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#
# 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 math
import sys
import unittest
from pyspark import serializers
from pyspark.serializers import CloudPickleSerializer, CompressedSerializer, \
AutoBatchedSerializer, BatchedSerializer, AutoSerializer, NoOpSerializer, PairDeserializer, \
FlattenedValuesSerializer, CartesianDeserializer, PickleSerializer, UTF8Deserializer, \
MarshalSerializer
from pyspark.testing.utils import PySparkTestCase, read_int, write_int, ByteArrayOutput, \
have_numpy, have_scipy
class SerializationTestCase(unittest.TestCase):
def test_namedtuple(self):
from collections import namedtuple
from pickle import dumps, loads
P = namedtuple("P", "x y")
p1 = P(1, 3)
p2 = loads(dumps(p1, 2))
self.assertEqual(p1, p2)
from pyspark.cloudpickle import dumps
P2 = loads(dumps(P))
p3 = P2(1, 3)
self.assertEqual(p1, p3)
def test_itemgetter(self):
from operator import itemgetter
ser = CloudPickleSerializer()
d = range(10)
getter = itemgetter(1)
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
getter = itemgetter(0, 3)
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
def test_function_module_name(self):
ser = CloudPickleSerializer()
59 ↛ exitline 59 didn't run the lambda on line 59 func = lambda x: x
func2 = ser.loads(ser.dumps(func))
self.assertEqual(func.__module__, func2.__module__)
def test_attrgetter(self):
from operator import attrgetter
ser = CloudPickleSerializer()
class C(object):
def __getattr__(self, item):
return item
d = C()
getter = attrgetter("a")
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
getter = attrgetter("a", "b")
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
d.e = C()
getter = attrgetter("e.a")
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
getter = attrgetter("e.a", "e.b")
getter2 = ser.loads(ser.dumps(getter))
self.assertEqual(getter(d), getter2(d))
# Regression test for SPARK-3415
def test_pickling_file_handles(self):
# to be corrected with SPARK-11160
try:
import xmlrunner # type: ignore[import] # noqa: F401
except ImportError:
ser = CloudPickleSerializer()
out1 = sys.stderr
out2 = ser.loads(ser.dumps(out1))
self.assertEqual(out1, out2)
def test_func_globals(self):
class Unpicklable(object):
def __reduce__(self):
raise RuntimeError("not picklable")
global exit
exit = Unpicklable()
ser = CloudPickleSerializer()
self.assertRaises(Exception, lambda: ser.dumps(exit))
def foo():
sys.exit(0)
self.assertTrue("exit" in foo.__code__.co_names)
ser.dumps(foo)
def test_compressed_serializer(self):
ser = CompressedSerializer(PickleSerializer())
from io import BytesIO as StringIO
io = StringIO()
ser.dump_stream(["abc", u"123", range(5)], io)
io.seek(0)
self.assertEqual(["abc", u"123", range(5)], list(ser.load_stream(io)))
ser.dump_stream(range(1000), io)
io.seek(0)
self.assertEqual(["abc", u"123", range(5)] + list(range(1000)), list(ser.load_stream(io)))
io.close()
def test_hash_serializer(self):
hash(NoOpSerializer())
hash(UTF8Deserializer())
hash(PickleSerializer())
hash(MarshalSerializer())
hash(AutoSerializer())
hash(BatchedSerializer(PickleSerializer()))
hash(AutoBatchedSerializer(MarshalSerializer()))
hash(PairDeserializer(NoOpSerializer(), UTF8Deserializer()))
hash(CartesianDeserializer(NoOpSerializer(), UTF8Deserializer()))
hash(CompressedSerializer(PickleSerializer()))
hash(FlattenedValuesSerializer(PickleSerializer()))
@unittest.skipIf(not have_scipy, "SciPy not installed")
class SciPyTests(PySparkTestCase):
"""General PySpark tests that depend on scipy """
def test_serialize(self):
from scipy.special import gammaln
x = range(1, 5)
expected = list(map(gammaln, x))
observed = self.sc.parallelize(x).map(gammaln).collect()
self.assertEqual(expected, observed)
@unittest.skipIf(not have_numpy, "NumPy not installed")
class NumPyTests(PySparkTestCase):
"""General PySpark tests that depend on numpy """
def test_statcounter_array(self):
import numpy as np
x = self.sc.parallelize([np.array([1.0, 1.0]), np.array([2.0, 2.0]), np.array([3.0, 3.0])])
s = x.stats()
self.assertSequenceEqual([2.0, 2.0], s.mean().tolist())
self.assertSequenceEqual([1.0, 1.0], s.min().tolist())
self.assertSequenceEqual([3.0, 3.0], s.max().tolist())
self.assertSequenceEqual([1.0, 1.0], s.sampleStdev().tolist())
stats_dict = s.asDict()
self.assertEqual(3, stats_dict['count'])
self.assertSequenceEqual([2.0, 2.0], stats_dict['mean'].tolist())
self.assertSequenceEqual([1.0, 1.0], stats_dict['min'].tolist())
self.assertSequenceEqual([3.0, 3.0], stats_dict['max'].tolist())
self.assertSequenceEqual([6.0, 6.0], stats_dict['sum'].tolist())
self.assertSequenceEqual([1.0, 1.0], stats_dict['stdev'].tolist())
self.assertSequenceEqual([1.0, 1.0], stats_dict['variance'].tolist())
stats_sample_dict = s.asDict(sample=True)
self.assertEqual(3, stats_dict['count'])
self.assertSequenceEqual([2.0, 2.0], stats_sample_dict['mean'].tolist())
self.assertSequenceEqual([1.0, 1.0], stats_sample_dict['min'].tolist())
self.assertSequenceEqual([3.0, 3.0], stats_sample_dict['max'].tolist())
self.assertSequenceEqual([6.0, 6.0], stats_sample_dict['sum'].tolist())
self.assertSequenceEqual(
[0.816496580927726, 0.816496580927726], stats_sample_dict['stdev'].tolist())
self.assertSequenceEqual(
[0.6666666666666666, 0.6666666666666666], stats_sample_dict['variance'].tolist())
class SerializersTest(unittest.TestCase):
def test_chunked_stream(self):
original_bytes = bytearray(range(100))
for data_length in [1, 10, 100]:
for buffer_length in [1, 2, 3, 5, 20, 99, 100, 101, 500]:
dest = ByteArrayOutput()
stream_out = serializers.ChunkedStream(dest, buffer_length)
stream_out.write(original_bytes[:data_length])
stream_out.close()
num_chunks = int(math.ceil(float(data_length) / buffer_length))
# length for each chunk, and a final -1 at the very end
exp_size = (num_chunks + 1) * 4 + data_length
self.assertEqual(len(dest.buffer), exp_size)
dest_pos = 0
data_pos = 0
for chunk_idx in range(num_chunks):
chunk_length = read_int(dest.buffer[dest_pos:(dest_pos + 4)])
if chunk_idx == num_chunks - 1:
exp_length = data_length % buffer_length
if exp_length == 0:
exp_length = buffer_length
else:
exp_length = buffer_length
self.assertEqual(chunk_length, exp_length)
dest_pos += 4
dest_chunk = dest.buffer[dest_pos:dest_pos + chunk_length]
orig_chunk = original_bytes[data_pos:data_pos + chunk_length]
self.assertEqual(dest_chunk, orig_chunk)
dest_pos += chunk_length
data_pos += chunk_length
# ends with a -1
self.assertEqual(dest.buffer[-4:], write_int(-1))
if __name__ == "__main__":
from pyspark.tests.test_serializers 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)
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