/**
* 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.mahout.benchmark;
import org.apache.commons.cli2.CommandLine;
import org.apache.commons.cli2.Group;
import org.apache.commons.cli2.Option;
import org.apache.commons.cli2.OptionException;
import org.apache.commons.cli2.builder.ArgumentBuilder;
import org.apache.commons.cli2.builder.DefaultOptionBuilder;
import org.apache.commons.cli2.builder.GroupBuilder;
import org.apache.commons.cli2.commandline.Parser;
import org.apache.commons.lang3.StringUtils;
import org.apache.mahout.benchmark.BenchmarkRunner.BenchmarkFn;
import org.apache.mahout.common.CommandLineUtil;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.common.TimingStatistics;
import org.apache.mahout.common.commandline.DefaultOptionCreator;
import org.apache.mahout.common.distance.ChebyshevDistanceMeasure;
import org.apache.mahout.common.distance.CosineDistanceMeasure;
import org.apache.mahout.common.distance.EuclideanDistanceMeasure;
import org.apache.mahout.common.distance.ManhattanDistanceMeasure;
import org.apache.mahout.common.distance.MinkowskiDistanceMeasure;
import org.apache.mahout.common.distance.SquaredEuclideanDistanceMeasure;
import org.apache.mahout.common.distance.TanimotoDistanceMeasure;
import org.apache.mahout.math.DenseVector;
import org.apache.mahout.math.RandomAccessSparseVector;
import org.apache.mahout.math.SequentialAccessSparseVector;
import org.apache.mahout.math.Vector;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.io.IOException;
import java.text.DecimalFormat;
import java.util.ArrayList;
import java.util.BitSet;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import java.util.Random;
import java.util.concurrent.TimeUnit;
import java.util.regex.Pattern;
public class VectorBenchmarks {
private static final int MAX_TIME_MS = 5000;
private static final int LEAD_TIME_MS = 15000;
public static final String CLUSTERS = "Clusters";
public static final String CREATE_INCREMENTALLY = "Create (incrementally)";
public static final String CREATE_COPY = "Create (copy)";
public static final String DENSE_FN_SEQ = "Dense.fn(Seq)";
public static final String RAND_FN_DENSE = "Rand.fn(Dense)";
public static final String SEQ_FN_RAND = "Seq.fn(Rand)";
public static final String RAND_FN_SEQ = "Rand.fn(Seq)";
public static final String SEQ_FN_DENSE = "Seq.fn(Dense)";
public static final String DENSE_FN_RAND = "Dense.fn(Rand)";
public static final String SEQ_SPARSE_VECTOR = "SeqSparseVector";
public static final String RAND_SPARSE_VECTOR = "RandSparseVector";
public static final String DENSE_VECTOR = "DenseVector";
private static final Logger log = LoggerFactory.getLogger(VectorBenchmarks.class);
private static final Pattern TAB_NEWLINE_PATTERN = Pattern.compile("[\n\t]");
private static final String[] EMPTY = new String[0];
private static final DecimalFormat DF = new DecimalFormat("#.##");
/* package private */
final Vector[][] vectors;
final Vector[] clusters;
final int cardinality;
final int numNonZeros;
final int numVectors;
final int numClusters;
final int loop = Integer.MAX_VALUE;
final int opsPerUnit;
final long maxTimeUsec;
final long leadTimeUsec;
private final List<Vector> randomVectors = new ArrayList<>();
private final List<int[]> randomVectorIndices = new ArrayList<>();
private final List<double[]> randomVectorValues = new ArrayList<>();
private final Map<String, Integer> implType = new HashMap<>();
private final Map<String, List<String[]>> statsMap = new HashMap<>();
private final BenchmarkRunner runner;
private final Random r = RandomUtils.getRandom();
public VectorBenchmarks(int cardinality, int numNonZeros, int numVectors, int numClusters,
int opsPerUnit) {
runner = new BenchmarkRunner(LEAD_TIME_MS, MAX_TIME_MS);
maxTimeUsec = TimeUnit.MILLISECONDS.toNanos(MAX_TIME_MS);
leadTimeUsec = TimeUnit.MILLISECONDS.toNanos(LEAD_TIME_MS);
this.cardinality = cardinality;
this.numNonZeros = numNonZeros;
this.numVectors = numVectors;
this.numClusters = numClusters;
this.opsPerUnit = opsPerUnit;
setUpVectors(cardinality, numNonZeros, numVectors);
vectors = new Vector[3][numVectors];
clusters = new Vector[numClusters];
}
private void setUpVectors(int cardinality, int numNonZeros, int numVectors) {
for (int i = 0; i < numVectors; i++) {
Vector v = new SequentialAccessSparseVector(cardinality, numNonZeros); // sparsity!
