Source code for apache_beam.metrics.metric

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

User-facing classes for Metrics API.

The classes in this file allow users to define and use metrics to be collected
and displayed as part of their pipeline execution.

- Metrics - This class lets pipeline and transform writers create and access
    metric objects such as counters, distributions, etc.
# pytype: skip-file
# mypy: disallow-untyped-defs

import logging
from typing import TYPE_CHECKING
from typing import Dict
from typing import FrozenSet
from typing import Iterable
from typing import List
from typing import Optional
from typing import Set
from typing import Type
from typing import Union

from apache_beam.metrics import cells
from apache_beam.metrics.execution import MetricUpdater
from apache_beam.metrics.metricbase import Counter
from apache_beam.metrics.metricbase import Distribution
from apache_beam.metrics.metricbase import Gauge
from apache_beam.metrics.metricbase import MetricName

  from apache_beam.metrics.execution import MetricKey
  from apache_beam.metrics.metricbase import Metric

__all__ = ['Metrics', 'MetricsFilter']

_LOGGER = logging.getLogger(__name__)

[docs]class Metrics(object): """Lets users create/access metric objects during pipeline execution."""
[docs] @staticmethod def get_namespace(namespace): # type: (Union[Type, str]) -> str if isinstance(namespace, type): return '{}.{}'.format(namespace.__module__, namespace.__name__) elif isinstance(namespace, str): return namespace else: raise ValueError('Unknown namespace type')
[docs] @staticmethod def counter(namespace, name): # type: (Union[Type, str], str) -> Metrics.DelegatingCounter """Obtains or creates a Counter metric. Args: namespace: A class or string that gives the namespace to a metric name: A string that gives a unique name to a metric Returns: A Counter object. """ namespace = Metrics.get_namespace(namespace) return Metrics.DelegatingCounter(MetricName(namespace, name))
[docs] @staticmethod def distribution(namespace, name): # type: (Union[Type, str], str) -> Metrics.DelegatingDistribution """Obtains or creates a Distribution metric. Distribution metrics are restricted to integer-only distributions. Args: namespace: A class or string that gives the namespace to a metric name: A string that gives a unique name to a metric Returns: A Distribution object. """ namespace = Metrics.get_namespace(namespace) return Metrics.DelegatingDistribution(MetricName(namespace, name))
[docs] @staticmethod def gauge(namespace, name): # type: (Union[Type, str], str) -> Metrics.DelegatingGauge """Obtains or creates a Gauge metric. Gauge metrics are restricted to integer-only values. Args: namespace: A class or string that gives the namespace to a metric name: A string that gives a unique name to a metric Returns: A Distribution object. """ namespace = Metrics.get_namespace(namespace) return Metrics.DelegatingGauge(MetricName(namespace, name))
[docs] class DelegatingCounter(Counter): """Metrics Counter that Delegates functionality to MetricsEnvironment.""" def __init__(self, metric_name, process_wide=False): # type: (MetricName, bool) -> None super(Metrics.DelegatingCounter, self).__init__(metric_name) = MetricUpdater( # type: ignore[assignment] cells.CounterCell, metric_name, default_value=1, process_wide=process_wide)
[docs] class DelegatingDistribution(Distribution): """Metrics Distribution Delegates functionality to MetricsEnvironment.""" def __init__(self, metric_name): # type: (MetricName) -> None super(Metrics.DelegatingDistribution, self).__init__(metric_name) self.update = MetricUpdater(cells.DistributionCell, metric_name) # type: ignore[assignment]
[docs] class DelegatingGauge(Gauge): """Metrics Gauge that Delegates functionality to MetricsEnvironment.""" def __init__(self, metric_name): # type: (MetricName) -> None super(Metrics.DelegatingGauge, self).__init__(metric_name) self.set = MetricUpdater(cells.GaugeCell, metric_name) # type: ignore[assignment]
