/**
* 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.
*/
package org.apache.hadoop.metrics2.lib;
import org.apache.hadoop.classification.InterfaceAudience;
import org.apache.hadoop.classification.InterfaceStability;
import org.apache.hadoop.metrics2.MetricHistogram;
import org.apache.hadoop.metrics2.MetricsExecutor;
import org.apache.hadoop.metrics2.MetricsRecordBuilder;
import org.apache.hadoop.metrics2.util.MetricQuantile;
import org.apache.hadoop.metrics2.util.MetricSampleQuantiles;
import java.io.IOException;
import java.util.Map;
import java.util.concurrent.TimeUnit;
/**
* Watches a stream of long values, maintaining online estimates of specific quantiles with provably
* low error bounds. This is particularly useful for accurate high-percentile (e.g. 95th, 99th)
* latency metrics.
*/
@InterfaceAudience.Public
@InterfaceStability.Evolving
public class MetricMutableQuantiles extends MetricMutable implements MetricHistogram {
static final MetricQuantile[] quantiles = {new MetricQuantile(0.50, 0.050),
new MetricQuantile(0.75, 0.025), new MetricQuantile(0.90, 0.010),
new MetricQuantile(0.95, 0.005), new MetricQuantile(0.99, 0.001)};
static final String[] quantilesSuffix = {"_Median",
"_75th_percentile", "_90th_percentile",
"_95th_percentile", "_99th_percentile"};
private final int interval;
private MetricSampleQuantiles estimator;
private long previousCount = 0;
private MetricsExecutor executor;
protected Map<MetricQuantile, Long> previousSnapshot = null;
/**
* Instantiates a new {@link MetricMutableQuantiles} for a metric that rolls itself over on the
* specified time interval.
*
* @param name of the metric
* @param description long-form textual description of the metric
* @param sampleName type of items in the stream (e.g., "Ops")
* @param valueName type of the values
* @param interval rollover interval (in seconds) of the estimator
*/
public MetricMutableQuantiles(String name, String description, String sampleName,
String valueName, int interval) {
super(name, description);
estimator = new MetricSampleQuantiles(quantiles);
executor = new MetricsExecutorImpl();
this.interval = interval;
executor.getExecutor().scheduleAtFixedRate(new RolloverSample(this),
interval,
interval,
TimeUnit.SECONDS);
}
public MetricMutableQuantiles(String name, String description) {
this(name, description, "Ops", "", 60);
}
@Override
public synchronized void snapshot(MetricsRecordBuilder builder, boolean all) {
if (all || changed()) {
builder.addCounter(name + "NumOps", description, previousCount);
for (int i = 0; i < quantiles.length; i++) {
long newValue = 0;
// If snapshot is null, we failed to update since the window was empty
if (previousSnapshot != null) {
newValue = previousSnapshot.get(quantiles[i]);
}
builder.addGauge(name + quantilesSuffix[i], description, newValue);
}
if (changed()) {
clearChanged();
}
}
}
public synchronized void add(long value) {
estimator.insert(value);
}
public int getInterval() {
return interval;
}
/** Runnable used to periodically roll over the internal {@link org.apache.hadoop.metrics2.util.MetricSampleQuantiles} every interval. */
private static class RolloverSample implements Runnable {
MetricMutableQuantiles parent;
public RolloverSample(MetricMutableQuantiles parent) {
this.parent = parent;
}
@Override
public void run() {
synchronized (parent) {
try {
parent.previousCount = parent.estimator.getCount();
parent.previousSnapshot = parent.estimator.snapshot();
} catch (IOException e) {
// Couldn't get a new snapshot because the window was empty
parent.previousCount = 0;
parent.previousSnapshot = null;
}
parent.estimator.clear();
}
parent.setChanged();
}
}
}