spark-instrumented-optimizer/python/pyspark/streaming/tests/test_context.py
zero323 31a16fbb40 [SPARK-32714][PYTHON] Initial pyspark-stubs port
### 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>
2020-09-24 14:15:36 +09:00

186 lines
7.1 KiB
Python

#
# 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 os
import struct
import tempfile
import time
from pyspark.streaming import StreamingContext
from pyspark.testing.streamingutils import PySparkStreamingTestCase
class StreamingContextTests(PySparkStreamingTestCase):
duration = 0.1
setupCalled = False
def _add_input_stream(self):
inputs = [range(1, x) for x in range(101)]
stream = self.ssc.queueStream(inputs)
self._collect(stream, 1, block=False)
def test_stop_only_streaming_context(self):
self._add_input_stream()
self.ssc.start()
self.ssc.stop(False)
self.assertEqual(len(self.sc.parallelize(range(5), 5).glom().collect()), 5)
def test_stop_multiple_times(self):
self._add_input_stream()
self.ssc.start()
self.ssc.stop(False)
self.ssc.stop(False)
def test_queue_stream(self):
input = [list(range(i + 1)) for i in range(3)]
dstream = self.ssc.queueStream(input)
result = self._collect(dstream, 3)
self.assertEqual(input, result)
def test_text_file_stream(self):
d = tempfile.mkdtemp()
self.ssc = StreamingContext(self.sc, self.duration)
dstream2 = self.ssc.textFileStream(d).map(int)
result = self._collect(dstream2, 2, block=False)
self.ssc.start()
for name in ('a', 'b'):
time.sleep(1)
with open(os.path.join(d, name), "w") as f:
f.writelines(["%d\n" % i for i in range(10)])
self.wait_for(result, 2)
self.assertEqual([list(range(10)), list(range(10))], result)
def test_binary_records_stream(self):
d = tempfile.mkdtemp()
self.ssc = StreamingContext(self.sc, self.duration)
dstream = self.ssc.binaryRecordsStream(d, 10).map(
lambda v: struct.unpack("10b", bytes(v)))
result = self._collect(dstream, 2, block=False)
self.ssc.start()
for name in ('a', 'b'):
time.sleep(1)
with open(os.path.join(d, name), "wb") as f:
f.write(bytearray(range(10)))
self.wait_for(result, 2)
self.assertEqual([list(range(10)), list(range(10))], [list(v[0]) for v in result])
def test_union(self):
input = [list(range(i + 1)) for i in range(3)]
dstream = self.ssc.queueStream(input)
dstream2 = self.ssc.queueStream(input)
dstream3 = self.ssc.union(dstream, dstream2)
result = self._collect(dstream3, 3)
expected = [i * 2 for i in input]
self.assertEqual(expected, result)
def test_transform(self):
dstream1 = self.ssc.queueStream([[1]])
dstream2 = self.ssc.queueStream([[2]])
dstream3 = self.ssc.queueStream([[3]])
def func(rdds):
rdd1, rdd2, rdd3 = rdds
return rdd2.union(rdd3).union(rdd1)
dstream = self.ssc.transform([dstream1, dstream2, dstream3], func)
self.assertEqual([2, 3, 1], self._take(dstream, 3))
def test_transform_pairrdd(self):
# This regression test case is for SPARK-17756.
dstream = self.ssc.queueStream(
[[1], [2], [3]]).transform(lambda rdd: rdd.cartesian(rdd))
self.assertEqual([(1, 1), (2, 2), (3, 3)], self._take(dstream, 3))
def test_get_active(self):
self.assertEqual(StreamingContext.getActive(), None)
# Verify that getActive() returns the active context
self.ssc.queueStream([[1]]).foreachRDD(lambda rdd: rdd.count())
self.ssc.start()
self.assertEqual(StreamingContext.getActive(), self.ssc)
# Verify that getActive() returns None
self.ssc.stop(False)
self.assertEqual(StreamingContext.getActive(), None)
# Verify that if the Java context is stopped, then getActive() returns None
self.ssc = StreamingContext(self.sc, self.duration)
self.ssc.queueStream([[1]]).foreachRDD(lambda rdd: rdd.count())
self.ssc.start()
self.assertEqual(StreamingContext.getActive(), self.ssc)
self.ssc._jssc.stop(False)
self.assertEqual(StreamingContext.getActive(), None)
def test_get_active_or_create(self):
# Test StreamingContext.getActiveOrCreate() without checkpoint data
# See CheckpointTests for tests with checkpoint data
self.ssc = None
self.assertEqual(StreamingContext.getActive(), None)
def setupFunc():
ssc = StreamingContext(self.sc, self.duration)
ssc.queueStream([[1]]).foreachRDD(lambda rdd: rdd.count())
self.setupCalled = True
return ssc
# Verify that getActiveOrCreate() (w/o checkpoint) calls setupFunc when no context is active
self.setupCalled = False
self.ssc = StreamingContext.getActiveOrCreate(None, setupFunc)
self.assertTrue(self.setupCalled)
# Verify that getActiveOrCreate() returns active context and does not call the setupFunc
self.ssc.start()
self.setupCalled = False
self.assertEqual(StreamingContext.getActiveOrCreate(None, setupFunc), self.ssc)
self.assertFalse(self.setupCalled)
# Verify that getActiveOrCreate() calls setupFunc after active context is stopped
self.ssc.stop(False)
self.setupCalled = False
self.ssc = StreamingContext.getActiveOrCreate(None, setupFunc)
self.assertTrue(self.setupCalled)
# Verify that if the Java context is stopped, then getActive() returns None
self.ssc = StreamingContext(self.sc, self.duration)
self.ssc.queueStream([[1]]).foreachRDD(lambda rdd: rdd.count())
self.ssc.start()
self.assertEqual(StreamingContext.getActive(), self.ssc)
self.ssc._jssc.stop(False)
self.setupCalled = False
self.ssc = StreamingContext.getActiveOrCreate(None, setupFunc)
self.assertTrue(self.setupCalled)
def test_await_termination_or_timeout(self):
self._add_input_stream()
self.ssc.start()
self.assertFalse(self.ssc.awaitTerminationOrTimeout(0.001))
self.ssc.stop(False)
self.assertTrue(self.ssc.awaitTerminationOrTimeout(0.001))
if __name__ == "__main__":
import unittest
from pyspark.streaming.tests.test_context 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)