package org.apache.cassandra.stress.generate;
/*
*
* 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.
*
*/
import java.util.Arrays;
import java.util.Random;
import org.apache.cassandra.stress.Stress;
public class DistributionQuantized extends Distribution
{
final Distribution delegate;
final long[] bounds;
final Random random = new Random();
public DistributionQuantized(Distribution delegate, int quantas)
{
this.delegate = delegate;
this.bounds = new long[quantas + 1];
bounds[0] = delegate.minValue();
bounds[quantas] = delegate.maxValue() + 1;
for (int i = 1 ; i < quantas ; i++)
bounds[i] = delegate.inverseCumProb(i / (double) quantas);
}
@Override
public long next()
{
int quanta = quanta(delegate.next());
return bounds[quanta] + (long) (random.nextDouble() * ((bounds[quanta + 1] - bounds[quanta])));
}
public double nextDouble()
{
throw new UnsupportedOperationException();
}
@Override
public long inverseCumProb(double cumProb)
{
long val = delegate.inverseCumProb(cumProb);
int quanta = quanta(val);
if (quanta < 0)
return bounds[0];
if (quanta >= bounds.length - 1)
return bounds[bounds.length - 1] - 1;
cumProb -= (quanta / ((double) bounds.length - 1));
cumProb *= (double) bounds.length - 1;
return bounds[quanta] + (long) (cumProb * (bounds[quanta + 1] - bounds[quanta]));
}
int quanta(long val)
{
int i = Arrays.binarySearch(bounds, val);
if (i < 0)
return -2 -i;
return i - 1;
}
public void setSeed(long seed)
{
delegate.setSeed(seed);
}
public static void main(String[] args) throws Exception
{
Stress.main(new String[] { "print", "dist=qextreme(1..1M,2,2)"});
}
}