BitSet featureSpace = new BitSet(cardinality);
int[] indexes = new int[numNonZeros];
double[] values = new double[numNonZeros];
int j = 0;
while (j < numNonZeros) {
double value = r.nextGaussian();
int index = r.nextInt(cardinality);
if (!featureSpace.get(index) && value != 0) {
featureSpace.set(index);
indexes[j] = index;
values[j++] = value;
v.set(index, value);
}
}
randomVectorIndices.add(indexes);
randomVectorValues.add(values);
randomVectors.add(v);
}
}
void printStats(TimingStatistics stats, String benchmarkName, String implName, String content) {
printStats(stats, benchmarkName, implName, content, 1);
}
void printStats(TimingStatistics stats, String benchmarkName, String implName) {
printStats(stats, benchmarkName, implName, "", 1);
}
private void printStats(TimingStatistics stats, String benchmarkName, String implName,
String content, int multiplier) {
float speed = multiplier * stats.getNCalls() * (numNonZeros * 1000.0f * 12 / stats.getSumTime());
float opsPerSec = stats.getNCalls() * 1000000000.0f / stats.getSumTime();
log.info("{} {} \n{} {} \nOps = {} Units/sec\nIOps = {} MBytes/sec", benchmarkName,
implName, content, stats.toString(), DF.format(opsPerSec), DF.format(speed));
if (!implType.containsKey(implName)) {
implType.put(implName, implType.size());
}
int implId = implType.get(implName);
if (!statsMap.containsKey(benchmarkName)) {
statsMap.put(benchmarkName, new ArrayList<String[]>());
}
List<String[]> implStats = statsMap.get(benchmarkName);
while (implStats.size() < implId + 1) {
implStats.add(EMPTY);
}
implStats.set(
implId,
TAB_NEWLINE_PATTERN.split(stats + "\tSpeed = " + DF.format(opsPerSec) + " /sec\tRate = "
+ DF.format(speed) + " MB/s"));
}
public void createData() {
for (int i = 0; i < Math.max(numVectors, numClusters); ++i) {
vectors[0][vIndex(i)] = new DenseVector(randomVectors.get(vIndex(i)));
vectors[1][vIndex(i)] = new RandomAccessSparseVector(randomVectors.get(vIndex(i)));
vectors[2][vIndex(i)] = new SequentialAccessSparseVector(randomVectors.get(vIndex(i)));
if (numClusters > 0) {
clusters[cIndex(i)] = new RandomAccessSparseVector(randomVectors.get(vIndex(i)));
}
}
}
public void createBenchmark() {
printStats(runner.benchmark(new BenchmarkFn() {
@Override
public Boolean apply(Integer i) {
vectors[0][vIndex(i)] = new DenseVector(randomVectors.get(vIndex(i)));
return depends(vectors[0][vIndex(i)]);
}
}), CREATE_COPY, DENSE_VECTOR);
printStats(runner.benchmark(new BenchmarkFn() {
@Override
public Boolean apply(Integer i) {
vectors[1][vIndex(i)] = new RandomAccessSparseVector(randomVectors.get(vIndex(i)));
return depends(vectors[1][vIndex(i)]);
}
}), CREATE_COPY, RAND_SPARSE_VECTOR);
printStats(runner.benchmark(new BenchmarkFn() {
@Override
public Boolean apply(Integer i) {
vectors[2][vIndex(i)] = new SequentialAccessSparseVector(randomVectors.get(vIndex(i)));
return depends(vectors[2][vIndex(i)]);
}
}), CREATE_COPY, SEQ_SPARSE_VECTOR);
if (numClusters > 0) {
printStats(runner.benchmark(new BenchmarkFn() {
@Override
public Boolean apply(Integer i) {
clusters[cIndex(i)] = new RandomAccessSparseVector(randomVectors.get(vIndex(i)));
return depends(clusters[cIndex(i)]);
}
}), CREATE_COPY, CLUSTERS);
}
}
private boolean buildVectorIncrementally(TimingStatistics stats, int randomIndex, Vector v, boolean useSetQuick) {
int[] indexes = randomVectorIndices.get(randomIndex);
double[] values = randomVectorValues.get(randomIndex);
List<Integer> randomOrder = new ArrayList<>();
for (int i = 0; i < indexes.length; i++) {
randomOrder.add(i);
}
Collections.shuffle(randomOrder);
int[] permutation = new int[randomOrder.size()];
for (int i = 0; i < randomOrder.size(); i++) {
permutation[i] = randomOrder.get(i);
}
TimingStatistics.Call call = stats.newCall(leadTimeUsec);
if (useSetQuick) {
for (int i : permutation) {
v.setQuick(indexes[i], values[i]);
}
} else {
for (int i : permutation) {
v.set(indexes[i], values[i]);
}
}
return call.end(maxTimeUsec);
}
public void incrementalCreateBenchmark() {
TimingStatistics stats = new TimingStatistics();
for (int i = 0; i < loop; i++) {
vectors[0][vIndex(i)] = new DenseVector(cardinality);
