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[SPARK-3013] [SQL] [PySpark] convert array into list #1928

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[SPARK-3013] [SQL] [PySpark] convert array into list #1928

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14 changes: 7 additions & 7 deletions python/pyspark/sql.py
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Original file line number Diff line number Diff line change
Expand Up @@ -498,10 +498,7 @@ def _infer_schema(row):

def _create_converter(obj, dataType):
"""Create an converter to drop the names of fields in obj """
if not _has_struct(dataType):
return lambda x: x

elif isinstance(dataType, ArrayType):
if isinstance(dataType, ArrayType):
conv = _create_converter(obj[0], dataType.elementType)
return lambda row: map(conv, row)

Expand All @@ -510,6 +507,9 @@ def _create_converter(obj, dataType):
conv = _create_converter(value, dataType.valueType)
return lambda row: dict((k, conv(v)) for k, v in row.iteritems())

elif not isinstance(dataType, StructType):
return lambda x: x

# dataType must be StructType
names = [f.name for f in dataType.fields]

Expand All @@ -529,8 +529,7 @@ def _create_converter(obj, dataType):
elif hasattr(obj, "__dict__"): # object
conv = lambda o: [o.__dict__.get(n, None) for n in names]

nested = any(_has_struct(f.dataType) for f in dataType.fields)
if not nested:
if all(isinstance(f.dataType, PrimitiveType) for f in dataType.fields):
return conv

row = conv(obj)
Expand Down Expand Up @@ -1037,7 +1036,8 @@ def inferSchema(self, rdd):
raise ValueError("The first row in RDD is empty, "
"can not infer schema")
if type(first) is dict:
warnings.warn("Using RDD of dict to inferSchema is deprecated")
warnings.warn("Using RDD of dict to inferSchema is deprecated,"
"please use pyspark.Row instead")

schema = _infer_schema(first)
rdd = rdd.mapPartitions(lambda rows: _drop_schema(rows, schema))
Expand Down