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https://issues.apache.org/jira/browse/HIVE-23530?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17116847#comment-17116847
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Jesus Camacho Rodriguez commented on HIVE-23530:
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[~kgyrtkirk], can you review this one?
https://github.com/apache/hive/pull/1034
Thanks
> Use SQL functions instead of compute_stats UDAF to compute column statistics
> ----------------------------------------------------------------------------
>
> Key: HIVE-23530
> URL: https://issues.apache.org/jira/browse/HIVE-23530
> Project: Hive
> Issue Type: Improvement
> Components: Statistics
> Reporter: Jesus Camacho Rodriguez
> Assignee: Jesus Camacho Rodriguez
> Priority: Major
> Attachments: HIVE-23530.01.patch, HIVE-23530.02.patch,
> HIVE-23530.03.patch, HIVE-23530.patch
>
>
> Currently we compute column statistics by relying on the {{compute_stats}}
> UDAF. For instance, for a given table {{tbl}}, the query to compute
> statistics for columns is translated internally into:
> {code}
> SELECT compute_stats(c1),
> compute_stats(c2),
> ...
> FROM tbl;
> {code}
> {{compute_stats}} produces data for the stats available for each column type,
> e.g., struct<"max":long,"min":long,"countnulls":long,...>.
> This issue is to produce a query that relies purely on SQL functions instead:
> {code}
> SELECT max(c1), min(c1), count(case when c1 is null then 1 else null end),
> ...
> FROM tbl;
> {code}
> This will allow us to deprecate the {{compute_stats}} UDAF since it mostly
> duplicates functionality found in those other functions. Additionally, many
> of those functions already provide a vectorized implementation so the
> approach can potentially improve the performance of column stats collection.
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