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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 com.datatorrent.lib.math;
import java.util.HashMap;
import java.util.Map;
import org.apache.commons.lang.mutable.MutableDouble;
import org.apache.commons.lang.mutable.MutableLong;
import com.datatorrent.api.DefaultInputPort;
import com.datatorrent.api.DefaultOutputPort;
import com.datatorrent.api.annotation.OutputPortFieldAnnotation;
import com.datatorrent.lib.util.BaseNumberKeyValueOperator;
import com.datatorrent.lib.util.KeyValPair;
/**
*
* Emits the average of values for each key at the end of window.
* <p>
* <br>User can block or only enable certain keys by setting filter-keys/inverse operator properties.
* <br> Block Key : inverse=true
* <br> Enable Key : inverse=false
* This is an end window operator. This can not be partitioned. Partitioning
* this will yield incorrect result.<br>
* <br>
* <b>Ports</b>:<br>
* <b>data</b>: expects KeyValPair&lt;K,V extends Number&gt;<br>
* <b>averagePort(s)</b>: emits KeyValPair&lt;K,V extends Number&gt;</b><br>
* <br>Output ports are optional.
* <br>
* <b>Properties</b>:<br>
* <b>inverse</b>: if set to true the key in the filter will block tuple (default : true).<br>
* <b>filterBy</b>: List of keys to filter on.<br>
* <br>
* <b>Specific compile time checks</b>: None<br>
* <b>Specific run time checks</b>: None<br>
* <p>
* @displayName Average Key Value
* @category Math
* @tags average, number, end window, key value
* @since 0.3.3
*/
public class AverageKeyVal<K> extends BaseNumberKeyValueOperator<K, Number>
{
// Aggregate sum of all values seen for a key.
protected HashMap<K, MutableDouble> sums = new HashMap<K, MutableDouble>();
// Count of number of values seen for key.
protected HashMap<K, MutableLong> counts = new HashMap<K, MutableLong>();
/**
* Input port that takes a key value pair.
*/
public final transient DefaultInputPort<KeyValPair<K, ? extends Number>> data = new DefaultInputPort<KeyValPair<K, ? extends Number>>()
{
/**
* Adds the values for each key, counts the number of occurrences of each
* key and computes the average.
*/
@Override
public void process(KeyValPair<K, ? extends Number> tuple)
{
K key = tuple.getKey();
if (!doprocessKey(key)) {
return;
}
MutableDouble val = sums.get(key);
if (val == null) {
val = new MutableDouble(tuple.getValue().doubleValue());
} else {
val.add(tuple.getValue().doubleValue());
}
sums.put(cloneKey(key), val);
MutableLong count = counts.get(key);
if (count == null) {
count = new MutableLong(0);
counts.put(cloneKey(key), count);
}
count.increment();
}
};
/**
* Double average output port.
*/
@OutputPortFieldAnnotation(optional = true)
public final transient DefaultOutputPort<KeyValPair<K, Double>> doubleAverage =
new DefaultOutputPort<KeyValPair<K, Double>>();
/**
* Integer average output port.
*/
@OutputPortFieldAnnotation(optional = true)
public final transient DefaultOutputPort<KeyValPair<K, Integer>> intAverage =
new DefaultOutputPort<KeyValPair<K, Integer>>();
/**
* Long average output port.
*/
@OutputPortFieldAnnotation(optional = true)
public final transient DefaultOutputPort<KeyValPair<K, Long>> longAverage =
new DefaultOutputPort<KeyValPair<K, Long>>();
/**
* Emits average for each key in end window. Data is computed during process
* on input port Clears the internal data before return.
*/
@Override
public void endWindow()
{
for (Map.Entry<K, MutableDouble> e : sums.entrySet()) {
K key = e.getKey();
double d = e.getValue().doubleValue();
if (doubleAverage.isConnected()) {
doubleAverage.emit(new KeyValPair<K, Double>(key, d / counts.get(key).doubleValue()));
}
if (intAverage.isConnected()) {
intAverage.emit(new KeyValPair<K, Integer>(key, (int)d));
}
if (longAverage.isConnected()) {
longAverage.emit(new KeyValPair<K, Long>(key, (long)d));
}
}
sums.clear();
counts.clear();
}
}