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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 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 union = new HashSet();
    private final Set intersect = new HashSet();

    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 a, final List 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);
    }

}
 















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