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BloomFilter.java
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BloomFilter.java
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import java.io.Serializable;
import java.nio.charset.Charset;
import java.security.MessageDigest;
import java.security.NoSuchAlgorithmException;
import java.util.BitSet;
import java.util.Collection;
@SuppressWarnings("serial")
public class BloomFilter<E> implements Serializable
{
private BitSet bitset;
private int bitSetSize;
private double bitsPerElement;
private int expectedNumberOfFilterElements; // expected (maximum) number of elements to be added
private int numberOfAddedElements; // number of elements actually added to the Bloom filter
private int k; // number of hash functions
static final Charset charset = Charset.forName("UTF-8"); // encoding used for storing hash values as strings
static final String hashName = "MD5"; // MD5 gives good enough accuracy in most circumstances. Change to SHA1 if it's needed
static final MessageDigest digestFunction;
static { // The digest method is reused between instances
MessageDigest tmp;
try
{
tmp = java.security.MessageDigest.getInstance(hashName);
}
catch (NoSuchAlgorithmException e)
{
tmp = null;
}
digestFunction = tmp;
}
public BloomFilter(double c, int n, int k)
{
this.expectedNumberOfFilterElements = n;
this.k = k;
this.bitsPerElement = c;
this.bitSetSize = (int)Math.ceil(c * n);
numberOfAddedElements = 0;
this.bitset = new BitSet(bitSetSize);
}
public BloomFilter(int bitSetSize, int expectedNumberOElements)
{
this(bitSetSize / (double)expectedNumberOElements,
expectedNumberOElements,
(int) Math.round((bitSetSize / (double)expectedNumberOElements) * Math.log(2.0)));
}
public BloomFilter(double falsePositiveProbability, int expectedNumberOfElements)
{
this(Math.ceil(-(Math.log(falsePositiveProbability) / Math.log(2))) / Math.log(2), // c = k / ln(2)
expectedNumberOfElements,
(int)Math.ceil(-(Math.log(falsePositiveProbability) / Math.log(2)))); // k = ceil(-log_2(false prob.))
}
public static int createHash(String val, Charset charset)
{
return createHash(val.getBytes(charset));
}
public static int createHash(String val)
{
return createHash(val, charset);
}
public static int createHash(byte[] data)
{
return createHashes(data, 1)[0];
}
public static int[] createHashes(byte[] data, int hashes)
{
int[] result = new int[hashes];
int k = 0;
byte salt = 0;
while (k < hashes)
{
byte[] digest;
synchronized (digestFunction)
{
digestFunction.update(salt);
salt++;
digest = digestFunction.digest(data);
}
for (int i = 0; i < digest.length/4 && k < hashes; i++)
{
int h = 0;
for (int j = (i*4); j < (i*4)+4; j++)
{
h <<= 8;
h |= ((int) digest[j]) & 0xFF;
}
result[k] = h;
k++;
}
}
return result;
}
@Override
public boolean equals(Object obj)
{
if (obj == null)
{
return false;
}
if (getClass() != obj.getClass())
{
return false;
}
final BloomFilter<E> other = (BloomFilter<E>) obj;
if (this.expectedNumberOfFilterElements != other.expectedNumberOfFilterElements)
{
return false;
}
if (this.k != other.k)
{
return false;
}
if (this.bitSetSize != other.bitSetSize)
{
return false;
}
if (this.bitset != other.bitset && (this.bitset == null || !this.bitset.equals(other.bitset)))
{
return false;
}
return true;
}
@Override
public int hashCode()
{
int hash = 7;
hash = 61 * hash + (this.bitset != null ? this.bitset.hashCode() : 0);
hash = 61 * hash + this.expectedNumberOfFilterElements;
hash = 61 * hash + this.bitSetSize;
hash = 61 * hash + this.k;
return hash;
}
public int getK()
{
return k;
}
public void clear()
{
bitset.clear();
numberOfAddedElements = 0;
}
public void add(E element)
{
add(element.toString().getBytes(charset));
}
public void add(byte[] bytes)
{
int[] hashes = createHashes(bytes, k);
for (int hash : hashes)
bitset.set(Math.abs(hash % bitSetSize), true);
numberOfAddedElements ++;
}
public boolean contains(E element)
{
return contains(element.toString().getBytes(charset));
}
public boolean contains(byte[] bytes)
{
int[] hashes = createHashes(bytes, k);
for (int hash : hashes)
{
if (!bitset.get(Math.abs(hash % bitSetSize)))
{
return false;
}
}
return true;
}
}