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new 00d7094dc30 [SPARK-39809][PYTHON] Support CharType in PySpark
00d7094dc30 is described below
commit 00d7094dc3024ae594605b311dcc55e95d277d5f
Author: Ruifeng Zheng <ruife...@apache.org>
AuthorDate: Tue Jul 19 10:22:04 2022 +0900
[SPARK-39809][PYTHON] Support CharType in PySpark
### What changes were proposed in this pull request?
Support CharType in PySpark
### Why are the changes needed?
for function parity
### Does this PR introduce _any_ user-facing change?
yes, new type added
### How was this patch tested?
added UT
Closes #37215 from zhengruifeng/py_add_char.
Authored-by: Ruifeng Zheng <ruife...@apache.org>
Signed-off-by: Hyukjin Kwon <gurwls...@apache.org>
---
python/pyspark/sql/tests/test_types.py | 26 ++++++++++++++++++---
python/pyspark/sql/types.py | 42 +++++++++++++++++++++++++++++++---
2 files changed, 62 insertions(+), 6 deletions(-)
diff --git a/python/pyspark/sql/tests/test_types.py
b/python/pyspark/sql/tests/test_types.py
index 218cfc413db..b1609417a0c 100644
--- a/python/pyspark/sql/tests/test_types.py
+++ b/python/pyspark/sql/tests/test_types.py
@@ -38,6 +38,7 @@ from pyspark.sql.types import (
DayTimeIntervalType,
MapType,
StringType,
+ CharType,
VarcharType,
StructType,
StructField,
@@ -740,9 +741,12 @@ class TypesTests(ReusedSQLTestCase):
from pyspark.sql.types import _all_atomic_types, _parse_datatype_string
for k, t in _all_atomic_types.items():
- if k != "varchar":
+ if k != "varchar" and k != "char":
self.assertEqual(t(), _parse_datatype_string(k))
self.assertEqual(IntegerType(), _parse_datatype_string("int"))
+ self.assertEqual(CharType(1), _parse_datatype_string("char(1)"))
+ self.assertEqual(CharType(10), _parse_datatype_string("char( 10 )"))
+ self.assertEqual(CharType(11), _parse_datatype_string("char( 11)"))
self.assertEqual(VarcharType(1), _parse_datatype_string("varchar(1)"))
self.assertEqual(VarcharType(10), _parse_datatype_string("varchar( 10
)"))
self.assertEqual(VarcharType(11), _parse_datatype_string("varchar(
11)"))
@@ -1033,6 +1037,7 @@ class TypesTests(ReusedSQLTestCase):
instances = [
NullType(),
StringType(),
+ CharType(10),
VarcharType(10),
BinaryType(),
BooleanType(),
@@ -1138,6 +1143,15 @@ class DataTypeTests(unittest.TestCase):
t3 = DecimalType(8)
self.assertNotEqual(t2, t3)
+ def test_char_type(self):
+ v1 = CharType(10)
+ v2 = CharType(20)
+ self.assertTrue(v2 is not v1)
+ self.assertNotEqual(v1, v2)
+ v3 = CharType(10)
+ self.assertEqual(v1, v3)
+ self.assertFalse(v1 is v3)
+
def test_varchar_type(self):
v1 = VarcharType(10)
v2 = VarcharType(20)
@@ -1221,14 +1235,18 @@ class DataTypeVerificationTests(unittest.TestCase):
success_spec = [
# String
("", StringType()),
- ("", StringType()),
(1, StringType()),
(1.0, StringType()),
([], StringType()),
({}, StringType()),
+ # Char
+ ("", CharType(10)),
+ (1, CharType(10)),
+ (1.0, CharType(10)),
+ ([], CharType(10)),
+ ({}, CharType(10)),
# Varchar
("", VarcharType(10)),
- ("", VarcharType(10)),
(1, VarcharType(10)),
(1.0, VarcharType(10)),
([], VarcharType(10)),
@@ -1289,6 +1307,8 @@ class DataTypeVerificationTests(unittest.TestCase):
failure_spec = [
# String (match anything but None)
(None, StringType(), ValueError),
+ # CharType (match anything but None)
+ (None, CharType(10), ValueError),
# VarcharType (match anything but None)
(None, VarcharType(10), ValueError),
# UDT
diff --git a/python/pyspark/sql/types.py b/python/pyspark/sql/types.py
index 7ab8f7c9c2d..e034ff75e10 100644
--- a/python/pyspark/sql/types.py
+++ b/python/pyspark/sql/types.py
@@ -56,6 +56,7 @@ U = TypeVar("U")
__all__ = [
"DataType",
"NullType",
+ "CharType",
"StringType",
"VarcharType",
"BinaryType",
@@ -182,6 +183,28 @@ class StringType(AtomicType, metaclass=DataTypeSingleton):
pass
+class CharType(AtomicType):
+ """Char data type
+
+ Parameters
+ ----------
+ length : int
+ the length limitation.
