本文整理汇总了Python中apache_beam.metrics.execution.MetricsContainer类的典型用法代码示例。如果您正苦于以下问题:Python MetricsContainer类的具体用法?Python MetricsContainer怎么用?Python MetricsContainer使用的例子?那么, 这里精选的类代码示例或许可以为您提供帮助。
在下文中一共展示了MetricsContainer类的12个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: call
def call(self):
self._call_count += 1
assert self._call_count <= (1 + len(self._applied_ptransform.side_inputs))
metrics_container = MetricsContainer(self._applied_ptransform.full_label)
scoped_metrics_container = ScopedMetricsContainer(metrics_container)
for side_input in self._applied_ptransform.side_inputs:
if side_input not in self._side_input_values:
has_result, value = (
self._evaluation_context.get_value_or_schedule_after_output(
side_input, self))
if not has_result:
# Monitor task will reschedule this executor once the side input is
# available.
return
self._side_input_values[side_input] = value
side_input_values = [self._side_input_values[side_input]
for side_input in self._applied_ptransform.side_inputs]
try:
evaluator = self._transform_evaluator_registry.get_evaluator(
self._applied_ptransform, self._input_bundle,
side_input_values, scoped_metrics_container)
if self._fired_timers:
for timer_firing in self._fired_timers:
evaluator.process_timer_wrapper(timer_firing)
if self._input_bundle:
for value in self._input_bundle.get_elements_iterable():
evaluator.process_element(value)
with scoped_metrics_container:
result = evaluator.finish_bundle()
result.logical_metric_updates = metrics_container.get_cumulative()
if self._evaluation_context.has_cache:
for uncommitted_bundle in result.uncommitted_output_bundles:
self._evaluation_context.append_to_cache(
self._applied_ptransform, uncommitted_bundle.tag,
uncommitted_bundle.get_elements_iterable())
undeclared_tag_values = result.undeclared_tag_values
if undeclared_tag_values:
for tag, value in undeclared_tag_values.iteritems():
self._evaluation_context.append_to_cache(
self._applied_ptransform, tag, value)
self._completion_callback.handle_result(self, self._input_bundle, result)
return result
except Exception as e: # pylint: disable=broad-except
self._completion_callback.handle_exception(self, e)
finally:
self._evaluation_context.metrics().commit_physical(
self._input_bundle,
metrics_container.get_cumulative())
self._transform_evaluation_state.complete(self)
示例2: __init__
def __init__(self, operation_name, spec, counter_factory, state_sampler):
"""Initializes a worker operation instance.
Args:
operation_name: The system name assigned by the runner for this
operation.
spec: A operation_specs.Worker* instance.
counter_factory: The CounterFactory to use for our counters.
state_sampler: The StateSampler for the current operation.
"""
self.operation_name = operation_name
self.spec = spec
self.counter_factory = counter_factory
self.consumers = collections.defaultdict(list)
# These are overwritten in the legacy harness.
self.step_name = operation_name
self.metrics_container = MetricsContainer(self.step_name)
self.scoped_metrics_container = ScopedMetricsContainer(
self.metrics_container)
self.state_sampler = state_sampler
self.scoped_start_state = self.state_sampler.scoped_state(
self.operation_name, 'start')
self.scoped_process_state = self.state_sampler.scoped_state(
self.operation_name, 'process')
self.scoped_finish_state = self.state_sampler.scoped_state(
self.operation_name, 'finish')
# TODO(ccy): the '-abort' state can be added when the abort is supported in
# Operations.
self.receivers = []
示例3: __init__
def __init__(self, name_context, spec, counter_factory, state_sampler):
"""Initializes a worker operation instance.
Args:
name_context: A NameContext instance or string(deprecated), with the
name information for this operation.
spec: A operation_specs.Worker* instance.
counter_factory: The CounterFactory to use for our counters.
state_sampler: The StateSampler for the current operation.
"""
if isinstance(name_context, common.NameContext):
