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https://issues.apache.org/jira/browse/SPARK-21358?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin resolved SPARK-21358.
---------------------------------
Resolution: Fixed
Assignee: chie hayashida
Fix Version/s: 2.3.0
> Argument of repartitionandsortwithinpartitions at pyspark
> ---------------------------------------------------------
>
> Key: SPARK-21358
> URL: https://issues.apache.org/jira/browse/SPARK-21358
> Project: Spark
> Issue Type: Improvement
> Components: Documentation, Examples
> Affects Versions: 2.1.1
> Reporter: chie hayashida
> Assignee: chie hayashida
> Priority: Minor
> Fix For: 2.3.0
>
>
> In rdd.py, implementation of repartitionandsortwithinpartitions is below.
> {code}
> def repartitionAndSortWithinPartitions(self, numPartitions=None,
> partitionFunc=portable_hash,
> ascending=True, keyfunc=lambda x:
> x):
> {code}
> And at document, there is following sample script.
> {code}
> >>> rdd = sc.parallelize([(0, 5), (3, 8), (2, 6), (0, 8), (3, 8), (1,
> 3)])
> >>> rdd2 = rdd.repartitionAndSortWithinPartitions(2, lambda x: x % 2,
> 2)
> {code}
> The third argument (ascending) expected to be boolean, so following script is
> better, I think.
> {code}
> >>> rdd = sc.parallelize([(0, 5), (3, 8), (2, 6), (0, 8), (3, 8), (1,
> 3)])
> >>> rdd2 = rdd.repartitionAndSortWithinPartitions(2, lambda x: x % 2,
> True)
> {code}
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