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HBASE-12133 Add FastLongHistogram for metric computation (Yi Deng)

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stack 2014-10-02 10:38:56 -07:00
parent e92036cd54
commit 0e1e64b821
3 changed files with 395 additions and 0 deletions
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63
hbase-common/src/main/java/org/apache/hadoop/hbase/util/AtomicUtils.java Normal file
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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.hbase.util;
import java.util.concurrent.atomic.AtomicLong;
import org.apache.hadoop.hbase.classification.InterfaceAudience;
/**
* Utilities related to atomic operations.
*/
@InterfaceAudience.Private
public class AtomicUtils {
/**
* Updates a AtomicLong which is supposed to maintain the minimum values. This method is not
* synchronized but is thread-safe.
*/
public static void updateMin(AtomicLong min, long value) {
while (true) {
long cur = min.get();
if (value >= cur) {
break;
}
if (min.compareAndSet(cur, value)) {
break;
}
}
}
/**
* Updates a AtomicLong which is supposed to maintain the maximum values. This method is not
* synchronized but is thread-safe.
*/
public static void updateMax(AtomicLong max, long value) {
while (true) {
long cur = max.get();
if (value <= cur) {
break;
}
if (max.compareAndSet(cur, value)) {
break;
}
}
}
}

233
hbase-common/src/main/java/org/apache/hadoop/hbase/util/FastLongHistogram.java Normal file
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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.hbase.util;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.atomic.AtomicLongArray;
import org.apache.hadoop.hbase.classification.InterfaceAudience;
import org.apache.hadoop.hbase.classification.InterfaceStability;
/**
* FastLongHistogram is a thread-safe class that estimate distribution of data and computes the
* quantiles.
*/
@InterfaceAudience.Public
@InterfaceStability.Evolving
public class FastLongHistogram {
/**
* Bins is a class containing a list of buckets(or bins) for estimation histogram of some data.
*/
private static class Bins {
private final AtomicLongArray counts;
// inclusive
private final long binsMin;
// exclusive
private final long binsMax;
private final long bins10XMax;
private final AtomicLong min = new AtomicLong(Long.MAX_VALUE);
private final AtomicLong max = new AtomicLong(0L);
// set to true when any of data has been inserted to the Bins. It is set after the counts are
// updated.
private final AtomicBoolean hasData = new AtomicBoolean(false);
/**
* The constructor for creating a Bins without any prior data.
*/
public Bins() {
this.counts = new AtomicLongArray(4);
this.binsMin = 0L;
this.binsMax = Long.MAX_VALUE;
this.bins10XMax = Long.MAX_VALUE;
}
/**
* The constructor for creating a Bins with last Bins.
* @param last the last Bins instance.
* @param quantiles the quantiles for creating the bins of the histogram.
*/
public Bins(Bins last, int numOfBins, double minQ, double maxQ) {
long[] values = last.getQuantiles(new double[] { minQ, maxQ });
long wd = values[1] - values[0] + 1;
// expand minQ and maxQ in two ends back assuming uniform distribution
this.binsMin = Math.max(0L, (long) (values[0] - wd * minQ));
long binsMax = (long) (values[1] + wd * (1 - maxQ)) + 1;
// make sure each of bins is at least of width 1
this.binsMax = Math.max(binsMax, this.binsMin + numOfBins);
this.bins10XMax = Math.max((long) (values[1] + (binsMax - 1) * 9), this.binsMax + 1);
this.counts = new AtomicLongArray(numOfBins + 3);
}
/**
* Adds a value to the histogram.
*/
public void add(long value, long count) {
AtomicUtils.updateMin(min, value);
AtomicUtils.updateMax(max, value);
if (value < this.binsMin) {
this.counts.addAndGet(0, count);
} else if (value > this.bins10XMax) {
this.counts.addAndGet(this.counts.length() - 1, count);
} else if (value >= this.binsMax) {
this.counts.addAndGet(this.counts.length() - 2, count);
} else {
// compute the position
int pos =
1 + (int) ((value - this.binsMin) * (this.counts.length() - 3) / (this.binsMax - this.binsMin));
this.counts.addAndGet(pos, count);
}
// hasData needs to be updated as last
this.hasData.set(true);
}
/**
* Computes the quantiles give the ratios.
* @param smooth set to true to have a prior on the distribution. Used for recreating the bins.
*/
public long[] getQuantiles(double[] quantiles) {
if (!this.hasData.get()) {
// No data yet.
return new long[quantiles.length];
}
// Make a snapshot of lowerCounter, higherCounter and bins.counts to counts.
// This is not synchronized, but since the counter are accumulating, the result is a good
// estimation of a snapshot.
long[] counts = new long[this.counts.length()];
long total = 0L;
for (int i = 0; i < this.counts.length(); i++) {
counts[i] = this.counts.get(i);
total += counts[i];
}
int rIndex = 0;
double qCount = total * quantiles[0];
long cum = 0L;
long[] res = new long[quantiles.length];
countsLoop: for (int i = 0; i < counts.length; i++) {
// mn and mx define a value range
long mn, mx;
if (i == 0) {
mn = this.min.get();
mx = this.binsMin;
} else if (i == counts.length - 1) {
mn = this.bins10XMax;
mx = this.max.get();
} else if (i == counts.length - 2) {
mn = this.binsMax;
mx = this.bins10XMax;
} else {
mn = this.binsMin + (i - 1) * (this.binsMax - this.binsMin) / (this.counts.length() - 3);
mx = this.binsMin + i * (this.binsMax - this.binsMin) / (this.counts.length() - 3);
}
if (mx < this.min.get()) {
continue;
}
if (mn > this.max.get()) {
break;
}
mn = Math.max(mn, this.min.get());
mx = Math.min(mx, this.max.get());
// lastCum/cum are the corresponding counts to mn/mx
double lastCum = cum;
cum += counts[i];
// fill the results for qCount is within current range.
while (qCount <= cum) {
if (cum == lastCum) {
res[rIndex] = mn;
} else {
res[rIndex] = (long) ((qCount - lastCum) * (mx - mn) / (cum - lastCum) + mn);
}
// move to next quantile
rIndex++;
if (rIndex >= quantiles.length) {
break countsLoop;
}
qCount = total * quantiles[rIndex];
}
}
// In case quantiles contains values >= 100%
for (; rIndex < quantiles.length; rIndex++) {
res[rIndex] = this.max.get();
}
return res;
}
}
// The bins counting values. It is replaced with a new one in calling of reset().
private volatile Bins bins = new Bins();
// The quantiles for creating a Bins with last Bins.
private final int numOfBins;
/**
* Constructor.
* @param numOfBins the number of bins for the histogram. A larger value results in more precise
* results but with lower efficiency, and vice versus.
*/
public FastLongHistogram(int numOfBins) {
this.numOfBins = numOfBins;
}
/**
* Constructor setting the bins assuming a uniform distribution within a range.
* @param numOfBins the number of bins for the histogram. A larger value results in more precise
* results but with lower efficiency, and vice versus.
* @param min lower bound of the region, inclusive.
* @param max higher bound of the region, inclusive.
*/
public FastLongHistogram(int numOfBins, long min, long max) {
this(numOfBins);
Bins bins = new Bins();
bins.add(min, 1);
bins.add(max, 1);
this.bins = new Bins(bins, numOfBins, 0.01, 0.99);
}
/**
* Adds a value to the histogram.
*/
public void add(long value, long count) {
this.bins.add(value, count);
}
/**
* Computes the quantiles give the ratios.
*/
public long[] getQuantiles(double[] quantiles) {
return this.bins.getQuantiles(quantiles);
}
/**
* Resets the histogram for new counting.
*/
public void reset() {
if (this.bins.hasData.get()) {
this.bins = new Bins(this.bins, numOfBins, 0.01, 0.99);
}
}
}

