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https://issues.apache.org/jira/browse/HIVE-11414?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Zheng Shao updated HIVE-11414:
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    Summary: Fix OOM in MapTask with many input partitions with RCFile  (was: 
Fix OOM in MapTask with many input partitions by making ColumnarSerDeBase's 
cachedLazyStruct weakly referenced)

> Fix OOM in MapTask with many input partitions with RCFile
> ---------------------------------------------------------
>
>                 Key: HIVE-11414
>                 URL: https://issues.apache.org/jira/browse/HIVE-11414
>             Project: Hive
>          Issue Type: Improvement
>          Components: File Formats, Serializers/Deserializers
>    Affects Versions: 0.11.0, 0.12.0, 0.14.0, 0.13.1, 1.2.0
>            Reporter: Zheng Shao
>            Priority: Minor
>
> MapTask hit OOM in the following situation in our production environment:
> * src: 2048 partitions, each with 1 file of about 2MB using RCFile format
> * query: INSERT OVERWRITE TABLE tgt SELECT * FROM src
> * Hadoop version: Both on CDH 4.7 using MR1 and CDH 5.4.1 using YARN.
> * MapTask memory Xmx: 1.5GB
> By analyzing the heap dump using jhat, we realized that the problem is:
> * One single mapper is processing many partitions (because of 
> CombineHiveInputFormat)
> * Each input path (equivalent to partition here) will construct its own SerDe
> * Each SerDe will do its own caching of deserialized object (and try to reuse 
> it), but will never release it (in this case, the 
> serde2.columnar.ColumnarSerDeBase has a field cachedLazyStruct which can take 
> a lot of space - pretty much the last N rows of a file where N is the number 
> of rows in a columnar block).
> * This problem may exist in other SerDe as well, but columnar file format are 
> affected the most because they need bigger cache for the last N rows instead 
> of 1 row.
> Proposed solution:
> * Make cachedLazyStruct a weakly referenced object.  Do similar changes to 
> other columnar serde if any (e.g. maybe ORCFile's serde as well).
> Alternative solutions:
> * We can also free up the whole SerDe after processing a block/file.  The 
> problem with that is that the input splits may contain multiple blocks/files 
> that maps to the same SerDe, and recreating a SerDe is just more work.
> * We can also move the SerDe creation/free-up to the place when input file 
> changes.  But that requires a much bigger change to the code.
> * We can also add a "cleanup()" method to SerDe interface that release the 
> cached object, but that change is not backward compatible with many SerDes 
> that people have wrote.



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