spark-instrumented-optimizer/python/pyspark/testing/sqlutils.py
zero323 31a16fbb40 [SPARK-32714][PYTHON] Initial pyspark-stubs port
### What changes were proposed in this pull request?

This PR proposes migration of [`pyspark-stubs`](https://github.com/zero323/pyspark-stubs) into Spark codebase.

### Why are the changes needed?

### Does this PR introduce _any_ user-facing change?

Yes. This PR adds type annotations directly to Spark source.

This can impact interaction with development tools for users, which haven't used `pyspark-stubs`.

### How was this patch tested?

- [x] MyPy tests of the PySpark source
    ```
    mypy --no-incremental --config python/mypy.ini python/pyspark
    ```
- [x] MyPy tests of Spark examples
    ```
   MYPYPATH=python/ mypy --no-incremental --config python/mypy.ini examples/src/main/python/ml examples/src/main/python/sql examples/src/main/python/sql/streaming
    ```
- [x] Existing Flake8 linter

- [x] Existing unit tests

Tested against:

- `mypy==0.790+dev.e959952d9001e9713d329a2f9b196705b028f894`
- `mypy==0.782`

Closes #29591 from zero323/SPARK-32681.

Authored-by: zero323 <mszymkiewicz@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>
2020-09-24 14:15:36 +09:00

262 lines
7.6 KiB
Python

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements. See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import datetime
import os
import shutil
import tempfile
from contextlib import contextmanager
from pyspark.sql import SparkSession
from pyspark.sql.types import ArrayType, DoubleType, UserDefinedType, Row
from pyspark.testing.utils import ReusedPySparkTestCase
pandas_requirement_message = None
try:
from pyspark.sql.pandas.utils import require_minimum_pandas_version
require_minimum_pandas_version()
except ImportError as e:
# If Pandas version requirement is not satisfied, skip related tests.
pandas_requirement_message = str(e)
pyarrow_requirement_message = None
try:
from pyspark.sql.pandas.utils import require_minimum_pyarrow_version
require_minimum_pyarrow_version()
except ImportError as e:
# If Arrow version requirement is not satisfied, skip related tests.
pyarrow_requirement_message = str(e)
test_not_compiled_message = None
try:
from pyspark.sql.utils import require_test_compiled
require_test_compiled()
except Exception as e:
test_not_compiled_message = str(e)
have_pandas = pandas_requirement_message is None
have_pyarrow = pyarrow_requirement_message is None
test_compiled = test_not_compiled_message is None
class UTCOffsetTimezone(datetime.tzinfo):
"""
Specifies timezone in UTC offset
"""
def __init__(self, offset=0):
self.ZERO = datetime.timedelta(hours=offset)
def utcoffset(self, dt):
return self.ZERO
def dst(self, dt):
return self.ZERO
class ExamplePointUDT(UserDefinedType):
"""
User-defined type (UDT) for ExamplePoint.
"""
@classmethod
def sqlType(self):
return ArrayType(DoubleType(), False)
@classmethod
def module(cls):
return 'pyspark.sql.tests'
@classmethod
def scalaUDT(cls):
return 'org.apache.spark.sql.test.ExamplePointUDT'
def serialize(self, obj):
return [obj.x, obj.y]
def deserialize(self, datum):
return ExamplePoint(datum[0], datum[1])
class ExamplePoint:
"""
An example class to demonstrate UDT in Scala, Java, and Python.
"""
__UDT__ = ExamplePointUDT()
def __init__(self, x, y):
self.x = x
self.y = y
def __repr__(self):
return "ExamplePoint(%s,%s)" % (self.x, self.y)
def __str__(self):
return "(%s,%s)" % (self.x, self.y)
def __eq__(self, other):
return isinstance(other, self.__class__) and \
other.x == self.x and other.y == self.y
class PythonOnlyUDT(UserDefinedType):
"""
User-defined type (UDT) for ExamplePoint.
"""
@classmethod
def sqlType(self):
return ArrayType(DoubleType(), False)
@classmethod
def module(cls):
return '__main__'
def serialize(self, obj):
return [obj.x, obj.y]
def deserialize(self, datum):
return PythonOnlyPoint(datum[0], datum[1])
@staticmethod
def foo():
pass
@property
def props(self):
return {}
class PythonOnlyPoint(ExamplePoint):
"""
An example class to demonstrate UDT in only Python
"""
__UDT__ = PythonOnlyUDT() # type: ignore
class MyObject(object):
def __init__(self, key, value):
self.key = key
self.value = value
class SQLTestUtils(object):
"""
This util assumes the instance of this to have 'spark' attribute, having a spark session.
It is usually used with 'ReusedSQLTestCase' class but can be used if you feel sure the
the implementation of this class has 'spark' attribute.
"""
@contextmanager
def sql_conf(self, pairs):
"""
A convenient context manager to test some configuration specific logic. This sets
`value` to the configuration `key` and then restores it back when it exits.
"""
assert isinstance(pairs, dict), "pairs should be a dictionary."
assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."
keys = pairs.keys()
new_values = pairs.values()
old_values = [self.spark.conf.get(key, None) for key in keys]
for key, new_value in zip(keys, new_values):
self.spark.conf.set(key, new_value)
try:
yield
finally:
for key, old_value in zip(keys, old_values):
if old_value is None:
self.spark.conf.unset(key)
else:
self.spark.conf.set(key, old_value)
@contextmanager
def database(self, *databases):
"""
A convenient context manager to test with some specific databases. This drops the given
databases if it exists and sets current database to "default" when it exits.
"""
assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."
try:
yield
finally:
for db in databases:
self.spark.sql("DROP DATABASE IF EXISTS %s CASCADE" % db)
self.spark.catalog.setCurrentDatabase("default")
@contextmanager
def table(self, *tables):
"""
A convenient context manager to test with some specific tables. This drops the given tables
if it exists.
"""
assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."
try:
yield
finally:
for t in tables:
self.spark.sql("DROP TABLE IF EXISTS %s" % t)
@contextmanager
def tempView(self, *views):
"""
A convenient context manager to test with some specific views. This drops the given views
if it exists.
"""
assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."
try:
yield
finally:
for v in views:
self.spark.catalog.dropTempView(v)
@contextmanager
def function(self, *functions):
"""
A convenient context manager to test with some specific functions. This drops the given
functions if it exists.
"""
assert hasattr(self, "spark"), "it should have 'spark' attribute, having a spark session."
try:
yield
finally:
for f in functions:
self.spark.sql("DROP FUNCTION IF EXISTS %s" % f)
class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils):
@classmethod
def setUpClass(cls):
super(ReusedSQLTestCase, cls).setUpClass()
cls.spark = SparkSession(cls.sc)
cls.tempdir = tempfile.NamedTemporaryFile(delete=False)
os.unlink(cls.tempdir.name)
cls.testData = [Row(key=i, value=str(i)) for i in range(100)]
cls.df = cls.spark.createDataFrame(cls.testData)
@classmethod
def tearDownClass(cls):
super(ReusedSQLTestCase, cls).tearDownClass()
cls.spark.stop()
shutil.rmtree(cls.tempdir.name, ignore_errors=True)