[jira] [Commented] (SPARK-7322) Window function support in Scala/Java DataFrame DSL

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

    [ https://issues.apache.org/jira/browse/SPARK-7322?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14555811#comment-14555811 ] 

Olivier Girardot commented on SPARK-7322:
-----------------------------------------

Thank you, that's great news !

> Window function support in Scala/Java DataFrame DSL
> ---------------------------------------------------
>
>                 Key: SPARK-7322
>                 URL: https://issues.apache.org/jira/browse/SPARK-7322
>             Project: Spark
>          Issue Type: Sub-task
>          Components: SQL
>            Reporter: Reynold Xin
>            Assignee: Cheng Hao
>              Labels: DataFrame
>             Fix For: 1.4.0
>
>
> Here's a proposal for supporting window functions in the DataFrame DSL:
> 1. Add an over function to Column:
> {code}
> class Column {
>   ...
>   def over(window: Window): Column
>   ...
> }
> {code}
> 2. Window:
> {code}
> object Window {
>   def partitionBy(...): Window
>   def orderBy(...): Window
>   object Frame {
>     def unbounded: Frame
>     def preceding(n: Long): Frame
>     def following(n: Long): Frame
>   }
>   class Frame
> }
> class Window {
>   def orderBy(...): Window
>   def rowsBetween(Frame, Frame): Window
>   def rangeBetween(Frame, Frame): Window  // maybe add this later
> }
> {code}
> Here's an example to use it:
> {code}
> df.select(
>   avg(“age”).over(Window.partitionBy(“..”, “..”).orderBy(“..”, “..”)
>     .rowsBetween(Frame.unbounded, Frame.currentRow))
> )
> df.select(
>   avg(“age”).over(Window.partitionBy(“..”, “..”).orderBy(“..”, “..”)
>     .rowsBetween(Frame.preceding(50), Frame.following(10)))
> )
> {code}



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