# TODO(BEAM-4028): Clean this up once it's completely migrated.
# We use the specific operation name that is used for metrics and state
# sampling.
self.name_context = name_context
else:
self.name_context = common.NameContext(name_context)
self.spec = spec
self.counter_factory = counter_factory
self.consumers = collections.defaultdict(list)
# These are overwritten in the legacy harness.
self.metrics_container = MetricsContainer(self.name_context.metrics_name())
self.state_sampler = state_sampler
self.scoped_start_state = self.state_sampler.scoped_state(
self.name_context, 'start', metrics_container=self.metrics_container)
self.scoped_process_state = self.state_sampler.scoped_state(
self.name_context, 'process', metrics_container=self.metrics_container)
self.scoped_finish_state = self.state_sampler.scoped_state(
self.name_context, 'finish', metrics_container=self.metrics_container)
# TODO(ccy): the '-abort' state can be added when the abort is supported in
# Operations.
self.receivers = []
示例4: test_uses_right_container
def test_uses_right_container(self):
c1 = MetricsContainer('step1')
c2 = MetricsContainer('step2')
counter = Metrics.counter('ns', 'name')
MetricsEnvironment.set_current_container(c1)
counter.inc()
MetricsEnvironment.set_current_container(c2)
counter.inc(3)
MetricsEnvironment.unset_current_container()
self.assertEqual(
c1.get_cumulative().counters.items(),
[(MetricKey('step1', MetricName('ns', 'name')), 1)])
self.assertEqual(
c2.get_cumulative().counters.items(),
[(MetricKey('step2', MetricName('ns', 'name')), 3)])
示例5: call
def call(self):
self._call_count += 1
assert self._call_count <= (1 + len(self._applied_ptransform.side_inputs))
metrics_container = MetricsContainer(self._applied_ptransform.full_label)
scoped_metrics_container = ScopedMetricsContainer(metrics_container)
for side_input in self._applied_ptransform.side_inputs:
if side_input not in self._side_input_values:
has_result, value = (
self._evaluation_context.get_value_or_schedule_after_output(
side_input, self))
if not has_result:
# Monitor task will reschedule this executor once the side input is
# available.
return
self._side_input_values[side_input] = value
side_input_values = [self._side_input_values[side_input]
for side_input in self._applied_ptransform.side_inputs]
while self._retry_count < self._max_retries_per_bundle:
try:
self.attempt_call(metrics_container,
scoped_metrics_container,
side_input_values)
break
except Exception as e:
self._retry_count += 1
logging.error(
'Exception at bundle %r, due to an exception.\n %s',
self._input_bundle, traceback.format_exc())
if self._retry_count == self._max_retries_per_bundle:
logging.error('Giving up after %s attempts.',
self._max_retries_per_bundle)
if self._retry_count == 1:
logging.info(
'Use the experimental flag --direct_runner_bundle_retry'
' to retry failed bundles (up to %d times).',
TransformExecutor._MAX_RETRY_PER_BUNDLE)
self._completion_callback.handle_exception(self, e)
self._evaluation_context.metrics().commit_physical(
self._input_bundle,
metrics_container.get_cumulative())
self._transform_evaluation_state.complete(self)
示例6: call
def call(self):
self._call_count += 1
assert self._call_count <= (1 + len(self._applied_ptransform.side_inputs))
metrics_container = MetricsContainer(self._applied_ptransform.full_label)
scoped_metrics_container = ScopedMetricsContainer(metrics_container)
for side_input in self._applied_ptransform.side_inputs:
# Find the projection of main's window onto the side input's window.
window_mapping_fn = side_input._view_options().get(
'window_mapping_fn', sideinputs._global_window_mapping_fn)
main_onto_side_window = window_mapping_fn(self._latest_main_input_window)
block_until = main_onto_side_window.end
if side_input not in self._side_input_values:
value = self._evaluation_context.get_value_or_block_until_ready(
side_input, self, block_until)
if not value:
# Monitor task will reschedule this executor once the side input is
# available.
return
self._side_input_values[side_input] = value
side_input_values = [self._side_input_values[side_input]
for side_input in self._applied_ptransform.side_inputs]
while self._retry_count < self._max_retries_per_bundle:
try:
self.attempt_call(metrics_container,
scoped_metrics_container,
side_input_values)
break
except Exception as e:
self._retry_count += 1
logging.error(
'Exception at bundle %r, due to an exception.\n %s',
self._input_bundle, traceback.format_exc())
if self._retry_count == self._max_retries_per_bundle:
logging.error('Giving up after %s attempts.',
self._max_retries_per_bundle)
self._completion_callback.handle_exception(self, e)
self._evaluation_context.metrics().commit_physical(
self._input_bundle,
metrics_container.get_cumulative())
self._transform_evaluation_state.complete(self)
示例7: test_scoped_container
def test_scoped_container(self):
c1 = MetricsContainer('mystep')
c2 = MetricsContainer('myinternalstep')
with ScopedMetricsContainer(c1):
self.assertEqual(c1, MetricsEnvironment.current_container())
counter = Metrics.counter('ns', 'name')
counter.inc(2)
with ScopedMetricsContainer(c2):
self.assertEqual(c2, MetricsEnvironment.current_container())
counter = Metrics.counter('ns', 'name')
counter.inc(3)
self.assertEqual(
c2.get_cumulative().counters.items(),
[(MetricKey('myinternalstep', MetricName('ns', 'name')), 3)])
self.assertEqual(c1, MetricsEnvironment.current_container())
counter = Metrics.counter('ns', 'name')
counter.inc(4)
self.assertEqual(
c1.get_cumulative().counters.items(),
[(MetricKey('mystep', MetricName('ns', 'name')), 6)])
示例8: test_get_cumulative_or_updates
def test_get_cumulative_or_updates(self):
mc = MetricsContainer('astep')
clean_values = []
dirty_values = []
for i in range(1, 11):
counter = mc.get_counter(MetricName('namespace', 'name{}'.format(i)))
distribution = mc.get_distribution(
MetricName('namespace', 'name{}'.format(i)))
counter.inc(i)
distribution.update(i)
if i % 2 == 0:
