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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/01/29 01:51:40 UTC
[jira] [Assigned] (SPARK-12913) Reimplement stddev/variance as
declarative function
[ https://issues.apache.org/jira/browse/SPARK-12913?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Apache Spark reassigned SPARK-12913:
------------------------------------
Assignee: (was: Apache Spark)
> Reimplement stddev/variance as declarative function
> ---------------------------------------------------
>
> Key: SPARK-12913
> URL: https://issues.apache.org/jira/browse/SPARK-12913
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Reporter: Davies Liu
>
> As benchmarked and discussed here: https://github.com/apache/spark/pull/10786/files#r50038294.
> Benefits from codegen, the declarative aggregate function could be much faster than imperative one, we should re-implement all the builtin aggregate functions as declarative one.
> For skewness and kurtosis, we need to benchmark it to make sure that the declarative one is actually faster than imperative one.
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