/*
* 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.knn;
import com.google.common.collect.Lists;
import org.apache.mahout.common.distance.EuclideanDistanceMeasure;
import org.apache.mahout.knn.search.BruteSearch;
import org.apache.mahout.math.ConstantVector;
import org.apache.mahout.math.DenseMatrix;
import org.apache.mahout.math.Matrix;
import org.apache.mahout.math.Vector;
import org.apache.mahout.math.random.MultiNormal;
import org.apache.mahout.math.random.Sampler;
import org.apache.mahout.math.WeightedVector;
import java.util.List;
public class BruteSpeedCheck {
private static final int VECTOR_DIMENSION = 250;
private static final int REFERENCE_SIZE = 10000;
private static final int QUERY_SIZE = 100;
public static void main(String[] args) {
Sampler<Vector> rand = new MultiNormal(new ConstantVector(1, VECTOR_DIMENSION));
List<WeightedVector> referenceVectors = Lists.newArrayListWithExpectedSize(REFERENCE_SIZE);
for (int i = 0; i < REFERENCE_SIZE; ++i) {
referenceVectors.add(new WeightedVector(rand.sample(), 1, i));
}
System.out.printf("Generated reference matrix.\n");
List<WeightedVector> queryVectors = Lists.newArrayListWithExpectedSize(QUERY_SIZE);
for (int i = 0; i < QUERY_SIZE; ++i) {
queryVectors.add(new WeightedVector(rand.sample(), 1, i));
}
System.out.printf("Generated query matrix.\n");
for (int threads : new int[]{1, 2, 3, 4, 5, 6, 10, 20, 50}) {
for (int block : new int[]{1, 10, 50}) {
BruteSearch search = new BruteSearch(new EuclideanDistanceMeasure());
search.addAll(referenceVectors);
long t0 = System.nanoTime();
search.search(queryVectors, block, threads);
long t1 = System.nanoTime();
System.out.printf("%d\t%d\t%.2f\n", threads, block, (t1 - t0) / 1e9);
}
}
}
}