/**
* Copyright (C) 2014-2016 LinkedIn Corp. (pinot-core@linkedin.com)
*
* Licensed 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 com.linkedin.pinot.tools.scan.query;
import java.util.ArrayList;
import java.util.Collections;
import com.linkedin.pinot.core.query.utils.Pair;
public class AvgFunction extends AggregationFunc {
private static final String _name = "avg";
AvgFunction(ResultTable rows, String column) {
super(rows, column);
}
@Override
public ResultTable run() {
Double sum = 0.0;
int numEntries = 0;
for (ResultTable.Row row : _rows) {
Object value = row.get(_column, _name);
if (value instanceof double []) {
double [] valArray = (double []) value;
sum += valArray[0];
numEntries += valArray[1];
} else {
sum += new Double(row.get(_column, _name).toString());
++numEntries;
}
}
double[] average = new double[2];
average[0] = sum;
average[1] = numEntries;
ResultTable resultTable = new ResultTable(new ArrayList<Pair>(), 1);
resultTable.add(0, average);
return resultTable;
}
}