Luke Miner created SPARK-14141:
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Summary: 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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