Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/18444#discussion_r128240401
--- Diff: python/pyspark/sql/types.py ---
@@ -915,6 +916,93 @@ 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. Also, JVM only support signed types, when converting unsigned
types,
+# keep in mind that it required 1 more bit when stored as singed types.
+#
+# 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
+# Reference for JVM's supported integral types:
+# http://docs.oracle.com/javase/specs/jvms/se8/html/jvms-2.html#jvms-2.3.1
+
+_array_signed_int_typecode_ctype_mappings = {
+ 'b': ctypes.c_byte,
+ 'h': ctypes.c_short,
+ 'i': ctypes.c_int,
+ 'l': ctypes.c_long,
+}
+
+_array_unsigned_int_typecode_ctype_mappings = {
+ 'B': ctypes.c_ubyte,
+ 'H': ctypes.c_ushort,
+ 'I': ctypes.c_uint,
+ 'L': ctypes.c_ulong
+}
+
+
+def _int_size_to_type(size):
+ """
+ Return the Scala type from the size of integers.
--- End diff --
nit: Scala type -> Catalyst datatype.
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