relationalOperator.POPartialAgg.java
> Rather than reading in 10000 records to establish an estimate of the reduction, I make an estimate after reading in enough tuples to fill pig.cachedbag.memusage percent of Runtime.getRuntime().maxMemory().
> I also made a change to guarantee at least one record allowed in second tier storage. In the current implementation, if the reduction is very high 1000:1, space in second tier storage is zero.
> With these changes, I can summarize large data sets with small JVMs. I also find that setting pig.cachedbag.memusage to a small number such as 0.05 results in much better garbage collection performance without reducing throughput. I suppose tuning GC would also solve a problem with excessive garbage collection.
> The performance is sweet. 



--
This message was sent by Atlassian JIRA
(v6.2#6252)