44b7931936
### What changes were proposed in this pull request? This PR corrects some exception type when the function input params are failed to validate due to TypeError. In order to convenient to review, there are 3 commits in this PR: - Standardize input validation error type on sql - Standardize input validation error type on ml - Standardize input validation error type on pandas ### Why are the changes needed? As suggestion from Python exception doc [1]: "Raised when an operation or function is applied to an object of inappropriate type.", but there are many Value error are raised in some pyspark code, this patch fix them. [1] https://docs.python.org/3/library/exceptions.html#TypeError Note that: this patch only addresses the exsiting some wrong raise type for input validation, the input validation decorator/framework which mentioned in [SPARK-35176](https://issues.apache.org/jira/browse/SPARK-35176), would be submited in a speparated patch. ### Does this PR introduce _any_ user-facing change? Yes, code can raise the right TypeError instead of ValueError. ### How was this patch tested? Existing test case and UT Closes #32368 from Yikun/SPARK-35176. Authored-by: Yikun Jiang <yikunkero@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
91 lines
3.2 KiB
Python
91 lines
3.2 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import unittest
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from pyspark.sql.types import DoubleType, IntegerType
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from pyspark.testing.mlutils import MockDataset, MockEstimator, MockUnaryTransformer, \
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MockTransformer, SparkSessionTestCase
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class TransformerTests(unittest.TestCase):
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def test_transform_invalid_type(self):
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transformer = MockTransformer()
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data = MockDataset()
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self.assertRaises(TypeError, transformer.transform, data, "")
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class UnaryTransformerTests(SparkSessionTestCase):
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def test_unary_transformer_validate_input_type(self):
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shiftVal = 3
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transformer = MockUnaryTransformer(shiftVal=shiftVal) \
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.setInputCol("input").setOutputCol("output")
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# should not raise any errors
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transformer.validateInputType(DoubleType())
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with self.assertRaises(TypeError):
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# passing the wrong input type should raise an error
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transformer.validateInputType(IntegerType())
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def test_unary_transformer_transform(self):
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shiftVal = 3
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transformer = MockUnaryTransformer(shiftVal=shiftVal) \
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.setInputCol("input").setOutputCol("output")
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df = self.spark.range(0, 10).toDF('input')
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df = df.withColumn("input", df.input.cast(dataType="double"))
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transformed_df = transformer.transform(df)
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results = transformed_df.select("input", "output").collect()
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for res in results:
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self.assertEqual(res.input + shiftVal, res.output)
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class EstimatorTest(unittest.TestCase):
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def setUp(self):
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self.estimator = MockEstimator()
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self.data = MockDataset()
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def test_fit_invalid_params(self):
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invalid_type_parms = ""
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self.assertRaises(TypeError, self.estimator.fit, self.data, invalid_type_parms)
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def testDefaultFitMultiple(self):
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N = 4
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params = [{self.estimator.fake: i} for i in range(N)]
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modelIter = self.estimator.fitMultiple(self.data, params)
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indexList = []
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for index, model in modelIter:
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self.assertEqual(model.getFake(), index)
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indexList.append(index)
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self.assertEqual(sorted(indexList), list(range(N)))
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if __name__ == "__main__":
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from pyspark.ml.tests.test_base import * # noqa: F401
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try:
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import xmlrunner # type: ignore[import]
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports', verbosity=2)
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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