/**
* 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 org.apache.cassandra.utils;
import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.BitSet;
import org.apache.cassandra.io.ICompactSerializer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class LegacyBloomFilter extends Filter
{
private static final int EXCESS = 20;
private static final Logger logger = LoggerFactory.getLogger(LegacyBloomFilter.class);
static ICompactSerializer<LegacyBloomFilter> serializer_ = new LegacyBloomFilterSerializer();
public static ICompactSerializer<LegacyBloomFilter> serializer()
{
return serializer_;
}
private BitSet filter_;
LegacyBloomFilter(int hashes, BitSet filter)
{
hashCount = hashes;
filter_ = filter;
}
private static BitSet bucketsFor(long numElements, int bucketsPer)
{
long numBits = numElements * bucketsPer + EXCESS;
return new BitSet((int)Math.min(Integer.MAX_VALUE, numBits));
}
/**
* @return A LegacyBloomFilter with the lowest practical false positive probability
* for the given number of elements.
*/
public static LegacyBloomFilter getFilter(long numElements, int targetBucketsPerElem)
{
int maxBucketsPerElement = Math.max(1, BloomCalculations.maxBucketsPerElement(numElements));
int bucketsPerElement = Math.min(targetBucketsPerElem, maxBucketsPerElement);
if (bucketsPerElement < targetBucketsPerElem)
{
logger.warn(String.format("Cannot provide an optimal LegacyBloomFilter for %d elements (%d/%d buckets per element).",
numElements, bucketsPerElement, targetBucketsPerElem));
}
BloomCalculations.BloomSpecification spec = BloomCalculations.computeBloomSpec(bucketsPerElement);
return new LegacyBloomFilter(spec.K, bucketsFor(numElements, spec.bucketsPerElement));
}
/**
* @return The smallest LegacyBloomFilter that can provide the given false positive
* probability rate for the given number of elements.
*
* Asserts that the given probability can be satisfied using this filter.
*/
public static LegacyBloomFilter getFilter(long numElements, double maxFalsePosProbability)
{
assert maxFalsePosProbability <= 1.0 : "Invalid probability";
int bucketsPerElement = BloomCalculations.maxBucketsPerElement(numElements);
BloomCalculations.BloomSpecification spec = BloomCalculations.computeBloomSpec(bucketsPerElement, maxFalsePosProbability);
return new LegacyBloomFilter(spec.K, bucketsFor(numElements, spec.bucketsPerElement));
}
public void clear()
{
filter_.clear();
}
int buckets()
{
return filter_.size();
}
public boolean isPresent(ByteBuffer key)
{
for (int bucketIndex : getHashBuckets(key))
{
if (!filter_.get(bucketIndex))
{
return false;
}
}
return true;
}
/*
@param key -- value whose hash is used to fill
the filter_.
This is a general purpose API.
*/
public void add(ByteBuffer key)
{
for (int bucketIndex : getHashBuckets(key))
{
filter_.set(bucketIndex);
}
}
public String toString()
{
return filter_.toString();
}
ICompactSerializer tserializer()
{
return serializer_;
}
int emptyBuckets()
{
int n = 0;
for (int i = 0; i < buckets(); i++)
{
if (!filter_.get(i))
{
n++;
}
}
return n;
}
/** @return a LegacyBloomFilter that always returns a positive match, for testing */
public static LegacyBloomFilter alwaysMatchingBloomFilter()
{
BitSet set = new BitSet(64);
set.set(0, 64);
return new LegacyBloomFilter(1, set);
}
public int[] getHashBuckets(ByteBuffer key)
{
return LegacyBloomFilter.getHashBuckets(key, hashCount, buckets());
}
// Murmur is faster than an SHA-based approach and provides as-good collision
// resistance. The combinatorial generation approach described in
// http://www.eecs.harvard.edu/~kirsch/pubs/bbbf/esa06.pdf
// does prove to work in actual tests, and is obviously faster
// than performing further iterations of murmur.
static int[] getHashBuckets(ByteBuffer b, int hashCount, int max)
{
int[] result = new int[hashCount];
int hash1 = MurmurHash.hash32(b, b.position(), b.remaining(), 0);
int hash2 = MurmurHash.hash32(b, b.position(), b.remaining(), hash1);
for (int i = 0; i < hashCount; i++)
{
result[i] = Math.abs((hash1 + i * hash2) % max);
}
return result;
}
public BitSet getBitSet(){
return filter_;
}
}