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Optional components of Mahout which generally support interaction with third party systems,
formats, APIs, etc.
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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.mahout.benchmark;
import static org.apache.mahout.benchmark.VectorBenchmarks.DENSE_FN_RAND;
import static org.apache.mahout.benchmark.VectorBenchmarks.DENSE_FN_SEQ;
import static org.apache.mahout.benchmark.VectorBenchmarks.DENSE_VECTOR;
import static org.apache.mahout.benchmark.VectorBenchmarks.RAND_FN_DENSE;
import static org.apache.mahout.benchmark.VectorBenchmarks.RAND_FN_SEQ;
import static org.apache.mahout.benchmark.VectorBenchmarks.RAND_SPARSE_VECTOR;
import static org.apache.mahout.benchmark.VectorBenchmarks.SEQ_FN_DENSE;
import static org.apache.mahout.benchmark.VectorBenchmarks.SEQ_FN_RAND;
import static org.apache.mahout.benchmark.VectorBenchmarks.SEQ_SPARSE_VECTOR;
import org.apache.mahout.benchmark.BenchmarkRunner.BenchmarkFnD;
import org.apache.mahout.common.distance.DistanceMeasure;
public class DistanceBenchmark {
private final VectorBenchmarks mark;
public DistanceBenchmark(VectorBenchmarks mark) {
this.mark = mark;
}
public void benchmark(final DistanceMeasure measure) {
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[0][mark.vIndex(i)], mark.vectors[0][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), DENSE_VECTOR);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[1][mark.vIndex(i)], mark.vectors[1][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), RAND_SPARSE_VECTOR);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[2][mark.vIndex(i)], mark.vectors[2][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), SEQ_SPARSE_VECTOR);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[0][mark.vIndex(i)], mark.vectors[1][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), DENSE_FN_RAND);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[0][mark.vIndex(i)], mark.vectors[2][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), DENSE_FN_SEQ);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[1][mark.vIndex(i)], mark.vectors[0][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), RAND_FN_DENSE);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[1][mark.vIndex(i)], mark.vectors[2][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), RAND_FN_SEQ);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[2][mark.vIndex(i)], mark.vectors[0][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), SEQ_FN_DENSE);
mark.printStats(mark.getRunner().benchmarkD(new BenchmarkFnD() {
@Override
public Double apply(Integer i) {
return measure.distance(mark.vectors[2][mark.vIndex(i)], mark.vectors[1][mark.vIndex(randIndex())]);
}
}), measure.getClass().getName(), SEQ_FN_RAND);
}
}