if (buildVectorIncrementally(stats, vIndex(i), vectors[0][vIndex(i)], false)) {
break;
}
}
printStats(stats, CREATE_INCREMENTALLY, DENSE_VECTOR);
stats = new TimingStatistics();
for (int i = 0; i < loop; i++) {
vectors[1][vIndex(i)] = new RandomAccessSparseVector(cardinality);
if (buildVectorIncrementally(stats, vIndex(i), vectors[1][vIndex(i)], false)) {
break;
}
}
printStats(stats, CREATE_INCREMENTALLY, RAND_SPARSE_VECTOR);
stats = new TimingStatistics();
for (int i = 0; i < loop; i++) {
vectors[2][vIndex(i)] = new SequentialAccessSparseVector(cardinality);
if (buildVectorIncrementally(stats, vIndex(i), vectors[2][vIndex(i)], false)) {
break;
}
}
printStats(stats, CREATE_INCREMENTALLY, SEQ_SPARSE_VECTOR);
if (numClusters > 0) {
stats = new TimingStatistics();
for (int i = 0; i < loop; i++) {
clusters[cIndex(i)] = new RandomAccessSparseVector(cardinality);
if (buildVectorIncrementally(stats, vIndex(i), clusters[cIndex(i)], false)) {
break;
}
}
printStats(stats, CREATE_INCREMENTALLY, CLUSTERS);
}
}
public int vIndex(int i) {
return i % numVectors;
}
public int cIndex(int i) {
return i % numClusters;
}
public static void main(String[] args) throws IOException {
DefaultOptionBuilder obuilder = new DefaultOptionBuilder();
ArgumentBuilder abuilder = new ArgumentBuilder();
GroupBuilder gbuilder = new GroupBuilder();
Option vectorSizeOpt = obuilder
.withLongName("vectorSize")
.withRequired(false)
.withArgument(abuilder.withName("vs").withDefault(1000000).create())
.withDescription("Cardinality of the vector. Default: 1000000").withShortName("vs").create();
Option numNonZeroOpt = obuilder
.withLongName("numNonZero")
.withRequired(false)
.withArgument(abuilder.withName("nz").withDefault(1000).create())
.withDescription("Size of the vector. Default: 1000").withShortName("nz").create();
Option numVectorsOpt = obuilder
.withLongName("numVectors")
.withRequired(false)
.withArgument(abuilder.withName("nv").withDefault(25).create())
.withDescription("Number of Vectors to create. Default: 25").withShortName("nv").create();
Option numClustersOpt = obuilder
.withLongName("numClusters")
.withRequired(false)
.withArgument(abuilder.withName("nc").withDefault(0).create())
.withDescription("Number of clusters to create. Set to non zero to run cluster benchmark. Default: 0")
.withShortName("nc").create();
Option numOpsOpt = obuilder
.withLongName("numOps")
.withRequired(false)
.withArgument(abuilder.withName("numOps").withDefault(10).create())
.withDescription(
"Number of operations to do per timer. "
+ "E.g In distance measure, the distance is calculated numOps times"
+ " and the total time is measured. Default: 10").withShortName("no").create();
Option helpOpt = DefaultOptionCreator.helpOption();
Group group = gbuilder.withName("Options").withOption(vectorSizeOpt).withOption(numNonZeroOpt)
.withOption(numVectorsOpt).withOption(numOpsOpt).withOption(numClustersOpt).withOption(helpOpt).create();
try {
Parser parser = new Parser();
parser.setGroup(group);
CommandLine cmdLine = parser.parse(args);
if (cmdLine.hasOption(helpOpt)) {
CommandLineUtil.printHelpWithGenericOptions(group);
return;
}
int cardinality = 1000000;
if (cmdLine.hasOption(vectorSizeOpt)) {
cardinality = Integer.parseInt((String) cmdLine.getValue(vectorSizeOpt));
}
int numClusters = 0;
if (cmdLine.hasOption(numClustersOpt)) {
numClusters = Integer.parseInt((String) cmdLine.getValue(numClustersOpt));
}
int numNonZero = 1000;
if (cmdLine.hasOption(numNonZeroOpt)) {
numNonZero = Integer.parseInt((String) cmdLine.getValue(numNonZeroOpt));
}
int numVectors = 25;
if (cmdLine.hasOption(numVectorsOpt)) {
numVectors = Integer.parseInt((String) cmdLine.getValue(numVectorsOpt));
}
int numOps = 10;
if (cmdLine.hasOption(numOpsOpt)) {
numOps = Integer.parseInt((String) cmdLine.getValue(numOpsOpt));
}
VectorBenchmarks mark = new VectorBenchmarks(cardinality, numNonZero, numVectors, numClusters, numOps);
runBenchmark(mark);
// log.info("\n{}", mark);
log.info("\n{}", mark.asCsvString());
} catch (OptionException e) {
CommandLineUtil.printHelp(group);
}
}
private static void runBenchmark(VectorBenchmarks mark) throws IOException {
// Required to set up data.
