org.apache.phoenix.iterate.TableSamplerPredicate Maven / Gradle / Ivy
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* 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,
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* See the License for the specific language governing permissions and
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*/
package org.apache.phoenix.iterate;
import com.google.common.base.Predicate;
/**
* TableSampler.
*
* A dice rolling on every targeted row to decide if this row is going
* to be picked or not.
* An application is table Sampler, based on boolean result, this row is
* then picked (or rejected) to be part of sample set.
*
* Currently implemented using FNV1a with Lazy mod mapping method to ensure
* the even distribution of hashed result, so that the final sampled result
* will be close to the size of expected
*
*/
public class TableSamplerPredicate implements Predicate{
private final double tableSamplingRate;
private TableSamplerPredicate(double tableSamplingRate){
this.tableSamplingRate=tableSamplingRate;
}
public static TableSamplerPredicate of(final Double tableSamplingRateRaw){
assert(tableSamplingRateRaw!=null):"tableSamplingRate can not be null";
assert(tableSamplingRateRaw>=0d&&tableSamplingRateRaw<=100d):"tableSamplingRate input has to be a rational number between 0 and 100";
TableSamplerPredicate self=new TableSamplerPredicate(tableSamplingRateRaw);
return self;
}
@Override
public boolean apply(byte[] bytes) {
final int hashcode_FNV1Lazy=FNV1LazyImpl(bytes);
final boolean result=evaluateWithChance(hashcode_FNV1Lazy);
return result;
}
/**
* Take build in FNV1a Hash function then apply lazy mod mapping method so that the
* hash is evenly distributed between 0 and 100.
*
* Quoted from http://isthe.com/chongo/tech/comp/fnv/,
* The FNV hash is designed for hash sizes that are a power of 2.
* If you need a hash size that is not a power of two, then you have two choices.
* One method is called the lazy mod mapping method and the other is called the retry method.
* Both involve mapping a range that is a power of 2 onto an arbitrary range.
*
* Lazy mod mapping method: The lazy mod mapping method uses a simple mod on an n-bit hash
* to yield an arbitrary range.
* To produce a hash range between 0 and X use a n-bit FNV hash where n is smallest FNV hash
* that will produce values larger than X without the need for xor-folding.
*
* For example, to produce a value between 0 and 2142779559 using the lazy mod mapping method,
* we select a 32-bit FNV hash because: 2 power 32 > 49999
* Before the final mod 50000 is performed,
* we check to see if the 32-bit FNV hash value is one of the upper biased values.
* If it is, we perform additional loop cycles until is below the bias level.
*
* An advantage of the lazy mod mapping method is that it requires only 1 more operation:
* only an additional mod is performed at the end.
* The disadvantage of the lazy mod mapping method is that there is a bias against
* the larger values.
*
* @param bytes
* @return
*/
final static private int FNV1LazyImpl(final byte[] bytes){
final int contentBasedHashCode = java.util.Arrays.hashCode(bytes);
return lazyRedistribute(contentBasedHashCode);
}
/**
* Lazy mod mapping method Implementation
*
* Output result should be following the same distribution as input hashcode,
* however re-mapped between 0 and 100.
*
* @param hashcode
* @return
*/
final static private int lazyRedistribute(final int hashcode){
return java.lang.Math.abs(hashcode%100);
}
/**
*
* @param hashcode
* @return
*/
final private boolean evaluateWithChance(final int hashcode){
assert((hashcode>=0)&&(hashcode<=100)):"hashcode should be re-distribute into 0 to 100";
return (hashcode
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