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A library for summarizing data in streams for which it is infeasible to store all events
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/*
* Copyright (C) 2011 Clearspring Technologies, Inc.
*
* 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.clearspring.analytics.stream;
import java.util.List;
import java.util.Random;
/**
* Estimates most frequently occurring items in a data stream
* using a bounded amount of memory.
*
* Warning: this class is not thread safe.
*/
public class StochasticTopper implements ITopK {
private int sampleSize;
private ISampleSet sample;
private Random random;
private long count;
public StochasticTopper(int sampleSize) {
this(sampleSize, null);
}
public StochasticTopper(int sampleSize, Long seed) {
this.sample = new SampleSet(sampleSize);
this.sampleSize = sampleSize;
if (seed != null) {
random = new Random(seed);
} else {
random = new Random();
}
}
public boolean offer(T item, int incrementCount) {
count++;
boolean taken = false;
if (sample.count() < sampleSize) {
sample.put(item, incrementCount);
taken = true;
} else if (random.nextDouble() < sampleSize / (double) count) {
sample.removeRandom();
sample.put(item, incrementCount);
taken = true;
}
return taken;
}
public boolean offer(T item) {
return offer(item, 1);
}
/**
* Retrieve top k items
*/
public List peek(int k) {
return sample.peek(k);
}
}