mark.createData();
mark.createBenchmark();
if (mark.cardinality < 200000) {
// Too slow.
mark.incrementalCreateBenchmark();
}
new CloneBenchmark(mark).benchmark();
new DotBenchmark(mark).benchmark();
new PlusBenchmark(mark).benchmark();
new MinusBenchmark(mark).benchmark();
new TimesBenchmark(mark).benchmark();
new SerializationBenchmark(mark).benchmark();
DistanceBenchmark distanceBenchmark = new DistanceBenchmark(mark);
distanceBenchmark.benchmark(new CosineDistanceMeasure());
distanceBenchmark.benchmark(new SquaredEuclideanDistanceMeasure());
distanceBenchmark.benchmark(new EuclideanDistanceMeasure());
distanceBenchmark.benchmark(new ManhattanDistanceMeasure());
distanceBenchmark.benchmark(new TanimotoDistanceMeasure());
distanceBenchmark.benchmark(new ChebyshevDistanceMeasure());
distanceBenchmark.benchmark(new MinkowskiDistanceMeasure());
if (mark.numClusters > 0) {
ClosestCentroidBenchmark centroidBenchmark = new ClosestCentroidBenchmark(mark);
centroidBenchmark.benchmark(new CosineDistanceMeasure());
centroidBenchmark.benchmark(new SquaredEuclideanDistanceMeasure());
centroidBenchmark.benchmark(new EuclideanDistanceMeasure());
centroidBenchmark.benchmark(new ManhattanDistanceMeasure());
centroidBenchmark.benchmark(new TanimotoDistanceMeasure());
centroidBenchmark.benchmark(new ChebyshevDistanceMeasure());
centroidBenchmark.benchmark(new MinkowskiDistanceMeasure());
}
}
private String asCsvString() {
List<String> keys = new ArrayList<>(statsMap.keySet());
Collections.sort(keys);
Map<Integer,String> implMap = new HashMap<>();
for (Entry<String,Integer> e : implType.entrySet()) {
implMap.put(e.getValue(), e.getKey());
}
StringBuilder sb = new StringBuilder(1000);
for (String benchmarkName : keys) {
int i = 0;
for (String[] stats : statsMap.get(benchmarkName)) {
if (stats.length < 8) {
continue;
}
sb.append(benchmarkName).append(',');
sb.append(implMap.get(i++)).append(',');
sb.append(stats[7].trim().split("=|/")[1].trim());
sb.append('\n');
}
}
sb.append('\n');
return sb.toString();
}
@Override
public String toString() {
int pad = 24;
StringBuilder sb = new StringBuilder(1000);
sb.append(StringUtils.rightPad("BenchMarks", pad));
for (int i = 0; i < implType.size(); i++) {
for (Entry<String,Integer> e : implType.entrySet()) {
if (e.getValue() == i) {
sb.append(StringUtils.rightPad(e.getKey(), pad).substring(0, pad));
break;
}
}
}
sb.append('\n');
List<String> keys = new ArrayList<>(statsMap.keySet());
Collections.sort(keys);
for (String benchmarkName : keys) {
List<String[]> implTokenizedStats = statsMap.get(benchmarkName);
int maxStats = 0;
for (String[] stat : implTokenizedStats) {
maxStats = Math.max(maxStats, stat.length);
}
for (int i = 0; i < maxStats; i++) {
boolean printedName = false;
for (String[] stats : implTokenizedStats) {
if (i == 0 && !printedName) {
sb.append(StringUtils.rightPad(benchmarkName, pad));
printedName = true;
} else if (!printedName) {
printedName = true;
sb.append(StringUtils.rightPad("", pad));
}
if (stats.length > i) {
sb.append(StringUtils.rightPad(stats[i], pad));
} else {
sb.append(StringUtils.rightPad("", pad));
}
}
sb.append('\n');
}
sb.append('\n');
}
return sb.toString();
}
public BenchmarkRunner getRunner() {
return runner;
}
}