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>
235 lines
9 KiB
Python
235 lines
9 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 math
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import sys
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import unittest
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from pyspark import serializers
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from pyspark.serializers import CloudPickleSerializer, CompressedSerializer, \
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AutoBatchedSerializer, BatchedSerializer, AutoSerializer, NoOpSerializer, PairDeserializer, \
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FlattenedValuesSerializer, CartesianDeserializer, PickleSerializer, UTF8Deserializer, \
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MarshalSerializer
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from pyspark.testing.utils import PySparkTestCase, read_int, write_int, ByteArrayOutput, \
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have_numpy, have_scipy
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class SerializationTestCase(unittest.TestCase):
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def test_namedtuple(self):
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from collections import namedtuple
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from pickle import dumps, loads
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P = namedtuple("P", "x y")
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p1 = P(1, 3)
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p2 = loads(dumps(p1, 2))
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self.assertEqual(p1, p2)
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from pyspark.cloudpickle import dumps
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P2 = loads(dumps(P))
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p3 = P2(1, 3)
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self.assertEqual(p1, p3)
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def test_itemgetter(self):
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from operator import itemgetter
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ser = CloudPickleSerializer()
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d = range(10)
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getter = itemgetter(1)
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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getter = itemgetter(0, 3)
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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def test_function_module_name(self):
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ser = CloudPickleSerializer()
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func = lambda x: x
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func2 = ser.loads(ser.dumps(func))
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self.assertEqual(func.__module__, func2.__module__)
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def test_attrgetter(self):
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from operator import attrgetter
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ser = CloudPickleSerializer()
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class C(object):
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def __getattr__(self, item):
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return item
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d = C()
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getter = attrgetter("a")
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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getter = attrgetter("a", "b")
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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d.e = C()
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getter = attrgetter("e.a")
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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getter = attrgetter("e.a", "e.b")
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getter2 = ser.loads(ser.dumps(getter))
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self.assertEqual(getter(d), getter2(d))
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# Regression test for SPARK-3415
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def test_pickling_file_handles(self):
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# to be corrected with SPARK-11160
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try:
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import xmlrunner # type: ignore[import] # noqa: F401
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except ImportError:
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ser = CloudPickleSerializer()
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out1 = sys.stderr
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out2 = ser.loads(ser.dumps(out1))
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self.assertEqual(out1, out2)
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def test_func_globals(self):
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class Unpicklable(object):
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def __reduce__(self):
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raise Exception("not picklable")
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global exit
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exit = Unpicklable()
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ser = CloudPickleSerializer()
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self.assertRaises(Exception, lambda: ser.dumps(exit))
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def foo():
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sys.exit(0)
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self.assertTrue("exit" in foo.__code__.co_names)
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ser.dumps(foo)
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def test_compressed_serializer(self):
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ser = CompressedSerializer(PickleSerializer())
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from io import BytesIO as StringIO
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io = StringIO()
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ser.dump_stream(["abc", u"123", range(5)], io)
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io.seek(0)
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self.assertEqual(["abc", u"123", range(5)], list(ser.load_stream(io)))
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ser.dump_stream(range(1000), io)
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io.seek(0)
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self.assertEqual(["abc", u"123", range(5)] + list(range(1000)), list(ser.load_stream(io)))
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io.close()
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def test_hash_serializer(self):
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hash(NoOpSerializer())
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hash(UTF8Deserializer())
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hash(PickleSerializer())
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hash(MarshalSerializer())
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hash(AutoSerializer())
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hash(BatchedSerializer(PickleSerializer()))
