[jira] [Updated] (SPARK-19503) Execution Plan Optimizer: avoid sort or shuffle when it does not change end result such as df.sort(...).count()

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

     [ https://issues.apache.org/jira/browse/SPARK-19503?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

R updated SPARK-19503:
----------------------
    Summary: Execution Plan Optimizer: avoid sort or shuffle when it does not change end result such as df.sort(...).count()  (was: Dumb Execution Plan)

> Execution Plan Optimizer: avoid sort or shuffle when it does not change end result such as df.sort(...).count()
> ---------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-19503
>                 URL: https://issues.apache.org/jira/browse/SPARK-19503
>             Project: Spark
>          Issue Type: Bug
>          Components: Optimizer
>    Affects Versions: 2.1.0
>         Environment: Perhaps only a pyspark or databricks AWS issue
>            Reporter: R
>            Priority: Minor
>              Labels: execution, optimizer, plan, query
>
> df.sort(...).count()
> performs shuffle and sort and then count! This is wasteful as sort is not required here and makes me wonder how smart the algebraic optimiser is indeed! The data may be partitioned by known count (such as parquet files) and we should not shuffle to just perform count.
> This may look trivial, but if optimiser fails to recognise this, I wonder what else is it missing especially in more complex operations.



--
This message was sent by Atlassian JIRA
(v6.3.15#6346)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org