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91f8b6da38
This CL also adds IncrementableMetric#reset() methods to allow resetting the value and start timestamp of IncrementableMetrics. This is necessary because some backends, like Stackdriver, use non-monotonic changes in cumulative metric values to detect timeseries restarts. Tracking and re-setting the start timestamp allows users to track mostly monotonic metrics which may have non-monotonic discontinuities. See https://cloud.google.com/monitoring/api/ref_v3/rest/v3/TimeSeries#Point for more details. ------------- Created by MOE: https://github.com/google/moe MOE_MIGRATED_REVID=130795229
91 lines
3.2 KiB
Java
91 lines
3.2 KiB
Java
// Copyright 2016 The Domain Registry Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package google.registry.monitoring.metrics;
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import com.google.common.annotations.VisibleForTesting;
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import com.google.common.base.Supplier;
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import com.google.common.collect.ImmutableList;
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import com.google.common.collect.ImmutableMap;
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import com.google.common.collect.ImmutableSet;
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import google.registry.monitoring.metrics.MetricSchema.Kind;
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import java.util.Map.Entry;
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import javax.annotation.concurrent.ThreadSafe;
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import org.joda.time.Instant;
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/**
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* A metric whose value is computed at sample-time.
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*
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* <p>This pattern works well for gauge-like metrics, such as CPU usage, memory usage, and file
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* descriptor counts.
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*
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* <p>The {@link MetricPoint#interval()} of values of instances of this metric will always have a
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* start time equal to the end time, since the metric value represents a point-in-time snapshot with
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* no relationship to prior values.
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*/
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@ThreadSafe
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public final class VirtualMetric<V> extends AbstractMetric<V> {
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private final Supplier<ImmutableMap<ImmutableList<String>, V>> valuesSupplier;
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/**
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* Local cache of the count of values so that we don't have to evaluate the callback function to
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* get the metric's cardinality.
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*/
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private volatile int cardinality;
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VirtualMetric(
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String name,
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String description,
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String valueDisplayName,
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ImmutableSet<LabelDescriptor> labels,
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Supplier<ImmutableMap<ImmutableList<String>, V>> valuesSupplier,
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Class<V> valueClass) {
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super(name, description, valueDisplayName, Kind.GAUGE, labels, valueClass);
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this.valuesSupplier = valuesSupplier;
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}
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/**
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* Returns a snapshot of the metric's values. This will evaluate the stored callback function. The
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* timestamp for each MetricPoint will be the current time.
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*/
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@Override
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public ImmutableList<MetricPoint<V>> getTimestampedValues() {
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return getTimestampedValues(Instant.now());
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}
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/**
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* Returns the cached value of the cardinality of this metric. The cardinality is computed when
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* the metric is evaluated. If the metric has never been evaluated, the cardinality is zero.
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*/
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@Override
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public int getCardinality() {
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return cardinality;
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}
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@VisibleForTesting
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ImmutableList<MetricPoint<V>> getTimestampedValues(Instant timestamp) {
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ImmutableMap<ImmutableList<String>, V> values = valuesSupplier.get();
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ImmutableList.Builder<MetricPoint<V>> metricPoints = ImmutableList.builder();
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for (Entry<ImmutableList<String>, V> entry : values.entrySet()) {
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metricPoints.add(
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MetricPoint.create(this, entry.getKey(), timestamp, timestamp, entry.getValue()));
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}
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cardinality = values.size();
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return metricPoints.build();
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}
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}
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