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From "George Pachitariu (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (HIVE-20523) Improve table statistics for Parquet format
Date Tue, 19 Feb 2019 15:41:00 GMT

     [ https://issues.apache.org/jira/browse/HIVE-20523?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

George Pachitariu resolved HIVE-20523.
--------------------------------------
    Resolution: Duplicate

> Improve table statistics for Parquet format
> -------------------------------------------
>
>                 Key: HIVE-20523
>                 URL: https://issues.apache.org/jira/browse/HIVE-20523
>             Project: Hive
>          Issue Type: Improvement
>          Components: Physical Optimizer
>            Reporter: George Pachitariu
>            Assignee: George Pachitariu
>            Priority: Minor
>         Attachments: HIVE-20523.1.patch, HIVE-20523.10.patch, HIVE-20523.11.patch, HIVE-20523.12.patch,
HIVE-20523.2.patch, HIVE-20523.3.patch, HIVE-20523.4.patch, HIVE-20523.5.patch, HIVE-20523.6.patch,
HIVE-20523.7.patch, HIVE-20523.8.patch, HIVE-20523.9.patch, HIVE-20523.patch
>
>
> Right now, in the table basic statistics, the *raw data size* for a row with any data
type in the Parquet format is 1. This is an underestimated value when columns are complex
data structures, like arrays.
> Having tables with underestimated raw data size makes Hive assign less containers (mappers/reducers)
to it, making the overall query slower. 
> Heavy underestimation also makes Hive choose MapJoin instead of the ShuffleJoin that
can fail with OOM errors.
> In this patch, I compute the columns data size better, taking into account complex structures.
I followed the Writer implementation for the ORC format.



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