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>
255 lines
8.7 KiB
Python
255 lines
8.7 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.functions import array, explode, col, lit, udf, pandas_udf
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from pyspark.sql.types import DoubleType, StructType, StructField, Row
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from pyspark.testing.sqlutils import ReusedSQLTestCase, have_pandas, have_pyarrow, \
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pandas_requirement_message, pyarrow_requirement_message
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from pyspark.testing.utils import QuietTest
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if have_pandas:
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import pandas as pd
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from pandas.util.testing import assert_frame_equal
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if have_pyarrow:
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import pyarrow as pa # noqa: F401
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@unittest.skipIf(
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not have_pandas or not have_pyarrow,
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pandas_requirement_message or pyarrow_requirement_message) # type: ignore[arg-type]
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class CogroupedMapInPandasTests(ReusedSQLTestCase):
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@property
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def data1(self):
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return self.spark.range(10).toDF('id') \
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.withColumn("ks", array([lit(i) for i in range(20, 30)])) \
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.withColumn("k", explode(col('ks')))\
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.withColumn("v", col('k') * 10)\
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.drop('ks')
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@property
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def data2(self):
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return self.spark.range(10).toDF('id') \
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.withColumn("ks", array([lit(i) for i in range(20, 30)])) \
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.withColumn("k", explode(col('ks'))) \
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.withColumn("v2", col('k') * 100) \
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.drop('ks')
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def test_simple(self):
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self._test_merge(self.data1, self.data2)
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def test_left_group_empty(self):
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left = self.data1.where(col("id") % 2 == 0)
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self._test_merge(left, self.data2)
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def test_right_group_empty(self):
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right = self.data2.where(col("id") % 2 == 0)
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self._test_merge(self.data1, right)
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def test_different_schemas(self):
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right = self.data2.withColumn('v3', lit('a'))
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self._test_merge(self.data1, right, 'id long, k int, v int, v2 int, v3 string')
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def test_complex_group_by(self):
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left = pd.DataFrame.from_dict({
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'id': [1, 2, 3],
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'k': [5, 6, 7],
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'v': [9, 10, 11]
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})
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right = pd.DataFrame.from_dict({
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'id': [11, 12, 13],
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'k': [5, 6, 7],
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'v2': [90, 100, 110]
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})
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left_gdf = self.spark\
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.createDataFrame(left)\
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.groupby(col('id') % 2 == 0)
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right_gdf = self.spark \
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.createDataFrame(right) \
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.groupby(col('id') % 2 == 0)
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def merge_pandas(l, r):
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return pd.merge(l[['k', 'v']], r[['k', 'v2']], on=['k'])
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result = left_gdf \
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.cogroup(right_gdf) \
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.applyInPandas(merge_pandas, 'k long, v long, v2 long') \
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.sort(['k']) \
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.toPandas()
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expected = pd.DataFrame.from_dict({
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'k': [5, 6, 7],
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'v': [9, 10, 11],
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'v2': [90, 100, 110]
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})
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assert_frame_equal(expected, result)
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def test_empty_group_by(self):
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left = self.data1
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right = self.data2
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def merge_pandas(l, r):
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return pd.merge(l, r, on=['id', 'k'])
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result = left.groupby().cogroup(right.groupby())\
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.applyInPandas(merge_pandas, 'id long, k int, v int, v2 int') \
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.sort(['id', 'k']) \
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.toPandas()
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left = left.toPandas()
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right = right.toPandas()
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expected = pd \
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.merge(left, right, on=['id', 'k']) \
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.sort_values(by=['id', 'k'])
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assert_frame_equal(expected, result)
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def test_mixed_scalar_udfs_followed_by_cogrouby_apply(self):
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df = self.spark.range(0, 10).toDF('v1')
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df = df.withColumn('v2', udf(lambda x: x + 1, 'int')(df['v1'])) \
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.withColumn('v3', pandas_udf(lambda x: x + 2, 'int')(df['v1']))
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result = df.groupby().cogroup(df.groupby()) \
