/* * 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.distance; import hivemall.knn.similarity.CosineSimilarityUDF; import hivemall.utils.hadoop.HiveUtils; import java.util.Arrays; import java.util.List; import org.apache.hadoop.hive.ql.exec.Description; import org.apache.hadoop.hive.ql.exec.UDFArgumentException; import org.apache.hadoop.hive.ql.metadata.HiveException; import org.apache.hadoop.hive.ql.udf.UDFType; import org.apache.hadoop.hive.ql.udf.generic.GenericUDF; import org.apache.hadoop.hive.serde2.objectinspector.ListObjectInspector; import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector; import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory; import org.apache.hadoop.io.FloatWritable; /** * @link http://en.wikipedia.org/wiki/Cosine_similarity */ //@formatter:off @Description(name = "cosine_distance", value = "_FUNC_(ftvec1, ftvec2) - Returns a cosine distance of the given two vectors", extended = "WITH docs as (\n" + " select 1 as docid, array('apple:1.0', 'orange:2.0', 'banana:1.0', 'kuwi:0') as features\n" + " union all\n" + " select 2 as docid, array('apple:1.0', 'orange:0', 'banana:2.0', 'kuwi:1.0') as features\n" + " union all\n" + " select 3 as docid, array('apple:2.0', 'orange:0', 'banana:2.0', 'kuwi:1.0') as features\n" + ") \n" + "select\n" + " l.docid as doc1,\n" + " r.docid as doc2,\n" + " cosine_distance(l.features, r.features) as distance,\n" + " distance2similarity(cosine_distance(l.features, r.features)) as similarity\n" + "from \n" + " docs l\n" + " CROSS JOIN docs r\n" + "where\n" + " l.docid != r.docid\n" + "order by \n" + " doc1 asc,\n" + " distance asc;\n" + "\n" + "doc1 doc2 distance similarity\n" + "1 3 0.45566893 0.6869694\n" + "1 2 0.5 0.6666667\n" + "2 3 0.04742068 0.95472616\n" + "2 1 0.5 0.6666667\n" + "3 2 0.04742068 0.95472616\n" + "3 1 0.45566893 0.6869694") @UDFType(deterministic = true, stateful = false) //@formatter:on public final class CosineDistanceUDF extends GenericUDF { private ListObjectInspector arg0ListOI, arg1ListOI; @Override public ObjectInspector initialize(ObjectInspector[] argOIs) throws UDFArgumentException { if (argOIs.length != 2) { throw new UDFArgumentException("cosine_distance takes 2 arguments"); } this.arg0ListOI = HiveUtils.asListOI(argOIs[0]); this.arg1ListOI = HiveUtils.asListOI(argOIs[1]); return PrimitiveObjectInspectorFactory.writableFloatObjectInspector; } @Override public FloatWritable evaluate(DeferredObject[] arguments) throws HiveException { List<String> ftvec1 = HiveUtils.asStringList(arguments[0], arg0ListOI); List<String> ftvec2 = HiveUtils.asStringList(arguments[1], arg1ListOI); float d = 1.f - CosineSimilarityUDF.cosineSimilarity(ftvec1, ftvec2); return new FloatWritable(d); } @Deprecated public FloatWritable evaluate(List<String> ftvec1, List<String> ftvec2) { float d = 1.f - CosineSimilarityUDF.cosineSimilarity(ftvec1, ftvec2); return new FloatWritable(d); } @Override public String getDisplayString(String[] children) { return "cosine_distance(" + Arrays.toString(children) + ")"; } }