#
# 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
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
"""
DirectRunner implementation of MetricResults. It is in charge not only of
responding to queries of current metrics, but also of keeping the common
state consistent.
"""
from collections import defaultdict
import threading
from apache_beam.metrics.cells import CounterAggregator
from apache_beam.metrics.cells import DistributionAggregator
from apache_beam.metrics.execution import MetricKey
from apache_beam.metrics.execution import MetricResult
from apache_beam.metrics.metric import MetricResults
[docs]class DirectMetrics(MetricResults):
def __init__(self):
self._counters = defaultdict(
lambda: DirectMetric(CounterAggregator()))
self._distributions = defaultdict(
lambda: DirectMetric(DistributionAggregator()))
def _apply_operation(self, bundle, updates, op):
for k, v in updates.counters.items():
op(self._counters[k], bundle, v)
for k, v in updates.distributions.items():
op(self._distributions[k], bundle, v)
[docs] def commit_logical(self, bundle, updates):
op = lambda obj, bundle, update: obj.commit_logical(bundle, update)
self._apply_operation(bundle, updates, op)
[docs] def commit_physical(self, bundle, updates):
op = lambda obj, bundle, update: obj.commit_physical(bundle, update)
self._apply_operation(bundle, updates, op)
[docs] def update_physical(self, bundle, updates):
op = lambda obj, bundle, update: obj.update_physical(bundle, update)
self._apply_operation(bundle, updates, op)
[docs] def query(self, filter=None):
counters = [MetricResult(MetricKey(k.step, k.metric),
v.extract_committed(),
v.extract_latest_attempted())
for k, v in self._counters.items()
if self.matches(filter, k)]
distributions = [MetricResult(MetricKey(k.step, k.metric),
v.extract_committed(),
v.extract_latest_attempted())
for k, v in self._distributions.items()
if self.matches(filter, k)]
return {'counters': counters,
'distributions': distributions}
[docs]class DirectMetric(object):
""" Keeps a consistent state for a single metric.
It keeps track of the metric's physical and logical updates.
It's thread safe.
"""
def __init__(self, aggregator):
self.aggregator = aggregator
self._attempted_lock = threading.Lock()
self.finished_attempted = aggregator.zero()
self.inflight_attempted = {}
self._committed_lock = threading.Lock()
self.finished_committed = aggregator.zero()
[docs] def commit_logical(self, bundle, update):
with self._committed_lock:
self.finished_committed = self.aggregator.combine(update,
self.finished_committed)
[docs] def commit_physical(self, bundle, update):
with self._attempted_lock:
self.inflight_attempted[bundle] = update
self.finished_attempted = self.aggregator.combine(update,
self.finished_attempted)
del self.inflight_attempted[bundle]
[docs] def update_physical(self, bundle, update):
self.inflight_attempted[bundle] = update