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https://github.com/nosqlbench/nosqlbench.git
synced 2025-02-25 18:55:28 -06:00
move stat bucket up to core api
This commit is contained in:
Jonathan Shook
@@ -1,50 +0,0 @@
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/*
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* Copyright (c) 2023 nosqlbench
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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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*/
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package io.nosqlbench.scenarios.simframe.stabilization;
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public class DoubleRing {
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private final double[] dbuf;
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private int count;
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private int idx;
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public DoubleRing(int size) {
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this.dbuf = new double[size];
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this.count = 0;
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}
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public DoubleRing(double[] samples) {
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this.dbuf=samples;
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this.count =samples.length;
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}
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public double push(double value) {
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double ejected = (count == dbuf.length) ? dbuf[idx] : Double.NaN;
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count += (count < dbuf.length) ? 1 : 0;
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dbuf[idx] = value;
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idx = (idx + 1) % dbuf.length;
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return ejected;
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}
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public int size() {
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return dbuf.length;
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}
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public int count() {
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return count;
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}
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}
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@@ -16,12 +16,12 @@
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package io.nosqlbench.scenarios.simframe.stabilization;
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import io.nosqlbench.nb.api.stats.StatBucket;
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import org.apache.logging.log4j.LogManager;
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import org.apache.logging.log4j.Logger;
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import java.util.Arrays;
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import java.util.List;
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import java.util.OptionalDouble;
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import java.util.function.DoubleSupplier;
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import java.util.function.Supplier;
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@@ -1,107 +0,0 @@
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/*
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* Copyright (c) 2023 nosqlbench
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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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*/
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package io.nosqlbench.scenarios.simframe.stabilization;
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import java.util.Objects;
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public final class StatBucket {
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DoubleRing ringbuf;
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private double mean;
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private double dSquared = 0.0d;
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public StatBucket() {
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this(10);
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}
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public StatBucket(int sampleWindow) {
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this.ringbuf = new DoubleRing(sampleWindow);
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}
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public StatBucket(double[] samples) {
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this.ringbuf = new DoubleRing(samples);
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}
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public StatBucket apply(double value) {
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// System.out.println("stat->" + value + " bucket:" + toString());
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double popped = ringbuf.push(value);
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if (ringbuf.count() == 1) {
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mean = value;
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dSquared = 0.0d;
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} else if (Double.isNaN(popped)) {
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var newMean = mean + ((value - mean) / ringbuf.count());
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var dSquaredIncrement = ((value - newMean) * (value - mean));
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// If this value is too small to be interpreted as a double it gets converted to
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// zero, which is not what we want. So we use the smallest possible double value
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if (dSquaredIncrement == 0) dSquaredIncrement = Double.MIN_VALUE;
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dSquared += dSquaredIncrement;
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mean = newMean;
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} else {
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var meanIncrement = (value - popped) / ringbuf.count();
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var newMean = mean + meanIncrement;
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var dSquaredIncrement = ((value - popped) * (value - newMean + popped - mean));
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// If this value is too small to be interpreted as a double it gets converted to
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// zero, which is not what we want. So we use the smallest possible double value
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if (dSquaredIncrement == 0) dSquaredIncrement = Double.MIN_VALUE;
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var newDSquared = this.dSquared + dSquaredIncrement;
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mean = newMean;
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dSquared = newDSquared;
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}
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return this;
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}
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public double variance() {
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double variance = dSquared / ringbuf.count();
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return (variance < 0) ? Math.abs(variance) : variance;
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}
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public double stddev() {
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return Math.sqrt(variance());
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}
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public int count() {
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return ringbuf.count();
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}
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public double mean() {
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return mean;
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}
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@Override
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public boolean equals(Object obj) {
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if (obj == this) return true;
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if (obj == null || obj.getClass() != this.getClass()) return false;
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var that = (StatBucket) obj;
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return this.ringbuf.count() == that.ringbuf.count() &&
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Double.doubleToLongBits(this.mean) == Double.doubleToLongBits(that.mean);
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}
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@Override
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public int hashCode() {
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return Objects.hash(ringbuf.count(), mean);
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}
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@Override
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public String toString() {
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return "StatBucket[" +
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"count=" + ringbuf.count() + ", " +
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"mean=" + mean + ", " +
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"stddev=" + stddev() + ']';
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}
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public boolean primed() {
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return this.count()== ringbuf.size();
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}
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}
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@@ -1,53 +0,0 @@
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/*
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* Copyright (c) 2023 nosqlbench
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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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*/
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package io.nosqlbench.scenarios.simframe.stats;
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import io.nosqlbench.scenarios.simframe.stabilization.StatBucket;
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import org.assertj.core.data.Offset;
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import org.junit.jupiter.api.Test;
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import static org.assertj.core.api.Assertions.assertThat;
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class StatBucketTest {
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@Test
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public void testStreamingMean() {
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var bucket = new StatBucket();
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bucket.apply(5.0d);
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assertThat(bucket.mean()).isCloseTo(5.0d,Offset.offset(0.001d));
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bucket.apply(10.0d);
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assertThat(bucket.mean()).isCloseTo(7.5d,Offset.offset(0.001d));
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bucket.apply(15.0d);
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assertThat(bucket.mean()).isCloseTo(10.0d,Offset.offset(0.001d));
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bucket.apply(20.0d);
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assertThat(bucket.mean()).isCloseTo(12.5d,Offset.offset(0.001d));
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}
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@Test
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public void testStreamingComputations() {
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double[] samples = new double[]{2,4,4,4,5,5,7,9};
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var bucket = new StatBucket(8);
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for (int i = 0; i < samples.length * 10; i++) {
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bucket.apply(samples[i%samples.length]);
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if (i>0&&(i%samples.length)==0) {
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assertThat(bucket.mean()).isCloseTo(5,Offset.offset(0.001d));
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assertThat(bucket.stddev()).isCloseTo(2.0,Offset.offset(0.001d));
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}
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}
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}
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}
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