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From "Josh Rosen (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-17514) df.take(1) and df.limit(1).collect() perform differently in Python
Date Tue, 13 Sep 2016 00:37:21 GMT
Josh Rosen created SPARK-17514:
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             Summary: df.take(1) and df.limit(1).collect() perform differently in Python
                 Key: SPARK-17514
                 URL: https://issues.apache.org/jira/browse/SPARK-17514
             Project: Spark
          Issue Type: Bug
          Components: PySpark, SQL
            Reporter: Josh Rosen
            Assignee: Josh Rosen


In PySpark, {{df.take(1)}} ends up running a single-stage job which computes only one partition
of {{df}}, while {{df.limit(1).collect()}} ends up computing all partitions of {{df}} and
runs a two-stage job. This difference in performance is confusing, so I think that we should
generalize the fix from SPARK-10731 so that {{Dataset.collect()}} can be implemented efficiently
in Python.



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