Github user BryanCutler commented on a diff in the pull request:
https://github.com/apache/spark/pull/15821#discussion_r106237765
--- Diff: python/pyspark/sql/dataframe.py ---
@@ -1597,21 +1598,46 @@ def toDF(self, *cols):
return DataFrame(jdf, self.sql_ctx)
@since(1.3)
- def toPandas(self):
- """Returns the contents of this :class:`DataFrame` as Pandas
``pandas.DataFrame``.
+ def toPandas(self, useArrow=False):
+ """
+ Returns the contents of this :class:`DataFrame` as Pandas
``pandas.DataFrame``.
This is only available if Pandas is installed and available.
+ :param useArrow: Make use of Apache Arrow for conversion, pyarrow
must be installed
+ and available on the calling Python process (Experimental).
+
.. note:: This method should only be used if the resulting
Pandas's DataFrame is expected
to be small, as all the data is loaded into the driver's
memory.
+ .. note:: Using pyarrow is experimental and currently supports the
following data types:
+ StringType, BinaryType, BooleanType, DoubleType, FloatType,
ByteType, IntegerType,
+ LongType, ShortType
+
>>> df.toPandas() # doctest: +SKIP
age name
0 2 Alice
1 5 Bob
"""
- import pandas as pd
- return pd.DataFrame.from_records(self.collect(),
columns=self.columns)
+ if useArrow:
+ from pyarrow.table import concat_tables
+ tables = self._collectAsArrow()
+ table = concat_tables(tables)
+ return table.to_pandas()
+ else:
+ import pandas as pd
+ return pd.DataFrame.from_records(self.collect(),
columns=self.columns)
+
+ def _collectAsArrow(self):
--- End diff --
This is done on the Scala tests, the error that is thrown is:
```
java.lang.UnsupportedOperationException: Unsupported data type:
ArrayType(IntegerType,false)
at org.apache.spark.sql.ColumnWriter$.apply(ArrowConverters.scala:416)
at
org.apache.spark.sql.ArrowConverters$$anonfun$1.apply(ArrowConverters.scala:162)
```
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