/*
* 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.xgboost.classification;
import java.util.UUID;
import org.apache.hadoop.hive.ql.exec.Description;
/** An alternative implementation of [[hivemall.xgboost.classification.XGBoostMulticlassClassifierUDTFWrapper]]. */
@Description(
name = "train_multiclass_xgboost_classifier",
value = "_FUNC_(string[] features, double target [, string options]) - Returns a relation consisting of <string model_id, array<byte> pred_model>"
)
public class XGBoostMulticlassClassifierUDTFWrapper extends XGBoostMulticlassClassifierUDTF {
private long sequence;
private long taskId;
public XGBoostMulticlassClassifierUDTFWrapper() {
this.sequence = 0L;
this.taskId = Thread.currentThread().getId();
}
@Override
protected String generateUniqueModelId() {
sequence++;
/**
* TODO: Check if it is unique over all tasks in executors of Spark.
*/
return "xgbmodel-" + taskId + "-" + UUID.randomUUID() + "-" + sequence;
}
}