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hbase-common/src/test/java/org/apache/hadoop/hbase/util/TestFastLongHistogram.java Normal file
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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.hbase.util;
import java.util.Arrays;
import java.util.Random;
import org.apache.hadoop.hbase.SmallTests;
import org.junit.Assert;
import org.junit.Test;
import org.junit.experimental.categories.Category;
/**
* Testcases for FastLongHistogram.
*/
@Category({ SmallTests.class })
public class TestFastLongHistogram {
private static void doTestUniform(FastLongHistogram hist) {
long[] VALUES = { 0, 10, 20, 30, 40, 50 };
double[] qs = new double[VALUES.length];
for (int i = 0; i < qs.length; i++) {
qs[i] = (double) VALUES[i] / VALUES[VALUES.length - 1];
}
for (int i = 0; i < 10; i++) {
for (long v : VALUES) {
hist.add(v, 1);
}
long[] vals = hist.getQuantiles(qs);
System.out.println(Arrays.toString(vals));
for (int j = 0; j < qs.length; j++) {
Assert.assertTrue(j + "-th element org: " + VALUES[j] + ", act: " + vals[j],
Math.abs(vals[j] - VALUES[j]) <= 10);
}
hist.reset();
}
}
@Test
public void testUniform() {
FastLongHistogram hist = new FastLongHistogram(100, 0, 50);
doTestUniform(hist);
}
@Test
public void testAdaptionOfChange() {
// assumes the uniform distribution
FastLongHistogram hist = new FastLongHistogram(100, 0, 100);
Random rand = new Random();
for (int n = 0; n < 10; n++) {
for (int i = 0; i < 900; i++) {
hist.add(rand.nextInt(100), 1);
}
// add 10% outliers, this breaks the assumption, hope bin10xMax works
for (int i = 0; i < 100; i++) {
hist.add(1000 + rand.nextInt(100), 1);
}
long[] vals = hist.getQuantiles(new double[] { 0.25, 0.75, 0.95 });
System.out.println(Arrays.toString(vals));
if (n == 0) {
Assert.assertTrue("Out of possible value", vals[0] >= 0 && vals[0] <= 50);
Assert.assertTrue("Out of possible value", vals[1] >= 50 && vals[1] <= 100);
Assert.assertTrue("Out of possible value", vals[2] >= 900 && vals[2] <= 1100);
}
hist.reset();
}
}
@Test
public void testSameValues() {
FastLongHistogram hist = new FastLongHistogram(100);
hist.add(50, 100);
hist.reset();
doTestUniform(hist);
}
}