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Posted to issues@spark.apache.org by "Luke Miner (JIRA)" <ji...@apache.org> on 2016/04/04 21:54:25 UTC
[jira] [Commented] (SPARK-14141) Let user specify datatypes of
pandas dataframe in toPandas()
[ https://issues.apache.org/jira/browse/SPARK-14141?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15224934#comment-15224934 ]
Luke Miner commented on SPARK-14141:
------------------------------------
Do you think you could sketch out your method? I'd love to try this out myself. How does count help?
> Let user specify datatypes of pandas dataframe in toPandas()
> ------------------------------------------------------------
>
> Key: SPARK-14141
> URL: https://issues.apache.org/jira/browse/SPARK-14141
> Project: Spark
> Issue Type: New Feature
> Components: Input/Output, PySpark, SQL
> Reporter: Luke Miner
> Priority: Minor
>
> Would be nice to specify the dtypes of the pandas dataframe during the toPandas() call. Something like:
> bq. pdf = df.toPandas(dtypes={'a': 'float64', 'b': 'datetime64', 'c': 'bool', 'd': 'category'})
> Since dtypes like `category` are more memory efficient, you could potentially load many more rows into a pandas dataframe with this option without running out of memory.
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