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Posted to issues@spark.apache.org by "Josh Rosen (JIRA)" <ji...@apache.org> on 2016/09/13 00:37:21 UTC
[jira] [Created] (SPARK-17514) df.take(1) and df.limit(1).collect()
perform differently in Python
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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