[ https://issues.apache.org/jira/browse/SPARK-7322?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Cheng Lian updated SPARK-7322: ------------------------------ Assignee: Cheng Hao > 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} -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org