def __init__(self,
control_address, # type: str
credentials=None,
worker_id=None, # type: Optional[str]
# Caching is disabled by default
state_cache_size=0,
# time-based data buffering is disabled by default
data_buffer_time_limit_ms=0,
profiler_factory=None, # type: Optional[Callable[..., Profile]]
status_address=None, # type: Optional[str, unicode]
):
self._alive = True
self._worker_index = 0
self._worker_id = worker_id
self._state_cache = StateCache(state_cache_size)
if credentials is None:
_LOGGER.info('Creating insecure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.insecure_channel(
control_address)
else:
_LOGGER.info('Creating secure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.secure_channel(
control_address, credentials)
grpc.channel_ready_future(self._control_channel).result(timeout=60)
_LOGGER.info('Control channel established.')
self._control_channel = grpc.intercept_channel(
self._control_channel, WorkerIdInterceptor(self._worker_id))
self._data_channel_factory = data_plane.GrpcClientDataChannelFactory(
credentials, self._worker_id, data_buffer_time_limit_ms)
self._state_handler_factory = GrpcStateHandlerFactory(
self._state_cache, credentials)
self._profiler_factory = profiler_factory
self._fns = {} # type: Dict[str, beam_fn_api_pb2.ProcessBundleDescriptor]
# BundleProcessor cache across all workers.
self._bundle_processor_cache = BundleProcessorCache(
state_handler_factory=self._state_handler_factory,
data_channel_factory=self._data_channel_factory,
fns=self._fns)
if status_address:
try:
self._status_handler = FnApiWorkerStatusHandler(
status_address, self._bundle_processor_cache)
except Exception:
traceback_string = traceback.format_exc()
_LOGGER.warning(
'Error creating worker status request handler, '
'skipping status report. Trace back: %s' % traceback_string)
else:
self._status_handler = None
# TODO(BEAM-8998) use common UnboundedThreadPoolExecutor to process bundle
# progress once dataflow runner's excessive progress polling is removed.
self._report_progress_executor = futures.ThreadPoolExecutor(max_workers=1)
self._worker_thread_pool = UnboundedThreadPoolExecutor()
self._responses = queue.Queue(
) # type: queue.Queue[beam_fn_api_pb2.InstructionResponse]
_LOGGER.info('Initializing SDKHarness with unbounded number of workers.')
def setUp(self):
self.num_request = 3
self.test_status_service = BeamFnStatusServicer(self.num_request)
self.server = grpc.server(UnboundedThreadPoolExecutor())
beam_fn_api_pb2_grpc.add_BeamFnWorkerStatusServicer_to_server(
self.test_status_service, self.server)
self.test_port = self.server.add_insecure_port('[::]:0')
self.server.start()
self.url = 'localhost:%s' % self.test_port
self.fn_status_handler = FnApiWorkerStatusHandler(self.url)
class FnApiWorkerStatusHandlerTest(unittest.TestCase):
def setUp(self):
self.num_request = 3
self.test_status_service = BeamFnStatusServicer(self.num_request)
self.server = grpc.server(
thread_pool_executor.shared_unbounded_instance())
beam_fn_api_pb2_grpc.add_BeamFnWorkerStatusServicer_to_server(
self.test_status_service, self.server)
self.test_port = self.server.add_insecure_port('[::]:0')
self.server.start()
self.url = 'localhost:%s' % self.test_port
self.fn_status_handler = FnApiWorkerStatusHandler(self.url)
def tearDown(self):
self.server.stop(5)
@timeout(5)
def test_send_status_response(self):
self.test_status_service.finished.acquire()
while len(
self.test_status_service.response_received) < self.num_request:
self.test_status_service.finished.wait(1)
self.test_status_service.finished.release()
for response in self.test_status_service.response_received:
self.assertIsNotNone(response.status_info)
self.fn_status_handler.close()
@timeout(5)
@mock.patch('apache_beam.runners.worker.worker_status'
'.FnApiWorkerStatusHandler.generate_status_response')
def test_generate_error(self, mock_method):
mock_method.side_effect = RuntimeError('error')
self.test_status_service.finished.acquire()
while len(
self.test_status_service.response_received) < self.num_request:
self.test_status_service.finished.wait(1)
self.test_status_service.finished.release()
for response in self.test_status_service.response_received:
self.assertIsNotNone(response.error)
self.fn_status_handler.close()
class SdkHarness(object):
REQUEST_METHOD_PREFIX = '_request_'
def __init__(self,
control_address, # type: str
credentials=None,
worker_id=None, # type: Optional[str]
# Caching is disabled by default
state_cache_size=0,
# time-based data buffering is disabled by default
data_buffer_time_limit_ms=0,
profiler_factory=None, # type: Optional[Callable[..., Profile]]
status_address=None, # type: Optional[str, unicode]
):
self._alive = True
self._worker_index = 0
self._worker_id = worker_id
self._state_cache = StateCache(state_cache_size)
if credentials is None:
_LOGGER.info('Creating insecure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.insecure_channel(
control_address)
else:
_LOGGER.info('Creating secure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.secure_channel(
control_address, credentials)
grpc.channel_ready_future(self._control_channel).result(timeout=60)
_LOGGER.info('Control channel established.')
