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From "Selina Zhang (JIRA)" <>
Subject [jira] [Updated] (HIVE-10036) Writing ORC format big table causes OOM - too many fixed sized stream buffers
Date Tue, 14 Apr 2015 02:24:12 GMT


Selina Zhang updated HIVE-10036:
    Attachment: HIVE-10036.6.patch

Test case vectorization_short_regress.q complained
java.lang.NoClassDefFoundError: io/netty/buffer/Unpooled
indicates the new jetty-4.0 jar is missing from the test environment. However, I cannot reproduce
the error locally. I run the unit tests locally and all seem fine. Upload the patch again
in case there was something messed up. 


> Writing ORC format big table causes OOM - too many fixed sized stream buffers
> -----------------------------------------------------------------------------
>                 Key: HIVE-10036
>                 URL:
>             Project: Hive
>          Issue Type: Improvement
>            Reporter: Selina Zhang
>            Assignee: Selina Zhang
>         Attachments: HIVE-10036.1.patch, HIVE-10036.2.patch, HIVE-10036.3.patch, HIVE-10036.5.patch,
> ORC writer keeps multiple out steams for each column. Each output stream is allocated
fixed size ByteBuffer (configurable, default to 256K). For a big table, the memory cost is
unbearable. Specially when HCatalog dynamic partition involves, several hundreds files may
be open and writing at the same time (same problems for FileSinkOperator). 
> Global ORC memory manager controls the buffer size, but it only got kicked in at 5000
rows interval. An enhancement could be done here, but the problem is reducing the buffer size
introduces worse compression and more IOs in read path. Sacrificing the read performance is
always not a good choice. 
> I changed the fixed size ByteBuffer to a dynamic growth buffer which up bound to the
existing configurable buffer size. Most of the streams does not need large buffer so the performance
got improved significantly. Comparing to Facebook's hive-dwrf, I monitored 2x performance
gain with this fix. 
> Solving OOM for ORC completely maybe needs lots of effort , but this is definitely a
low hanging fruit. 

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