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.applyInPandas(lambda x, y: pd.DataFrame([(x.sum().sum(), y.sum().sum())]),
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'sum1 int, sum2 int').collect()
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self.assertEquals(result[0]['sum1'], 165)
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self.assertEquals(result[0]['sum2'], 165)
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def test_with_key_left(self):
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self._test_with_key(self.data1, self.data1, isLeft=True)
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def test_with_key_right(self):
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self._test_with_key(self.data1, self.data1, isLeft=False)
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def test_with_key_left_group_empty(self):
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left = self.data1.where(col("id") % 2 == 0)
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self._test_with_key(left, self.data1, isLeft=True)
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def test_with_key_right_group_empty(self):
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right = self.data1.where(col("id") % 2 == 0)
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self._test_with_key(self.data1, right, isLeft=False)
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def test_with_key_complex(self):
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def left_assign_key(key, l, _):
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return l.assign(key=key[0])
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result = self.data1 \
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.groupby(col('id') % 2 == 0)\
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.cogroup(self.data2.groupby(col('id') % 2 == 0)) \
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.applyInPandas(left_assign_key, 'id long, k int, v int, key boolean') \
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.sort(['id', 'k']) \
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.toPandas()
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expected = self.data1.toPandas()
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expected = expected.assign(key=expected.id % 2 == 0)
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assert_frame_equal(expected, result)
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def test_wrong_return_type(self):
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# Test that we get a sensible exception invalid values passed to apply
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left = self.data1
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right = self.data2
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with QuietTest(self.sc):
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with self.assertRaisesRegexp(
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NotImplementedError,
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'Invalid return type.*MapType'):
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left.groupby('id').cogroup(right.groupby('id')).applyInPandas(
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lambda l, r: l, 'id long, v map<int, int>')
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def test_wrong_args(self):
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left = self.data1
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right = self.data2
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with self.assertRaisesRegexp(ValueError, 'Invalid function'):
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left.groupby('id').cogroup(right.groupby('id')) \
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.applyInPandas(lambda: 1, StructType([StructField("d", DoubleType())]))
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def test_case_insensitive_grouping_column(self):
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# SPARK-31915: case-insensitive grouping column should work.
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df1 = self.spark.createDataFrame([(1, 1)], ("column", "value"))
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row = df1.groupby("ColUmn").cogroup(
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df1.groupby("COLUMN")
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).applyInPandas(lambda r, l: r + l, "column long, value long").first()
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self.assertEquals(row.asDict(), Row(column=2, value=2).asDict())
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df2 = self.spark.createDataFrame([(1, 1)], ("column", "value"))
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row = df1.groupby("ColUmn").cogroup(
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df2.groupby("COLUMN")
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).applyInPandas(lambda r, l: r + l, "column long, value long").first()
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self.assertEquals(row.asDict(), Row(column=2, value=2).asDict())
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@staticmethod
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def _test_with_key(left, right, isLeft):
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def right_assign_key(key, l, r):
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return l.assign(key=key[0]) if isLeft else r.assign(key=key[0])
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result = left \
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.groupby('id') \
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.cogroup(right.groupby('id')) \
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.applyInPandas(right_assign_key, 'id long, k int, v int, key long') \
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.toPandas()
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expected = left.toPandas() if isLeft else right.toPandas()
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expected = expected.assign(key=expected.id)
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assert_frame_equal(expected, result)
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@staticmethod
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def _test_merge(left, right, output_schema='id long, k int, v int, v2 int'):
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def merge_pandas(l, r):
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return pd.merge(l, r, on=['id', 'k'])
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result = left \
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.groupby('id') \
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.cogroup(right.groupby('id')) \
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.applyInPandas(merge_pandas, output_schema)\
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.sort(['id', 'k']) \
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.toPandas()
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left = left.toPandas()
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right = right.toPandas()
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expected = pd \
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.merge(left, right, on=['id', 'k']) \
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.sort_values(by=['id', 'k'])
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assert_frame_equal(expected, result)
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if __name__ == "__main__":
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from pyspark.sql.tests.test_pandas_cogrouped_map 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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