self._control_channel = grpc.intercept_channel(
self._control_channel, WorkerIdInterceptor(self._worker_id))
self._data_channel_factory = data_plane.GrpcClientDataChannelFactory(
credentials, self._worker_id, data_buffer_time_limit_ms)
self._state_handler_factory = GrpcStateHandlerFactory(
self._state_cache, credentials)
self._profiler_factory = profiler_factory
self._fns = {} # type: Dict[str, beam_fn_api_pb2.ProcessBundleDescriptor]
# BundleProcessor cache across all workers.
self._bundle_processor_cache = BundleProcessorCache(
state_handler_factory=self._state_handler_factory,
data_channel_factory=self._data_channel_factory,
fns=self._fns)
if status_address:
try:
self._status_handler = FnApiWorkerStatusHandler(
status_address, self._bundle_processor_cache)
except Exception:
traceback_string = traceback.format_exc()
_LOGGER.warning(
'Error creating worker status request handler, '
'skipping status report. Trace back: %s' % traceback_string)
else:
self._status_handler = None
# TODO(BEAM-8998) use common UnboundedThreadPoolExecutor to process bundle
# progress once dataflow runner's excessive progress polling is removed.
self._report_progress_executor = futures.ThreadPoolExecutor(max_workers=1)
self._worker_thread_pool = UnboundedThreadPoolExecutor()
self._responses = queue.Queue(
) # type: queue.Queue[beam_fn_api_pb2.InstructionResponse]
_LOGGER.info('Initializing SDKHarness with unbounded number of workers.')
def run(self):
control_stub = beam_fn_api_pb2_grpc.BeamFnControlStub(self._control_channel)
no_more_work = object()
def get_responses():
# type: () -> Iterator[beam_fn_api_pb2.InstructionResponse]
while True:
response = self._responses.get()
if response is no_more_work:
return
yield response
self._alive = True
try:
for work_request in control_stub.Control(get_responses()):
_LOGGER.debug('Got work %s', work_request.instruction_id)
request_type = work_request.WhichOneof('request')
# Name spacing the request method with 'request_'. The called method
# will be like self.request_register(request)
getattr(self, SdkHarness.REQUEST_METHOD_PREFIX + request_type)(
work_request)
finally:
self._alive = False
_LOGGER.info('No more requests from control plane')
_LOGGER.info('SDK Harness waiting for in-flight requests to complete')
# Wait until existing requests are processed.
self._worker_thread_pool.shutdown()
# get_responses may be blocked on responses.get(), but we need to return
# control to its caller.
self._responses.put(no_more_work)
# Stop all the workers and clean all the associated resources
self._data_channel_factory.close()
self._state_handler_factory.close()
self._bundle_processor_cache.shutdown()
if self._status_handler:
self._status_handler.close()
_LOGGER.info('Done consuming work.')
