Hyukjin Kwon created SPARK-42021:
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Summary: createDataFrame with array.array
Key: SPARK-42021
URL: https://issues.apache.org/jira/browse/SPARK-42021
Project: Spark
Issue Type: Sub-task
Components: Connect
Affects Versions: 3.4.0
Reporter: Hyukjin Kwon
{code}
pyspark/sql/tests/test_types.py:964 (TypesParityTests.test_array_types)
self = <pyspark.sql.tests.connect.test_parity_types.TypesParityTests
testMethod=test_array_types>
def test_array_types(self):
# This test need to make sure that the Scala type selected is at least
# as large as the python's types. This is necessary because python's
# array types depend on C implementation on the machine. Therefore there
# is no machine independent correspondence between python's array types
# and Scala types.
# See: https://docs.python.org/2/library/array.html
def assertCollectSuccess(typecode, value):
row = Row(myarray=array.array(typecode, [value]))
df = self.spark.createDataFrame([row])
self.assertEqual(df.first()["myarray"][0], value)
# supported string types
#
# String types in python's array are "u" for Py_UNICODE and "c" for
char.
# "u" will be removed in python 4, and "c" is not supported in python 3.
supported_string_types = []
if sys.version_info[0] < 4:
supported_string_types += ["u"]
# test unicode
> assertCollectSuccess("u", "a")
../test_types.py:986:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
../test_types.py:975: in assertCollectSuccess
df = self.spark.createDataFrame([row])
../../connect/session.py:278: in createDataFrame
_table = pa.Table.from_pylist([row.asDict(recursive=True) for row in _data])
pyarrow/table.pxi:3700: in pyarrow.lib.Table.from_pylist
???
pyarrow/table.pxi:5221: in pyarrow.lib._from_pylist
???
pyarrow/table.pxi:3575: in pyarrow.lib.Table.from_arrays
???
pyarrow/table.pxi:1383: in pyarrow.lib._sanitize_arrays
???
pyarrow/table.pxi:1364: in pyarrow.lib._schema_from_arrays
???
pyarrow/array.pxi:320: in pyarrow.lib.array
???
pyarrow/array.pxi:39: in pyarrow.lib._sequence_to_array
???
pyarrow/error.pxi:144: in pyarrow.lib.pyarrow_internal_check_status
???
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
> ???
E pyarrow.lib.ArrowInvalid: Could not convert array('u', 'a') with type
array.array: did not recognize Python value type when inferring an Arrow data
type
pyarrow/error.pxi:100: ArrowInvalid
{code}
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