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