Details
Major Description
This PR intends to fix bus for casting data from/to PythonUserDefinedType. A sequence of queries to reproduce this issue is as follows;
>>> from pyspark.sql import Row >>> from pyspark.sql.functions import col >>> from pyspark.sql.types import * >>> from pyspark.testing.sqlutils import * >>> >>> row = Row(point=ExamplePoint(1.0, 2.0)) >>> df = spark.createDataFrame([row]) >>> df.select(col("point").cast(PythonOnlyUDT())) Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/Users/maropu/Repositories/spark/spark-master/python/pyspark/sql/dataframe.py", line 1402, in select jdf = self._jdf.select(self._jcols(*cols)) File "/Users/maropu/Repositories/spark/spark-master/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1305, in __call__ File "/Users/maropu/Repositories/spark/spark-master/python/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/Users/maropu/Repositories/spark/spark-master/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o44.select. : java.lang.NullPointerException at org.apache.spark.sql.types.UserDefinedType.acceptsType(UserDefinedType.scala:84) at org.apache.spark.sql.catalyst.expressions.Cast$.canCast(Cast.scala:96) at org.apache.spark.sql.catalyst.expressions.CastBase.checkInputDataTypes(Cast.scala:267) at org.apache.spark.sql.catalyst.expressions.CastBase.resolved$lzycompute(Cast.scala:290) at org.apache.spark.sql.catalyst.expressions.CastBase.resolved(Cast.scala:290)}}
A root cause of this issue is that, since PythonUserDefinedType#userClassis always null, isAssignableFrom in UserDefinedType#acceptsType throws a null exception. To fix it, this PR defines acceptsType in PythonUserDefinedType and filters out the null case in UserDefinedType#acceptsType.
