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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.
/*
* 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.cassandra.metrics;
import com.codahale.metrics.Gauge;
import static org.apache.cassandra.metrics.CassandraMetricsRegistry.Metrics;
public class MinMaxAvgMetric
{
private final MetricNameFactory factory;
private final String namePrefix;
final Gauge minGauge;
final Gauge maxGauge;
final Gauge avgGauge;
final Gauge stddevGauge;
final Gauge numSamplesGauge;
private long min;
private long max;
private long sum;
private long sumSquares;
private int numSamples;
public MinMaxAvgMetric(MetricNameFactory factory, String namePrefix)
{
this.factory = factory;
this.namePrefix = namePrefix;
minGauge = Metrics.register(factory.createMetricName(namePrefix + "Min"), () -> min);
maxGauge = Metrics.register(factory.createMetricName(namePrefix + "Max"), () -> max);
avgGauge = Metrics.register(factory.createMetricName(namePrefix + "Avg"), () -> numSamples > 0 ? ((double) sum) / numSamples : 0);
stddevGauge = Metrics.register(factory.createMetricName(namePrefix + "StdDev"), () -> stddev());
numSamplesGauge = Metrics.register(factory.createMetricName(namePrefix + "NumSamples"), () -> numSamples);
}
public void release()
{
Metrics.remove(factory.createMetricName(namePrefix + "Min"));
Metrics.remove(factory.createMetricName(namePrefix + "Max"));
Metrics.remove(factory.createMetricName(namePrefix + "Avg"));
Metrics.remove(factory.createMetricName(namePrefix + "StdDev"));
Metrics.remove(factory.createMetricName(namePrefix + "NumSamples"));
}
public void reset()
{
sum = 0;
sumSquares = 0;
max = Long.MIN_VALUE;
min = Long.MAX_VALUE;
numSamples = 0;
}
public void update(long value)
{
max = max > value ? max : value;
min = min < value ? min : value;
sum += value;
sumSquares += value * value;
numSamples++;
}
private Double stddev()
{
if (numSamples > 0)
{
double avgSquare = ((double) sumSquares) / numSamples;
double avg = ((double) sum) / numSamples;
return Math.sqrt(avgSquare - avg * avg);
}
else
{
return 0.0;
}
}
@Override
public String toString()
{
return "{" +
"min=" + min +
", max=" + max +
", avg=" + (sum * 1.0 / numSamples) +
", stdDev=" + stddev() +
", numSamples=" + numSamples +
'}';
}
}
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