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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 org.apache.hadoop.hive.ql.udf.generic;

import java.util.ArrayList;
import java.util.List;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.WindowFunctionDescription;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.serde2.io.DoubleWritable;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.io.IntWritable;

@WindowFunctionDescription
(
		description = @Description(
								name = "cume_dist",
								value = "_FUNC_(x) - The CUME_DIST function (defined as the inverse of percentile in some " +
									"statistical books) computes the position of a specified value relative to a set of values. " +
									"To compute the CUME_DIST of a value x in a set S of size N, you use the formula: " +
									"CUME_DIST(x) =  number of values in S coming before " +
									"   and including x in the specified order/ N"
								),
		supportsWindow = false,
		pivotResult = true
)
public class GenericUDAFCumeDist extends GenericUDAFRank
{

	static final Log LOG = LogFactory.getLog(GenericUDAFCumeDist.class.getName());

	@Override
  protected GenericUDAFRankEvaluator createEvaluator()
	{
		return new GenericUDAFCumeDistEvaluator();
	}

  public static class GenericUDAFCumeDistEvaluator extends GenericUDAFRankEvaluator
  {
    @Override
    public ObjectInspector init(Mode m, ObjectInspector[] parameters) throws HiveException
    {
      super.init(m, parameters);
      return ObjectInspectorFactory
          .getStandardListObjectInspector(PrimitiveObjectInspectorFactory.writableDoubleObjectInspector);
    }

    @Override
    public Object terminate(AggregationBuffer agg) throws HiveException
    {
      List ranks = ((RankBuffer) agg).rowNums;
      int ranksSize = ranks.size();
      double ranksSizeDouble = ranksSize;
      List distances = new ArrayList(ranksSize);
      int last = -1;
      int current = -1;
      // tracks the number of elements with the same rank at the current time
      int elementsAtRank = 1;
      for (int index = 0; index < ranksSize; index++) {
        current = ranks.get(index).get();
        if (index == 0) {
          last = current;
        } else if (last == current) {
          elementsAtRank++;
        } else {
          last = current;
          double distance = ((double) index) / ranksSizeDouble;
          while (elementsAtRank-- > 0) {
            distances.add(new DoubleWritable(distance));
          }
          elementsAtRank = 1;
        }
      }
      if (ranksSize > 0 && last == current) {
        double distance = ((double) ranksSize) / ranksSizeDouble;
        while (elementsAtRank-- > 0) {
          distances.add(new DoubleWritable(distance));
        }
      }
      return distances;
    }
  }
}