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/**
* 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.classification.VisibleForTesting;
import org.apache.hadoop.metrics2.util.Quantile;
import java.text.DecimalFormat;
import static org.apache.hadoop.metrics2.lib.Interns.info;
/**
* Watches a stream of long values, maintaining online estimates of specific
* quantiles with provably low error bounds. Inverse quantiles are meant for
* highly accurate low-percentile (e.g. 1st, 5th) metrics.
* InverseQuantiles are used for metrics where higher the value better it is.
* ( eg: data transfer rate ).
* The 1st percentile here corresponds to the 99th inverse percentile metric,
* 5th percentile to 95th and so on.
*/
@InterfaceAudience.Public
@InterfaceStability.Evolving
public class MutableInverseQuantiles extends MutableQuantiles{
static class InversePercentile extends Quantile {
InversePercentile(double inversePercentile) {
super(inversePercentile/100, inversePercentile/1000);
}
}
@VisibleForTesting
public static final Quantile[] INVERSE_QUANTILES = {new InversePercentile(50),
new InversePercentile(25), new InversePercentile(10),
new InversePercentile(5), new InversePercentile(1)};
/**
* Instantiates a new {@link MutableInverseQuantiles} 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 intervalSecs rollover interval (in seconds) of the estimator
*/
public MutableInverseQuantiles(String name, String description, String sampleName,
String valueName, int intervalSecs) {
super(name, description, sampleName, valueName, intervalSecs);
}
/**
* Sets quantileInfo.
*
* @param ucName capitalized name of the metric
* @param uvName capitalized type of the values
* @param desc uncapitalized long-form textual description of the metric
* @param lvName uncapitalized type of the values
* @param df Number formatter for inverse percentile value
*/
void setQuantiles(String ucName, String uvName, String desc, String lvName, DecimalFormat df) {
for (int i = 0; i < INVERSE_QUANTILES.length; i++) {
double inversePercentile = 100 * (1 - INVERSE_QUANTILES[i].quantile);
String nameTemplate = ucName + df.format(inversePercentile) + "thInversePercentile" + uvName;
String descTemplate = df.format(inversePercentile) + " inverse percentile " + lvName
+ " with " + getInterval() + " second interval for " + desc;
addQuantileInfo(i, info(nameTemplate, descTemplate));
}
}
/**
* Returns the array of Inverse Quantiles declared in MutableInverseQuantiles.
*
* @return array of Inverse Quantiles
*/
public synchronized Quantile[] getQuantiles() {
return INVERSE_QUANTILES;
}
}
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