[jira] Updated: (HIVE-165) var(col) built-in to go with avg(col) and count(col)

["Adam Kramer (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/HIVE-165?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Adam Kramer updated HIVE-165:
-----------------------------

    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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