Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/15821#discussion_r122282259
--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1648,8 +1650,30 @@ def toPandas(self):
0 2 Alice
1 5 Bob
"""
- import pandas as pd
- return pd.DataFrame.from_records(self.collect(),
columns=self.columns)
+ if self.sql_ctx.getConf("spark.sql.execution.arrow.enable",
"false").lower() == "true":
+ try:
+ import pyarrow
+ tables = self._collectAsArrow()
+ table = pyarrow.concat_tables(tables)
+ return table.to_pandas()
--- End diff --
`toPandas()` is a collect operation on the driver, so all data will have to
be present before the pandas.DataFrame can be made regardless. As @leifwalsh
pointed out, the batch size limiting is to benefit the JVM running the
executor, which might have different limitations that the driver.
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