class MetricResults(object): COUNTERS = "counters" DISTRIBUTIONS = "distributions" GAUGES = "gauges" @staticmethod def _matches_name(filter, metric_key): # type: (MetricsFilter, MetricKey) -> bool if ((filter.namespaces and metric_key.metric.namespace not in filter.namespaces) or (filter.names and not in filter.names)): return False else: return True @staticmethod def _is_sub_list(needle, haystack): # type: (List[str], List[str]) -> bool """True iff `needle` is a sub-list of `haystack` (i.e. a contiguous slice of `haystack` exactly matches `needle`""" needle_len = len(needle) haystack_len = len(haystack) for i in range(0, haystack_len - needle_len + 1): if haystack[i:i + needle_len] == needle: return True return False @staticmethod def _matches_sub_path(actual_scope, filter_scope): # type: (str, str) -> bool """True iff the '/'-delimited pieces of filter_scope exist as a sub-list of the '/'-delimited pieces of actual_scope""" return MetricResults._is_sub_list( filter_scope.split('/'), actual_scope.split('/')) @staticmethod def _matches_scope(filter, metric_key): # type: (MetricsFilter, MetricKey) -> bool if not filter.steps: return True for step in filter.steps: if MetricResults._matches_sub_path(metric_key.step, step): return True return False @staticmethod def matches(filter, metric_key): # type: (Optional[MetricsFilter], MetricKey) -> bool if filter is None: return True if (MetricResults._matches_name(filter, metric_key) and MetricResults._matches_scope(filter, metric_key)): return True return False def query(self, filter=None): # type: (Optional[MetricsFilter]) -> Dict[str, List[MetricResults]] """Queries the runner for existing user metrics that match the filter. It should return a dictionary, with lists of each kind of metric, and each list contains the corresponding kind of MetricResult. Like so: { "counters": [MetricResult(counter_key, committed, attempted), ...], "distributions": [MetricResult(dist_key, committed, attempted), ...], "gauges": [] // Empty list if nothing matched the filter. } The committed / attempted values are DistributionResult / GaugeResult / int objects. """ raise NotImplementedError
[docs]class MetricsFilter(object): """Simple object to filter metrics results. This class is experimental. No backwards-compatibility guarantees. If filters by matching a result's step-namespace-name with three internal sets. No execution/matching logic is added to this object, so that it may be used to construct arguments as an RPC request. It is left for runners to implement matching logic by themselves. Note: This class only supports user defined metrics. """ def __init__(self): # type: () -> None self._names = set() # type: Set[str] self._namespaces = set() # type: Set[str] self._steps = set() # type: Set[str] @property def steps(self): # type: () -> FrozenSet[str] return frozenset(self._steps) @property def names(self): # type: () -> FrozenSet[str] return frozenset(self._names) @property def namespaces(self): # type: () -> FrozenSet[str] return frozenset(self._namespaces)
[docs] def with_metric(self, metric): # type: (Metric) -> MetricsFilter name = or '' namespace = metric.metric_name.namespace or '' return self.with_name(name).with_namespace(namespace)
[docs] def with_name(self, name): # type: (str) -> MetricsFilter return self.with_names([name])
[docs] def with_names(self, names): # type: (Iterable[str]) -> MetricsFilter if isinstance(names, str): raise ValueError('Names must be a collection, not a string') self._names.update(names) return self
[docs] def with_namespace(self, namespace): # type: (Union[Type, str]) -> MetricsFilter return self.with_namespaces([namespace])
[docs] def with_namespaces(self, namespaces): # type: (Iterable[Union[Type, str]]) -> MetricsFilter if isinstance(namespaces, str): raise ValueError('Namespaces must be an iterable, not a string') self._namespaces.update([Metrics.get_namespace(ns) for ns in namespaces]) return self
[docs] def with_step(self, step): # type: (str) -> MetricsFilter return self.with_steps([step])
[docs] def with_steps(self, steps): # type: (Iterable[str]) -> MetricsFilter if isinstance(steps, str): raise ValueError('Steps must be an iterable, not a string') self._steps.update(steps) return self