def _execute(self,
task, # type: Callable[[], beam_fn_api_pb2.InstructionResponse]
request # type: beam_fn_api_pb2.InstructionRequest
):
# type: (...) -> None
with statesampler.instruction_id(request.instruction_id):
try:
response = task()
except Exception: # pylint: disable=broad-except
traceback_string = traceback.format_exc()
print(traceback_string, file=sys.stderr)
_LOGGER.error(
'Error processing instruction %s. Original traceback is\n%s\n',
request.instruction_id,
traceback_string)
response = beam_fn_api_pb2.InstructionResponse(
instruction_id=request.instruction_id, error=traceback_string)
self._responses.put(response)
def _request_register(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
# registration request is handled synchronously
self._execute(lambda: self.create_worker().do_instruction(request), request)
def _request_process_bundle(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_execute(request)
def _request_process_bundle_split(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_process_bundle_action(request)
def _request_process_bundle_progress(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_process_bundle_action(request)
def _request_process_bundle_action(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
def task():
instruction_id = getattr(
request, request.WhichOneof('request')).instruction_id
# only process progress/split request when a bundle is in processing.
if (instruction_id in
self._bundle_processor_cache.active_bundle_processors):
self._execute(
lambda: self.create_worker().do_instruction(request), request)
else:
self._execute(
lambda: beam_fn_api_pb2.InstructionResponse(
instruction_id=request.instruction_id,
error=('Unknown process bundle instruction {}').format(
instruction_id)),
request)
self._report_progress_executor.submit(task)
def _request_finalize_bundle(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_execute(request)
def _request_execute(self, request):
def task():
self._execute(
lambda: self.create_worker().do_instruction(request), request)
self._worker_thread_pool.submit(task)
_LOGGER.debug(
"Currently using %s threads." % len(self._worker_thread_pool._workers))
def create_worker(self):
return SdkWorker(
self._bundle_processor_cache,
state_cache_metrics_fn=self._state_cache.get_monitoring_infos,
profiler_factory=self._profiler_factory)
def __init__(
self,
control_address, # type: str
credentials=None, # type: Optional[grpc.ChannelCredentials]
worker_id=None, # type: Optional[str]
# Caching is disabled by default
state_cache_size=0, # type: int
# time-based data buffering is disabled by default
data_buffer_time_limit_ms=0, # type: int
profiler_factory=None, # type: Optional[Callable[..., Profile]]
status_address=None, # type: Optional[str]
# Heap dump through status api is disabled by default
enable_heap_dump=False, # type: bool
):
# type: (...) -> None
self._alive = True
self._worker_index = 0
self._worker_id = worker_id
self._state_cache = StateCache(state_cache_size)
options = [('grpc.max_receive_message_length', -1),
('grpc.max_send_message_length', -1)]
if credentials is None:
_LOGGER.info('Creating insecure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.insecure_channel(
control_address, options=options)
else:
_LOGGER.info('Creating secure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.secure_channel(
control_address, credentials, options=options)
grpc.channel_ready_future(self._control_channel).result(timeout=60)
_LOGGER.info('Control channel established.')
self._control_channel = grpc.intercept_channel(
self._control_channel, WorkerIdInterceptor(self._worker_id))
self._data_channel_factory = data_plane.GrpcClientDataChannelFactory(
credentials, self._worker_id, data_buffer_time_limit_ms)
self._state_handler_factory = GrpcStateHandlerFactory(
self._state_cache, credentials)
self._profiler_factory = profiler_factory
def default_factory(id):
# type: (str) -> beam_fn_api_pb2.ProcessBundleDescriptor
return self._control_stub.GetProcessBundleDescriptor(
beam_fn_api_pb2.GetProcessBundleDescriptorRequest(
process_bundle_descriptor_id=id))
self._fns = KeyedDefaultDict(default_factory)
