Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/17435#discussion_r108082197
--- Diff: python/pyspark/sql/types.py ---
@@ -57,7 +57,25 @@ def __ne__(self, other):
@classmethod
def typeName(cls):
- return cls.__name__[:-4].lower()
+ typeTypeNameMap = {"DataType": "data",
+ "NullType": "null",
+ "StringType": "string",
+ "BinaryType": "binary",
+ "BooleanType": "boolean",
+ "DateType": "date",
+ "TimestampType": "timestamp",
+ "DecimalType": "decimal",
+ "DoubleType": "double",
+ "FloatType": "float",
+ "ByteType": "byte",
+ "IntegerType": "integer",
+ "LongType": "long",
+ "ShortType": "short",
+ "ArrayType": "array",
+ "MapType": "map",
+ "StructField": "struct",
--- End diff --
Yeah, I don't think it is valid to call `typeName` against a `StructField`.
Actually, `StructField` is not a data type, strictly speaking...
I don't know why `StructField` inherits `DataType` in pyspark. In scala, it
is not.
Throwing an exception when calling `typeName` on `StructField` seems good
enough, instead of a map like this.
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