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https://issues.apache.org/jira/browse/SPARK-18818?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Hyukjin Kwon resolved SPARK-18818.
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Resolution: Won't Fix
> Window...orderBy() should accept an 'ascending' parameter just like
> DataFrame.orderBy()
> ---------------------------------------------------------------------------------------
>
> Key: SPARK-18818
> URL: https://issues.apache.org/jira/browse/SPARK-18818
> Project: Spark
> Issue Type: Improvement
> Components: PySpark, SQL
> Reporter: Nicholas Chammas
> Priority: Minor
>
> It seems inconsistent that {{Window...orderBy()}} does not accept an
> {{ascending}} parameter, when {{DataFrame.orderBy()}} does.
> It's also slightly inconvenient since to specify a descending sort order you
> have to build a column object, whereas with the {{ascending}} parameter you
> don't.
> For example:
> {code}
> from pyspark.sql.functions import row_number
> df.select(
> row_number()
> .over(
> Window
> .partitionBy(...)
> .orderBy('timestamp', ascending=False)))
> {code}
> vs.
> {code}
> from pyspark.sql.functions import row_number, col
> df.select(
> row_number()
> .over(
> Window
> .partitionBy(...)
> .orderBy(col('timestamp').desc())))
> {code}
> It would be better if {{Window...orderBy()}} supported an {{ascending}}
> parameter just like {{DataFrame.orderBy()}}.
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