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hash(AutoBatchedSerializer(MarshalSerializer()))
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hash(PairDeserializer(NoOpSerializer(), UTF8Deserializer()))
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hash(CartesianDeserializer(NoOpSerializer(), UTF8Deserializer()))
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hash(CompressedSerializer(PickleSerializer()))
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hash(FlattenedValuesSerializer(PickleSerializer()))
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@unittest.skipIf(not have_scipy, "SciPy not installed")
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class SciPyTests(PySparkTestCase):
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"""General PySpark tests that depend on scipy """
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def test_serialize(self):
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from scipy.special import gammaln
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x = range(1, 5)
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expected = list(map(gammaln, x))
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observed = self.sc.parallelize(x).map(gammaln).collect()
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self.assertEqual(expected, observed)
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@unittest.skipIf(not have_numpy, "NumPy not installed")
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class NumPyTests(PySparkTestCase):
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"""General PySpark tests that depend on numpy """
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def test_statcounter_array(self):
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import numpy as np
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x = self.sc.parallelize([np.array([1.0, 1.0]), np.array([2.0, 2.0]), np.array([3.0, 3.0])])
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s = x.stats()
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self.assertSequenceEqual([2.0, 2.0], s.mean().tolist())
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self.assertSequenceEqual([1.0, 1.0], s.min().tolist())
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self.assertSequenceEqual([3.0, 3.0], s.max().tolist())
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self.assertSequenceEqual([1.0, 1.0], s.sampleStdev().tolist())
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stats_dict = s.asDict()
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self.assertEqual(3, stats_dict['count'])
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self.assertSequenceEqual([2.0, 2.0], stats_dict['mean'].tolist())
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self.assertSequenceEqual([1.0, 1.0], stats_dict['min'].tolist())
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self.assertSequenceEqual([3.0, 3.0], stats_dict['max'].tolist())
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self.assertSequenceEqual([6.0, 6.0], stats_dict['sum'].tolist())
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self.assertSequenceEqual([1.0, 1.0], stats_dict['stdev'].tolist())
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self.assertSequenceEqual([1.0, 1.0], stats_dict['variance'].tolist())
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stats_sample_dict = s.asDict(sample=True)
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self.assertEqual(3, stats_dict['count'])
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self.assertSequenceEqual([2.0, 2.0], stats_sample_dict['mean'].tolist())
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self.assertSequenceEqual([1.0, 1.0], stats_sample_dict['min'].tolist())
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self.assertSequenceEqual([3.0, 3.0], stats_sample_dict['max'].tolist())
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self.assertSequenceEqual([6.0, 6.0], stats_sample_dict['sum'].tolist())
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self.assertSequenceEqual(
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[0.816496580927726, 0.816496580927726], stats_sample_dict['stdev'].tolist())
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self.assertSequenceEqual(
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[0.6666666666666666, 0.6666666666666666], stats_sample_dict['variance'].tolist())
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class SerializersTest(unittest.TestCase):
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def test_chunked_stream(self):
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original_bytes = bytearray(range(100))
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for data_length in [1, 10, 100]:
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for buffer_length in [1, 2, 3, 5, 20, 99, 100, 101, 500]:
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dest = ByteArrayOutput()
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stream_out = serializers.ChunkedStream(dest, buffer_length)
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stream_out.write(original_bytes[:data_length])
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stream_out.close()
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num_chunks = int(math.ceil(float(data_length) / buffer_length))
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# length for each chunk, and a final -1 at the very end
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exp_size = (num_chunks + 1) * 4 + data_length
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self.assertEqual(len(dest.buffer), exp_size)
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dest_pos = 0
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data_pos = 0
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for chunk_idx in range(num_chunks):
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chunk_length = read_int(dest.buffer[dest_pos:(dest_pos + 4)])
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if chunk_idx == num_chunks - 1:
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exp_length = data_length % buffer_length
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if exp_length == 0:
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exp_length = buffer_length
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else:
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exp_length = buffer_length
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self.assertEqual(chunk_length, exp_length)
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dest_pos += 4
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dest_chunk = dest.buffer[dest_pos:dest_pos + chunk_length]
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orig_chunk = original_bytes[data_pos:data_pos + chunk_length]
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self.assertEqual(dest_chunk, orig_chunk)
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dest_pos += chunk_length
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data_pos += chunk_length
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# ends with a -1
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self.assertEqual(dest.buffer[-4:], write_int(-1))
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if __name__ == "__main__":
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from pyspark.tests.test_serializers 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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