/*
* 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 java.util.Arrays;
import java.util.Collections;
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;
/**
* Adding feature indices to a dense feature.
*
* <pre>
* Usage: select add_feature_index(array(3,4.0,5)) from dual;
* > ["1:3.0","2:4.0","3:5.0"]
* </pre>
*/
@Description(
name = "add_feature_index",
value = "_FUNC_(ARRAY[DOUBLE]: dense feature vector) - Returns a feature vector with feature indicies")
@UDFType(deterministic = true, stateful = false)
public final class AddFeatureIndexUDF extends UDF {
public List<Text> evaluate(List<Double> ftvec) {
if (ftvec == null) {
return null;
}
int size = ftvec.size();
if (size == 0) {
return Collections.emptyList();
}
final Text[] array = new Text[size];
for (int i = 0; i < size; i++) {
Double v = ftvec.get(i);
array[i] = new Text(String.valueOf(i + 1) + ':' + v);
}
return Arrays.asList(array);
}
}