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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
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*/
package hivemall.knn.similarity;
import static hivemall.utils.hadoop.WritableUtils.val;
import hivemall.knn.distance.HammingDistanceUDF;
import java.math.BigInteger;
import java.util.HashSet;
import java.util.List;
import java.util.Set;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDF;
import org.apache.hadoop.hive.ql.udf.UDFType;
import org.apache.hadoop.io.FloatWritable;
@Description(name = "jaccard_similarity",
value = "_FUNC_(A, B [,int k]) - Returns Jaccard similarity coefficient of A and B")
@UDFType(deterministic = true, stateful = false)
public final class JaccardIndexUDF extends UDF {
private final Set<Object> union = new HashSet<Object>();
private final Set<Object> intersect = new HashSet<Object>();
public FloatWritable evaluate(long a, long b) {
return evaluate(a, b, 128);
}
public FloatWritable evaluate(long a, long b, int k) {
int countMatches = k - HammingDistanceUDF.hammingDistance(a, b);
float jaccard = countMatches / (float) k;
return val(2.f * (jaccard - 0.5f));
}
public FloatWritable evaluate(String a, String b) {
return evaluate(a, b, 128);
}
public FloatWritable evaluate(String a, String b, int k) {
BigInteger ai = new BigInteger(a);
BigInteger bi = new BigInteger(b);
int countMatches = k - HammingDistanceUDF.hammingDistance(ai, bi);
float jaccard = countMatches / (float) k;
return val(2.f * (jaccard - 0.5f));
}
public FloatWritable evaluate(final List<String> a, final List<String> b) {
if (a == null && b == null) {
return new FloatWritable(1.f);
} else if (a == null || b == null) {
return new FloatWritable(0.f);
}
final int asize = a.size();
final int bsize = b.size();
if (asize == 0 && bsize == 0) {
return new FloatWritable(1.f);
} else if (asize == 0 || bsize == 0) {
return new FloatWritable(0.f);
}
union.addAll(a);
union.addAll(b);
float unionSize = union.size();
union.clear();
intersect.addAll(a);
intersect.retainAll(b);
float intersectSize = intersect.size();
intersect.clear();
return new FloatWritable(intersectSize / unionSize);
}
}