apache_beam.metrics.cells module

This file contains metric cell classes. A metric cell is used to accumulate in-memory changes to a metric. It represents a specific metric in a single context.

class apache_beam.metrics.cells.MetricAggregator

Bases: object

For internal use only; no backwards-compatibility guarantees.

Base interface for aggregating metric data during pipeline execution.

combine(x, y)

identity_element()

Returns the identical element of an Aggregation.

For the identity element, it must hold that: Aggregator.combine(any_element, identity_element) == any_element.

result(x)

class apache_beam.metrics.cells.MetricCell

Bases: object

For internal use only; no backwards-compatibility guarantees.

Accumulates in-memory changes to a metric.

A MetricCell represents a specific metric in a single context and bundle. All subclasses must be thread safe, as these are used in the pipeline runners, and may be subject to parallel/concurrent updates. Cells should only be used directly within a runner.

get_cumulative()

reset()

to_runner_api_monitoring_info(name, transform_id)

to_runner_api_monitoring_info_impl(name, transform_id)

update(value)

class apache_beam.metrics.cells.MetricCellFactory: Bases: object

class apache_beam.metrics.cells.DistributionResult(data)

Bases: object

The result of a Distribution metric.

property count

property max

property mean

Returns the float mean of the distribution.

If the distribution contains no elements, it returns None.

property min

property sum

class apache_beam.metrics.cells.GaugeResult(data)

Bases: object

property timestamp

property value