[DO NOT MERGE] Run all PostCommit and PreCommit Tests against Release Branch #189
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Aug 22, 2024 in 0s
1 fail, 21 skipped, 18 pass in 9m 55s
40 tests 18 ✅ 9m 55s ⏱️
1 suites 21 💤
1 files 1 ❌
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Check warning on line 0 in apache_beam.examples.complete.distribopt_test.DistribOptimizationTest
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test_basics (apache_beam.examples.complete.distribopt_test.DistribOptimizationTest) failed
sdks/python/pytest_postCommitExamples-flink-py38.xml [took 20s]
Raw output
RuntimeError: Pipeline BeamApp-runner-0822225732-6fc40dbb_65a5cb53-52cb-4d83-b9d7-40c8807c1446 failed in state FAILED: java.io.IOException: Insufficient number of network buffers: required 16, but only 6 available. The total number of network buffers is currently set to 2048 of 32768 bytes each. You can increase this number by setting the configuration keys 'taskmanager.memory.network.fraction', 'taskmanager.memory.network.min', and 'taskmanager.memory.network.max'.
self = <apache_beam.examples.complete.distribopt_test.DistribOptimizationTest testMethod=test_basics>
@pytest.mark.sickbay_dataflow
@pytest.mark.examples_postcommit
def test_basics(self):
test_pipeline = TestPipeline(is_integration_test=True)
# Setup the files with expected content.
temp_location = test_pipeline.get_option('temp_location')
input = '/'.join([temp_location, str(uuid.uuid4()), 'input.txt'])
output = '/'.join([temp_location, str(uuid.uuid4()), 'result'])
create_file(input, FILE_CONTENTS)
extra_opts = {'input': input, 'output': output}
# Run pipeline
# Avoid dependency on SciPy
scipy_mock = MagicMock()
result_mock = MagicMock(x=np.ones(3))
scipy_mock.optimize.minimize = MagicMock(return_value=result_mock)
modules = {'scipy': scipy_mock, 'scipy.optimize': scipy_mock.optimize}
with patch.dict('sys.modules', modules):
from apache_beam.examples.complete import distribopt
> distribopt.run(
test_pipeline.get_full_options_as_args(**extra_opts),
save_main_session=False)
apache_beam/examples/complete/distribopt_test.py:70:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/examples/complete/distribopt.py:359: in run
best | 'write optimum' >> beam.io.WriteToText(known_args.output)
apache_beam/pipeline.py:621: in __exit__
self.result.wait_until_finish()
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <apache_beam.runners.portability.portable_runner.PipelineResult object at 0x7b2f1dbac490>
duration = None
def wait_until_finish(self, duration=None):
"""
:param duration: The maximum time in milliseconds to wait for the result of
the execution. If None or zero, will wait until the pipeline finishes.
:return: The result of the pipeline, i.e. PipelineResult.
"""
def read_messages() -> None:
previous_state = -1
for message in self._message_stream:
if message.HasField('message_response'):
logging.log(
MESSAGE_LOG_LEVELS[message.message_response.importance],
"%s",
message.message_response.message_text)
else:
current_state = message.state_response.state
if current_state != previous_state:
_LOGGER.info(
"Job state changed to %s",
self.runner_api_state_to_pipeline_state(current_state))
previous_state = current_state
self._messages.append(message)
message_thread = threading.Thread(
target=read_messages, name='wait_until_finish_read')
message_thread.daemon = True
message_thread.start()
if duration:
state_thread = threading.Thread(
target=functools.partial(self._observe_state, message_thread),
name='wait_until_finish_state_observer')
state_thread.daemon = True
state_thread.start()
start_time = time.time()
duration_secs = duration / 1000
while (time.time() - start_time < duration_secs and
state_thread.is_alive()):
time.sleep(1)
else:
self._observe_state(message_thread)
if self._runtime_exception:
> raise self._runtime_exception
E RuntimeError: Pipeline BeamApp-runner-0822225732-6fc40dbb_65a5cb53-52cb-4d83-b9d7-40c8807c1446 failed in state FAILED: java.io.IOException: Insufficient number of network buffers: required 16, but only 6 available. The total number of network buffers is currently set to 2048 of 32768 bytes each. You can increase this number by setting the configuration keys 'taskmanager.memory.network.fraction', 'taskmanager.memory.network.min', and 'taskmanager.memory.network.max'.
apache_beam/runners/portability/portable_runner.py:568: RuntimeError
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