# BundleProcessor cache across all workers.
self._bundle_processor_cache = BundleProcessorCache(
state_handler_factory=self._state_handler_factory,
data_channel_factory=self._data_channel_factory,
fns=self._fns)
if status_address:
try:
self._status_handler = FnApiWorkerStatusHandler(
status_address, self._bundle_processor_cache,
enable_heap_dump) # type: Optional[FnApiWorkerStatusHandler]
except Exception:
traceback_string = traceback.format_exc()
_LOGGER.warning(
'Error creating worker status request handler, '
'skipping status report. Trace back: %s' % traceback_string)
else:
self._status_handler = None
# TODO(BEAM-8998) use common
# thread_pool_executor.shared_unbounded_instance() to process bundle
# progress once dataflow runner's excessive progress polling is removed.
self._report_progress_executor = futures.ThreadPoolExecutor(max_workers=1)
self._worker_thread_pool = thread_pool_executor.shared_unbounded_instance()
self._responses = queue.Queue(
) # type: queue.Queue[Union[beam_fn_api_pb2.InstructionResponse, Sentinel]]
_LOGGER.info('Initializing SDKHarness with unbounded number of workers.')
class SdkHarness(object):
REQUEST_METHOD_PREFIX = '_request_'
def __init__(
self,
control_address, # type: str
credentials=None, # type: Optional[grpc.ChannelCredentials]
worker_id=None, # type: Optional[str]
# Caching is disabled by default
state_cache_size=0, # type: int
# time-based data buffering is disabled by default
data_buffer_time_limit_ms=0, # type: int
profiler_factory=None, # type: Optional[Callable[..., Profile]]
status_address=None, # type: Optional[str]
# Heap dump through status api is disabled by default
enable_heap_dump=False, # type: bool
):
# type: (...) -> None
self._alive = True
self._worker_index = 0
self._worker_id = worker_id
self._state_cache = StateCache(state_cache_size)
options = [('grpc.max_receive_message_length', -1),
('grpc.max_send_message_length', -1)]
if credentials is None:
_LOGGER.info('Creating insecure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.insecure_channel(
control_address, options=options)
else:
_LOGGER.info('Creating secure control channel for %s.', control_address)
self._control_channel = GRPCChannelFactory.secure_channel(
control_address, credentials, options=options)
grpc.channel_ready_future(self._control_channel).result(timeout=60)
_LOGGER.info('Control channel established.')
self._control_channel = grpc.intercept_channel(
self._control_channel, WorkerIdInterceptor(self._worker_id))
self._data_channel_factory = data_plane.GrpcClientDataChannelFactory(
credentials, self._worker_id, data_buffer_time_limit_ms)
self._state_handler_factory = GrpcStateHandlerFactory(
self._state_cache, credentials)
self._profiler_factory = profiler_factory
def default_factory(id):
# type: (str) -> beam_fn_api_pb2.ProcessBundleDescriptor
return self._control_stub.GetProcessBundleDescriptor(
beam_fn_api_pb2.GetProcessBundleDescriptorRequest(
process_bundle_descriptor_id=id))
self._fns = KeyedDefaultDict(default_factory)
# BundleProcessor cache across all workers.
self._bundle_processor_cache = BundleProcessorCache(
state_handler_factory=self._state_handler_factory,
data_channel_factory=self._data_channel_factory,
fns=self._fns)
if status_address:
try:
self._status_handler = FnApiWorkerStatusHandler(
status_address, self._bundle_processor_cache,
enable_heap_dump) # type: Optional[FnApiWorkerStatusHandler]
except Exception:
traceback_string = traceback.format_exc()
_LOGGER.warning(
'Error creating worker status request handler, '
'skipping status report. Trace back: %s' % traceback_string)
else:
self._status_handler = None
# TODO(BEAM-8998) use common
# thread_pool_executor.shared_unbounded_instance() to process bundle
# progress once dataflow runner's excessive progress polling is removed.
self._report_progress_executor = futures.ThreadPoolExecutor(max_workers=1)
self._worker_thread_pool = thread_pool_executor.shared_unbounded_instance()
self._responses = queue.Queue(
) # type: queue.Queue[Union[beam_fn_api_pb2.InstructionResponse, Sentinel]]
_LOGGER.info('Initializing SDKHarness with unbounded number of workers.')