+ """
+
+ def __init__(self, length: int):
+ self.length = length
+
+ def simpleString(self) -> str:
+ return "char(%d)" % (self.length)
+
+ def jsonValue(self) -> str:
+ return "char(%d)" % (self.length)
+
+ def __repr__(self) -> str:
+ return "CharType(%d)" % (self.length)
+
+
class VarcharType(AtomicType):
"""Varchar data type
@@ -648,6 +671,10 @@ class StructType(DataType):
>>> struct2 = StructType([StructField("f1", StringType(), True)])
>>> struct1 == struct2
True
+ >>> struct1 = StructType([StructField("f1", CharType(10), True)])
+ >>> struct2 = StructType([StructField("f1", CharType(10), True)])
+ >>> struct1 == struct2
+ True
>>> struct1 = StructType([StructField("f1", VarcharType(10), True)])
>>> struct2 = StructType([StructField("f1", VarcharType(10), True)])
>>> struct1 == struct2
@@ -971,6 +998,7 @@ class UserDefinedType(DataType):
_atomic_types: List[Type[DataType]] = [
StringType,
+ CharType,
VarcharType,
BinaryType,
BooleanType,
@@ -993,6 +1021,7 @@ _all_complex_types: Dict[str, Type[Union[ArrayType,
MapType, StructType]]] = dic
(v.typeName(), v) for v in _complex_types
)
+_LENGTH_CHAR = re.compile(r"char\(\s*(\d+)\s*\)")
_LENGTH_VARCHAR = re.compile(r"varchar\(\s*(\d+)\s*\)")
_FIXED_DECIMAL = re.compile(r"decimal\(\s*(\d+)\s*,\s*(-?\d+)\s*\)")
_INTERVAL_DAYTIME = re.compile(r"interval (day|hour|minute|second)( to
(day|hour|minute|second))?")
@@ -1015,6 +1044,8 @@ def _parse_datatype_string(s: str) -> DataType:
StructType([StructField('a', ByteType(), True), StructField('b',
DecimalType(16,8), True)])
>>> _parse_datatype_string("a DOUBLE, b STRING")
StructType([StructField('a', DoubleType(), True), StructField('b',
StringType(), True)])
+ >>> _parse_datatype_string("a DOUBLE, b CHAR( 50 )")
+ StructType([StructField('a', DoubleType(), True), StructField('b',
CharType(50), True)])
>>> _parse_datatype_string("a DOUBLE, b VARCHAR( 50 )")
StructType([StructField('a', DoubleType(), True), StructField('b',
VarcharType(50), True)])
>>> _parse_datatype_string("a: array< short>")
@@ -1085,7 +1116,7 @@ def _parse_datatype_json_string(json_string: str) ->
DataType:
... python_datatype =
_parse_datatype_json_string(scala_datatype.json())
... assert datatype == python_datatype
>>> for cls in _all_atomic_types.values():
- ... if cls is not VarcharType:
+ ... if cls is not VarcharType and cls is not CharType:
... check_datatype(cls())
... else:
... check_datatype(cls(1))
@@ -1112,6 +1143,7 @@ def _parse_datatype_json_string(json_string: str) ->
DataType:
... StructField("simpleMap", simple_maptype, True),
... StructField("simpleStruct", simple_structtype, True),
... StructField("boolean", BooleanType(), False),
+ ... StructField("chars", CharType(10), False),
... StructField("words", VarcharType(10), False),
... StructField("withMeta", DoubleType(), False, {"name": "age"})])
>>> check_datatype(complex_structtype)
@@ -1145,6 +1177,9 @@ def _parse_datatype_json_value(json_value: Union[dict,
str]) -> DataType:
if first_field is not None and second_field is None:
return DayTimeIntervalType(first_field)
return DayTimeIntervalType(first_field, second_field)
+ elif _LENGTH_CHAR.match(json_value):
+ m = _LENGTH_CHAR.match(json_value)
+ return CharType(int(m.group(1))) # type: ignore[union-attr]
elif _LENGTH_VARCHAR.match(json_value):
m = _LENGTH_VARCHAR.match(json_value)
return VarcharType(int(m.group(1))) # type: ignore[union-attr]
@@ -1586,6 +1621,7 @@ _acceptable_types = {
DoubleType: (float,),
DecimalType: (decimal.Decimal,),
StringType: (str,),
+ CharType: (str,),
VarcharType: (str,),
BinaryType: (bytearray, bytes),
DateType: (datetime.date, datetime.datetime),
@@ -1697,8 +1733,8 @@ def _make_type_verifier(
new_msg("%s can not accept object %r in type %s" % (dataType,
obj, type(obj)))
)
- if isinstance(dataType, (StringType, VarcharType)):
- # StringType and VarcharType can work with any types
+ if isinstance(dataType, (StringType, CharType, VarcharType)):
+ # StringType, CharType and VarcharType can work with any types
def verify_value(obj: Any) -> None:
pass
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