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[SPARK-46500][PS][TESTS] Reorganize
FrameParityPivotTests
### What changes were proposed in this pull request? Reorganize `FrameParityPivotTests`: break `test_pivot_table` into mutiple tests ### Why are the changes needed? this test is slow ``` Starting test(python3.9): pyspark.pandas.tests.connect.computation.test_parity_pivot (temp output: /__w/spark/spark/python/target/5f37e442-9037-47cc-8c6b-e9a273299d0d/python3.9__pyspark.pandas.tests.connect.computation.test_parity_pivot__ozvdx_ay.log) Finished test(python3.9): pyspark.pandas.tests.connect.computation.test_parity_pivot (524s) ``` ### Does this PR introduce _any_ user-facing change? no, test only ### How was this patch tested? ci ### Was this patch authored or co-authored using generative AI tooling? no Closes apache#44478 from zhengruifeng/ps_test_pivot_multi. Authored-by: Ruifeng Zheng <[email protected]> Signed-off-by: Ruifeng Zheng <[email protected]>
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93 changes: 93 additions & 0 deletions
93
python/pyspark/pandas/tests/computation/test_pivot_table.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,93 @@ | ||
| # | ||
| # 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 | ||
|
|
||
| import numpy as np | ||
| import pandas as pd | ||
|
|
||
| from pyspark import pandas as ps | ||
| from pyspark.testing.pandasutils import ComparisonTestBase | ||
| from pyspark.testing.sqlutils import SQLTestUtils | ||
|
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|
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| class PivotTableMixin: | ||
| def test_pivot_table(self): | ||
| pdf = pd.DataFrame( | ||
| { | ||
| "a": [4, 2, 3, 4, 8, 6], | ||
| "b": [1, 2, 2, 4, 2, 4], | ||
| "e": [10, 20, 20, 40, 20, 40], | ||
| "c": [1, 2, 9, 4, 7, 4], | ||
| "d": [-1, -2, -3, -4, -5, -6], | ||
| }, | ||
| index=np.random.rand(6), | ||
| ) | ||
| psdf = ps.from_pandas(pdf) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table(columns="a", values="b").sort_index(), | ||
| pdf.pivot_table(columns="a", values="b").sort_index(), | ||
| almost=True, | ||
| ) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table(index=["c"], columns="a", values="b").sort_index(), | ||
| pdf.pivot_table(index=["c"], columns="a", values="b").sort_index(), | ||
| almost=True, | ||
| ) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table(index=["c"], columns="a", values="b", aggfunc="sum").sort_index(), | ||
| pdf.pivot_table(index=["c"], columns="a", values="b", aggfunc="sum").sort_index(), | ||
| almost=True, | ||
| ) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table(index=["c"], columns="a", values=["b"], aggfunc="sum").sort_index(), | ||
| pdf.pivot_table(index=["c"], columns="a", values=["b"], aggfunc="sum").sort_index(), | ||
| almost=True, | ||
| ) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e"], aggfunc="sum" | ||
| ).sort_index(), | ||
| pdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e"], aggfunc="sum" | ||
| ).sort_index(), | ||
| almost=True, | ||
| ) | ||
|
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|
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| class PivotTableTests( | ||
| PivotTableMixin, | ||
| ComparisonTestBase, | ||
| SQLTestUtils, | ||
| ): | ||
| pass | ||
|
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|
|
||
| if __name__ == "__main__": | ||
| from pyspark.pandas.tests.computation.test_pivot_table import * # noqa: F401 | ||
|
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| try: | ||
| import xmlrunner | ||
|
|
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| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) | ||
| except ImportError: | ||
| testRunner = None | ||
| unittest.main(testRunner=testRunner, verbosity=2) |
93 changes: 93 additions & 0 deletions
93
python/pyspark/pandas/tests/computation/test_pivot_table_adv.py
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,93 @@ | ||
| # | ||
| # 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 | ||
|
|
||
| import numpy as np | ||
| import pandas as pd | ||
|
|
||
| from pyspark import pandas as ps | ||
| from pyspark.testing.pandasutils import ComparisonTestBase | ||
| from pyspark.testing.sqlutils import SQLTestUtils | ||
|
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||
|
|
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| class PivotTableAdvMixin: | ||
| def test_pivot_table(self): | ||
| pdf = pd.DataFrame( | ||
| { | ||
| "a": [4, 2, 3, 4, 8, 6], | ||
| "b": [1, 2, 2, 4, 2, 4], | ||
| "e": [10, 20, 20, 40, 20, 40], | ||
| "c": [1, 2, 9, 4, 7, 4], | ||
| "d": [-1, -2, -3, -4, -5, -6], | ||
| }, | ||
| index=np.random.rand(6), | ||
| ) | ||
| psdf = ps.from_pandas(pdf) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e", "d"], aggfunc="sum" | ||
| ).sort_index(), | ||
| pdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e", "d"], aggfunc="sum" | ||
| ).sort_index(), | ||
| almost=True, | ||
| ) | ||
|
|
||
| self.assert_eq( | ||
| psdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e"], aggfunc={"b": "mean", "e": "sum"} | ||
| ).sort_index(), | ||
| pdf.pivot_table( | ||
| index=["c"], columns="a", values=["b", "e"], aggfunc={"b": "mean", "e": "sum"} | ||
| ).sort_index(), | ||
| almost=True, | ||
| ) | ||
|
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||
| self.assert_eq( | ||
| psdf.pivot_table(index=["e", "c"], columns="a", values="b").sort_index(), | ||
| pdf.pivot_table(index=["e", "c"], columns="a", values="b").sort_index(), | ||
| almost=True, | ||
| ) | ||
|
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||
| self.assert_eq( | ||
| psdf.pivot_table( | ||
| index=["e", "c"], columns="a", values="b", fill_value=999 | ||
| ).sort_index(), | ||
| pdf.pivot_table(index=["e", "c"], columns="a", values="b", fill_value=999).sort_index(), | ||
| almost=True, | ||
| ) | ||
|
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|
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| class PivotTableAdvTests( | ||
| PivotTableAdvMixin, | ||
| ComparisonTestBase, | ||
| SQLTestUtils, | ||
| ): | ||
| pass | ||
|
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|
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| if __name__ == "__main__": | ||
| from pyspark.pandas.tests.computation.test_pivot_table_adv import * # noqa: F401 | ||
|
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| try: | ||
| import xmlrunner | ||
|
|
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| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) | ||
| except ImportError: | ||
| testRunner = None | ||
| unittest.main(testRunner=testRunner, verbosity=2) |
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