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https://issues.apache.org/jira/browse/HIVE-165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Adam Kramer updated HIVE-165:
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Description:
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.)
was: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
one reduce step that 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)
> 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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