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https://issues.apache.org/jira/browse/HIVE-223?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12678073#action_12678073
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Joydeep Sen Sarma commented on HIVE-223:
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+ // In case merge is called without an iterate, the
+ if (pos == -1) {
+ mSum += Double.parseDouble(o);
+ mCount ++;
+ }
assuming this happens when iterate is called with null - is it correct to
include the null entry in the count?
I did some search on web (for ex:
http://www.databasejournal.com/features/mssql/article.php/3399931/Working-With-Columns-That-Contain-Null-Values.htm)
- it suggests that AVG definition skips nulls ..
anyway - this is inconsistent with the way the iterate is coded (the iterate
doesn't bump count for nulls)
> when using map-side aggregates - perform single map-reduce group-by
> -------------------------------------------------------------------
>
> Key: HIVE-223
> URL: https://issues.apache.org/jira/browse/HIVE-223
> Project: Hadoop Hive
> Issue Type: Improvement
> Components: Query Processor
> Reporter: Joydeep Sen Sarma
> Assignee: Namit Jain
> Attachments: 223.2.txt, 223.3.txt, 223.patch1.txt, patch.txt
>
>
> today even when we do map side aggregates - we do multiple map-reduce jobs.
> however - the reason for doing multiple map-reduce group-bys (for single
> group-bys) was the fear of skews. When we are doing map side aggregates -
> skews should not exist for the most part. There can be two reason for skews:
> - large number of entries for a single grouping set - map side aggregates
> should take care of this
> - badness in hash function that sends too much stuff to one reducer - we
> should be able to take care of this by having good hash functions (and prime
> number reducer counts)
> So i think we should be able to do a single stage map-reduce when doing
> map-side aggregates.
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