Github user zasdfgbnm commented on a diff in the pull request:

    https://github.com/apache/spark/pull/18444#discussion_r127521525
  
    --- Diff: python/pyspark/sql/types.py ---
    @@ -915,6 +916,90 @@ def _parse_datatype_json_value(json_value):
             long: LongType,
         })
     
    +# Mapping Python array types to Spark SQL DataType
    +# We should be careful here. The size of these types in python depends on C
    +# implementation. We need to make sure that this conversion does not lose 
any
    +# precision.
    +#
    +# Reference for C integer size, see:
    +# ISO/IEC 9899:201x specification, chapter 5.2.4.2.1 Sizes of integer 
types <limits.h>.
    +# Reference for python array typecode, see:
    +# https://docs.python.org/2/library/array.html
    +# https://docs.python.org/3.6/library/array.html
    +
    +_array_int_typecode_ctype_mappings = {
    +    'b': ctypes.c_byte,
    +    'B': ctypes.c_ubyte,
    +    'h': ctypes.c_short,
    +    'H': ctypes.c_ushort,
    +    'i': ctypes.c_int,
    +    'I': ctypes.c_uint,
    +    'l': ctypes.c_long,
    +    'L': ctypes.c_ulong
    +}
    +
    +# TODO: Uncomment this when 'q' and 'Q' are supported by 
net.razorvine.pickle
    +# Type code 'q' and 'Q' are not available at python 2
    +# if sys.version_info[0] >= 3:
    +#     _array_int_typecode_ctype_mappings.update({
    +#         'q': ctypes.c_longlong,
    +#         'Q': ctypes.c_ulonglong
    +#     })
    +
    +
    +def _int_size_to_type(size):
    +    """
    +    Return the Scala type from the size of integers.
    +    """
    +    if size <= 8:
    +        return ByteType
    +    if size <= 16:
    +        return ShortType
    +    if size <= 32:
    +        return IntegerType
    +    if size <= 64:
    +        return LongType
    +    raise TypeError("not supported type: integer size too large.")
    +
    +# The list of all supported array typecodes is stored here
    +_array_type_mappings = {
    +    # Warning: Actual properties for float and double in C is not 
specified in C.
    +    # On almost every system supported by both python and JVM, they are 
IEEE 754
    +    # single-precision binary floating-point format and IEEE 754 
double-precision
    +    # binary floating-point format. And we do assume the same thing here 
for now.
    +    'f': FloatType,
    +    'd': DoubleType
    +}
    +
    +# compute array typecode mappings for integer types
    +for _typecode in _array_int_typecode_ctype_mappings.keys():
    +    size = ctypes.sizeof(_array_int_typecode_ctype_mappings[_typecode]) * 8
    +    if _typecode.isupper():  # 1 extra bit is required to store unsigned 
types
    --- End diff --
    
    This is actually a good suggestion!


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