def run(self):
# type: () -> None
self._control_stub = beam_fn_api_pb2_grpc.BeamFnControlStub(
self._control_channel)
no_more_work = Sentinel.sentinel
def get_responses():
# type: () -> Iterator[beam_fn_api_pb2.InstructionResponse]
while True:
response = self._responses.get()
if response is no_more_work:
return
yield response
self._alive = True
try:
for work_request in self._control_stub.Control(get_responses()):
_LOGGER.debug('Got work %s', work_request.instruction_id)
request_type = work_request.WhichOneof('request')
# Name spacing the request method with 'request_'. The called method
# will be like self.request_register(request)
getattr(self, SdkHarness.REQUEST_METHOD_PREFIX + request_type)(
work_request)
finally:
self._alive = False
_LOGGER.info('No more requests from control plane')
_LOGGER.info('SDK Harness waiting for in-flight requests to complete')
# Wait until existing requests are processed.
self._worker_thread_pool.shutdown()
# get_responses may be blocked on responses.get(), but we need to return
# control to its caller.
self._responses.put(no_more_work)
# Stop all the workers and clean all the associated resources
self._data_channel_factory.close()
self._state_handler_factory.close()
self._bundle_processor_cache.shutdown()
if self._status_handler:
self._status_handler.close()
_LOGGER.info('Done consuming work.')
def _execute(
self,
task, # type: Callable[[], beam_fn_api_pb2.InstructionResponse]
request # type: beam_fn_api_pb2.InstructionRequest
):
# type: (...) -> None
with statesampler.instruction_id(request.instruction_id):
try:
response = task()
except Exception: # pylint: disable=broad-except
traceback_string = traceback.format_exc()
print(traceback_string, file=sys.stderr)
_LOGGER.error(
'Error processing instruction %s. Original traceback is\n%s\n',
request.instruction_id,
traceback_string)
response = beam_fn_api_pb2.InstructionResponse(
instruction_id=request.instruction_id, error=traceback_string)
self._responses.put(response)
def _request_register(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
# registration request is handled synchronously
self._execute(lambda: self.create_worker().do_instruction(request), request)
def _request_process_bundle(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._bundle_processor_cache.activate(request.instruction_id)
self._request_execute(request)
def _request_process_bundle_split(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_process_bundle_action(request)
def _request_process_bundle_progress(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_process_bundle_action(request)
def _request_process_bundle_action(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
def task():
# type: () -> None
self._execute(
lambda: self.create_worker().do_instruction(request), request)
self._report_progress_executor.submit(task)
def _request_finalize_bundle(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._request_execute(request)
def _request_harness_monitoring_infos(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
process_wide_monitoring_infos = MetricsEnvironment.process_wide_container(
).to_runner_api_monitoring_infos(None).values()
self._execute(
lambda: beam_fn_api_pb2.InstructionResponse(
instruction_id=request.instruction_id,
harness_monitoring_infos=(
beam_fn_api_pb2.HarnessMonitoringInfosResponse(
monitoring_data={
SHORT_ID_CACHE.get_short_id(info): info.payload
for info in process_wide_monitoring_infos
}))),
request)
def _request_monitoring_infos(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
self._execute(
lambda: beam_fn_api_pb2.InstructionResponse(
instruction_id=request.instruction_id,
monitoring_infos=beam_fn_api_pb2.MonitoringInfosMetadataResponse(
monitoring_info=SHORT_ID_CACHE.get_infos(
request.monitoring_infos.monitoring_info_id))),
request)
def _request_execute(self, request):
# type: (beam_fn_api_pb2.InstructionRequest) -> None
def task():
# type: () -> None
self._execute(
lambda: self.create_worker().do_instruction(request), request)
self._worker_thread_pool.submit(task)
_LOGGER.debug(
"Currently using %s threads." % len(self._worker_thread_pool._workers))
def create_worker(self):
# type: () -> SdkWorker
return SdkWorker(
self._bundle_processor_cache,
state_cache_metrics_fn=self._state_cache.get_monitoring_infos,
profiler_factory=self._profiler_factory)