# Some are left to be DIRTY (i.e. not yet committed).
# Some are left to be CLEAN (i.e. already committed).
dirty_values.append(i)
continue
# Assert: Counter/Distribution is DIRTY or COMMITTING (not CLEAN)
self.assertEqual(distribution.commit.before_commit(), True)
self.assertEqual(counter.commit.before_commit(), True)
distribution.commit.after_commit()
counter.commit.after_commit()
# Assert: Counter/Distribution has been committed, therefore it's CLEAN
self.assertEqual(counter.commit.state, CellCommitState.CLEAN)
self.assertEqual(distribution.commit.state, CellCommitState.CLEAN)
clean_values.append(i)
# Retrieve NON-COMMITTED updates.
logical = mc.get_updates()
self.assertEqual(len(logical.counters), 5)
self.assertEqual(len(logical.distributions), 5)
self.assertEqual(set(dirty_values),
set([v for _, v in logical.counters.items()]))
# Retrieve ALL updates.
cumulative = mc.get_cumulative()
self.assertEqual(len(cumulative.counters), 10)
self.assertEqual(len(cumulative.distributions), 10)
self.assertEqual(set(dirty_values + clean_values),
set([v for _, v in cumulative.counters.items()]))
示例9: Operation
class Operation(object):
"""An operation representing the live version of a work item specification.
An operation can have one or more outputs and for each output it can have
one or more receiver operations that will take that as input.
"""
def __init__(self, operation_name, spec, counter_factory, state_sampler):
"""Initializes a worker operation instance.
Args:
operation_name: The system name assigned by the runner for this
operation.
spec: A operation_specs.Worker* instance.
counter_factory: The CounterFactory to use for our counters.
state_sampler: The StateSampler for the current operation.
"""
self.operation_name = operation_name
self.spec = spec
self.counter_factory = counter_factory
self.consumers = collections.defaultdict(list)
# These are overwritten in the legacy harness.
self.step_name = operation_name
self.metrics_container = MetricsContainer(self.step_name)
self.scoped_metrics_container = ScopedMetricsContainer(
self.metrics_container)
self.state_sampler = state_sampler
self.scoped_start_state = self.state_sampler.scoped_state(
self.operation_name, 'start')
self.scoped_process_state = self.state_sampler.scoped_state(
self.operation_name, 'process')
self.scoped_finish_state = self.state_sampler.scoped_state(
self.operation_name, 'finish')
# TODO(ccy): the '-abort' state can be added when the abort is supported in
# Operations.
self.receivers = []
def start(self):
"""Start operation."""
self.debug_logging_enabled = logging.getLogger().isEnabledFor(
logging.DEBUG)
# Everything except WorkerSideInputSource, which is not a
# top-level operation, should have output_coders
if getattr(self.spec, 'output_coders', None):
self.receivers = [ConsumerSet(self.counter_factory, self.step_name,
i, self.consumers[i], coder)
for i, coder in enumerate(self.spec.output_coders)]
def finish(self):
"""Finish operation."""
pass
def process(self, o):
"""Process element in operation."""
pass
def output(self, windowed_value, output_index=0):
cython.cast(Receiver, self.receivers[output_index]).receive(windowed_value)
def add_receiver(self, operation, output_index=0):
"""Adds a receiver operation for the specified output."""
self.consumers[output_index].append(operation)
def progress_metrics(self):
return beam_fn_api_pb2.Metrics.PTransform(
processed_elements=beam_fn_api_pb2.Metrics.PTransform.ProcessedElements(
measured=beam_fn_api_pb2.Metrics.PTransform.Measured(
total_time_spent=(
self.scoped_start_state.sampled_seconds()
+ self.scoped_process_state.sampled_seconds()
+ self.scoped_finish_state.sampled_seconds()),
# Multi-output operations should override this.
output_element_counts=(
# If there is exactly one output, we can unambiguously
# fix its name later, which we do.
# TODO(robertwb): Plumb the actual name here.
{'ONLY_OUTPUT': self.receivers[0].opcounter
.element_counter.value()}
if len(self.receivers) == 1
else None))),
user=self.metrics_container.to_runner_api())
def __str__(self):
"""Generates a useful string for this object.
