[jira] [Assigned] (SPARK-7322) Add DataFrame DSL for window function support

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

     [ https://issues.apache.org/jira/browse/SPARK-7322?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-7322:
-----------------------------------

    Assignee: Cheng Hao  (was: Apache Spark)

> Add DataFrame DSL for window function support
> ---------------------------------------------
>
>                 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
>
> Here's a proposal for supporting window functions in the DataFrame DSL:
> 1. Add an over function to Column:
> {code}
> class Column {
>   ...
>   def over(): WindowFunctionSpec
>   ...
> }
> {code}
> 2. WindowFunctionSpec:
> {code}
> // By default frame = full partition
> class WindowFunctionSpec {
>   def partitionBy(cols: Column*): WindowFunctionSpec
>   def orderBy(cols: Column*): WindowFunctionSpec
>   // restrict frame beginning from current row - n position
>   def rowsPreceding(n: Int): WindowFunctionSpec
>   // restrict frame ending from current row - n position
>   def rowsFollowing(n: Int): WindowFunctionSpec
>   def rangePreceding(n: Int): WindowFunctionSpec
>   def rowsFollowing(n: Int): WindowFunctionSpec
> }
> {code}
> Here's an example to use it:
> {code}
> df.select(
>   df.store,
>   df.date,
>   df.sales,
>   avg(df.sales).over.partitionBy(df.store)
>                     .orderBy(df.store) 
>                     .rowsFollowing(0)    // this means from unbounded preceding to current row
> )
> {code}



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