/* * 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.ftvec; import static hivemall.utils.hadoop.WritableUtils.val; import java.util.Arrays; import java.util.List; 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.Text; @Description(name = "extract_feature", value = "_FUNC_(feature_vector in array<string>) - Returns features in array<string>") @UDFType(deterministic = true, stateful = false) public class ExtractFeatureUDF extends UDF { public Text evaluate(String featureVector) { if (featureVector == null) { return null; } return val(extractFeature(featureVector)); } public List<Text> evaluate(List<String> featureVectors) { if (featureVectors == null) { return null; } final int size = featureVectors.size(); final Text[] output = new Text[size]; for (int i = 0; i < size; i++) { String fv = featureVectors.get(i); if (fv != null) { output[i] = new Text(extractFeature(fv)); } } return Arrays.asList(output); } public static String extractFeature(final String ftvec) { int pos = ftvec.indexOf(":"); if (pos > 0) { return ftvec.substring(0, pos); } else { return ftvec; } } }