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Python MetricsContainer.reset方法代码示例

本文整理汇总了Python中apache_beam.metrics.execution.MetricsContainer.reset方法的典型用法代码示例。如果您正苦于以下问题:Python MetricsContainer.reset方法的具体用法?Python MetricsContainer.reset怎么用?Python MetricsContainer.reset使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在apache_beam.metrics.execution.MetricsContainer的用法示例。


在下文中一共展示了MetricsContainer.reset方法的1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: Operation

# 需要导入模块: from apache_beam.metrics.execution import MetricsContainer [as 别名]
# 或者: from apache_beam.metrics.execution.MetricsContainer import reset [as 别名]
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.........
开发者ID:eralmas7,项目名称:beam,代码行数:103,代码来源:operations.py


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