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https://issues.apache.org/jira/browse/HIVE-165?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12656219#action_12656219
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David Phillips commented on HIVE-165:
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Rather than add a non-standard VAR function, we should add these ANSI SQL 2003
functions:
COVAR_POP
COVAR_SAMP
STDDEV_POP
STDDEV_SAMP
VAR_POP
VAR_SAMP
I recommend against adding the non-standard STDDEV and VARIANCE functions as
their behavior differs between MySQL (population) and Oracle/PostgreSQL
(sample).
For the time being, you can use this workaround:
VAR_POP = (SUM(x * x) - (SUM(x) * AVG(x))) / COUNT(x)
VAR_SAMP = (SUM(x * x) - (SUM(x) * AVG(x))) / (COUNT(x) - 1)
> var(col) built-in to go with avg(col) and count(col)
> ----------------------------------------------------
>
> Key: HIVE-165
> URL: https://issues.apache.org/jira/browse/HIVE-165
> Project: Hadoop Hive
> Issue Type: Wish
> Reporter: Adam Kramer
> Priority: Minor
>
> The last step in the unholy triumvirate of statistical built-ins is the
> variance. We already have the n (count) and the mean (avg). I currently have
> a job or two that filters all of the data into a single reducer which just
> computes mean/n/variance and writes it to a table...so my guess is that this
> would be a pretty big speed increase. Not a huge deal though, as computing
> the variance myself is trivial.
> (Average, variance, and n can be co-computed in one pass, so if you're doing
> var() you can basically have avg() and count() for free.)
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