31a16fbb40
### 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>
78 lines
2.8 KiB
Python
78 lines
2.8 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 unittest
|
|
|
|
from pyspark.sql.types import DoubleType, IntegerType
|
|
from pyspark.testing.mlutils import MockDataset, MockEstimator, MockUnaryTransformer, \
|
|
SparkSessionTestCase
|
|
|
|
|
|
class UnaryTransformerTests(SparkSessionTestCase):
|
|
|
|
def test_unary_transformer_validate_input_type(self):
|
|
shiftVal = 3
|
|
transformer = MockUnaryTransformer(shiftVal=shiftVal) \
|
|
.setInputCol("input").setOutputCol("output")
|
|
|
|
# should not raise any errors
|
|
transformer.validateInputType(DoubleType())
|
|
|
|
with self.assertRaises(TypeError):
|
|
# passing the wrong input type should raise an error
|
|
transformer.validateInputType(IntegerType())
|
|
|
|
def test_unary_transformer_transform(self):
|
|
shiftVal = 3
|
|
transformer = MockUnaryTransformer(shiftVal=shiftVal) \
|
|
.setInputCol("input").setOutputCol("output")
|
|
|
|
df = self.spark.range(0, 10).toDF('input')
|
|
df = df.withColumn("input", df.input.cast(dataType="double"))
|
|
|
|
transformed_df = transformer.transform(df)
|
|
results = transformed_df.select("input", "output").collect()
|
|
|
|
for res in results:
|
|
self.assertEqual(res.input + shiftVal, res.output)
|
|
|
|
|
|
class EstimatorTest(unittest.TestCase):
|
|
|
|
def testDefaultFitMultiple(self):
|
|
N = 4
|
|
data = MockDataset()
|
|
estimator = MockEstimator()
|
|
params = [{estimator.fake: i} for i in range(N)]
|
|
modelIter = estimator.fitMultiple(data, params)
|
|
indexList = []
|
|
for index, model in modelIter:
|
|
self.assertEqual(model.getFake(), index)
|
|
indexList.append(index)
|
|
self.assertEqual(sorted(indexList), list(range(N)))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
from pyspark.ml.tests.test_base import * # noqa: F401
|
|
|
|
try:
|
|
import xmlrunner # type: ignore[import]
|
|
testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
|
|
except ImportError:
|
|
testRunner = None
|
|
unittest.main(testRunner=testRunner, verbosity=2)
|