Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/18444#discussion_r125171044
--- Diff: python/pyspark/sql/types.py ---
@@ -935,6 +936,86 @@ 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, § 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 > "2":
+# _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.")
+
+_array_type_mappings = {
+ # Warning: Actual properties for float and double in C is not
unspecified.
--- End diff --
So I think you mean to say "is not specified"
On the other hand, is there a reason we couldn't use sys.float_info to
determine the ranges on this? I have not done a lot of poking with float arrays
in Python though so just a question.
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