#
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# 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
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# http://www.apache.org/licenses/LICENSE-2.0
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# distributed under the License is distributed on an "AS IS" BASIS,
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"""
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
if TYPE_CHECKING:
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)
self.inc = 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 metric_key.metric.name 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 = metric.metric_name.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