Compactly displays interesting fields. In particular, pickled
fields are not displayed. Note that we collapse the fields of the
contained Worker* object into this object, since there is a 1-1
mapping between Operation and operation_specs.Worker*.
Returns:
Compact string representing this object.
"""
return self.str_internal()
def str_internal(self, is_recursive=False):
"""Internal helper for __str__ that supports recursion.
#.........这里部分代码省略.........
示例10: test_add_to_counter
def test_add_to_counter(self):
mc = MetricsContainer('astep')
counter = mc.get_counter(MetricName('namespace', 'name'))
counter.inc()
counter = mc.get_counter(MetricName('namespace', 'name'))
self.assertEqual(counter.value, 1)
示例11: test_create_new_counter
def test_create_new_counter(self):
mc = MetricsContainer('astep')
self.assertFalse(MetricName('namespace', 'name') in mc.counters)
mc.get_counter(MetricName('namespace', 'name'))
self.assertTrue(MetricName('namespace', 'name') in mc.counters)
示例12: Operation
class Operation(object):
"""An operation representing the live version of a work item specification.
An operation can have one or more outputs and for each output it can have
one or more receiver operations that will take that as input.
"""
def __init__(self, name_context, spec, counter_factory, state_sampler):
"""Initializes a worker operation instance.
Args:
name_context: A NameContext instance or string(deprecated), with the
name information for this operation.
spec: A operation_specs.Worker* instance.
counter_factory: The CounterFactory to use for our counters.
state_sampler: The StateSampler for the current operation.
"""
if isinstance(name_context, common.NameContext):
# TODO(BEAM-4028): Clean this up once it's completely migrated.
# We use the specific operation name that is used for metrics and state
# sampling.
self.name_context = name_context
else:
self.name_context = common.NameContext(name_context)
self.spec = spec
self.counter_factory = counter_factory
self.execution_context = None
self.consumers = collections.defaultdict(list)
# These are overwritten in the legacy harness.
self.metrics_container = MetricsContainer(self.name_context.metrics_name())
self.state_sampler = state_sampler
self.scoped_start_state = self.state_sampler.scoped_state(
self.name_context, 'start', metrics_container=self.metrics_container)
self.scoped_process_state = self.state_sampler.scoped_state(
self.name_context, 'process', metrics_container=self.metrics_container)
self.scoped_finish_state = self.state_sampler.scoped_state(
self.name_context, 'finish', metrics_container=self.metrics_container)
# TODO(ccy): the '-abort' state can be added when the abort is supported in
# Operations.
self.receivers = []
# Legacy workers cannot call setup() until after setting additional state
# on the operation.
self.setup_done = False
def setup(self):
with self.scoped_start_state:
self.debug_logging_enabled = logging.getLogger().isEnabledFor(
logging.DEBUG)
# Everything except WorkerSideInputSource, which is not a
# top-level operation, should have output_coders
#TODO(pabloem): Define better what step name is used here.
if getattr(self.spec, 'output_coders', None):
self.receivers = [
ConsumerSet.create(
self.counter_factory,
self.name_context.logging_name(),
i,
self.consumers[i], coder)
for i, coder in enumerate(self.spec.output_coders)]
self.setup_done = True
def start(self):
"""Start operation."""
if not self.setup_done:
# For legacy workers.
self.setup()
def process(self, o):
"""Process element in operation."""
pass
def try_split(self, fraction_of_remainder):
return None
def finish(self):
"""Finish operation."""
pass
def reset(self):
self.metrics_container.reset()
def output(self, windowed_value, output_index=0):
cython.cast(Receiver, self.receivers[output_index]).receive(windowed_value)
def add_receiver(self, operation, output_index=0):
"""Adds a receiver operation for the specified output."""
self.consumers[output_index].append(operation)
def progress_metrics(self):
return beam_fn_api_pb2.Metrics.PTransform(
processed_elements=beam_fn_api_pb2.Metrics.PTransform.ProcessedElements(
measured=beam_fn_api_pb2.Metrics.PTransform.Measured(
total_time_spent=(
self.scoped_start_state.sampled_seconds()
+ self.scoped_process_state.sampled_seconds()
+ self.scoped_finish_state.sampled_seconds()),
# Multi-output operations should override this.
#.........这里部分代码省略.........