| 1 | /** |
| 2 | * This program is free software: you can redistribute it and/or modify |
| 3 | * it under the terms of the GNU Lesser General Public License as published by |
| 4 | * the Free Software Foundation, either version 3 of the License, or |
| 5 | * (at your option) any later version. |
| 6 | * |
| 7 | * This program is distributed in the hope that it will be useful, |
| 8 | * but WITHOUT ANY WARRANTY; without even the implied warranty of |
| 9 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
| 10 | * GNU Lesser General Public License for more details. |
| 11 | * |
| 12 | * You should have received a copy of the GNU Lesser General Public License |
| 13 | * along with this program. If not, see <http://www.gnu.org/licenses/>. |
| 14 | */ |
| 15 | |
| 16 | package felix.util; |
| 17 | |
| 18 | import java.io.Serializable; |
| 19 | import java.nio.charset.Charset; |
| 20 | import java.security.MessageDigest; |
| 21 | import java.security.NoSuchAlgorithmException; |
| 22 | import java.util.BitSet; |
| 23 | import java.util.Collection; |
| 24 | |
| 25 | /** |
| 26 | * Implementation of a Bloom-filter, as described here: |
| 27 | * http://en.wikipedia.org/wiki/Bloom_filter |
| 28 | * |
| 29 | * Inspired by the SimpleBloomFilter-class written by Ian Clarke. This |
| 30 | * implementation provides a more evenly distributed Hash-function by |
| 31 | * using a proper digest instead of the Java RNG. Many of the changes |
| 32 | * were proposed in comments in his blog: |
| 33 | * http://blog.locut.us/2008/01/12/a-decent-stand-alone-java-bloom-filter-implementation/ |
| 34 | * |
| 35 | * @param <E> Object type that is to be inserted into the Bloom filter, e.g. String or Integer. |
| 36 | * @author Magnus Skjegstad <magnus@skjegstad.com> |
| 37 | */ |
| 38 | public class BloomFilter<E> implements Serializable { |
| 39 | private BitSet bitset; |
| 40 | private int bitSetSize; |
| 41 | private double bitsPerElement; |
| 42 | private int expectedNumberOfFilterElements; // expected (maximum) number of elements to be added |
| 43 | private int numberOfAddedElements; // number of elements actually added to the Bloom filter |
| 44 | private int k; // number of hash functions |
| 45 | |
| 46 | static final Charset charset = Charset.forName("UTF-8"); // encoding used for storing hash values as strings |
| 47 | |
| 48 | static final String hashName = "MD5"; // MD5 gives good enough accuracy in most circumstances. Change to SHA1 if it's needed |
| 49 | static final MessageDigest digestFunction; |
| 50 | static { // The digest method is reused between instances |
| 51 | MessageDigest tmp; |
| 52 | try { |
| 53 | tmp = java.security.MessageDigest.getInstance(hashName); |
| 54 | } catch (NoSuchAlgorithmException e) { |
| 55 | tmp = null; |
| 56 | } |
| 57 | digestFunction = tmp; |
| 58 | } |
| 59 | |
| 60 | /** |
| 61 | * Constructs an empty Bloom filter. The total length of the Bloom filter will be |
| 62 | * c*n. |
| 63 | * |
| 64 | * @param c is the number of bits used per element. |
| 65 | * @param n is the expected number of elements the filter will contain. |
| 66 | * @param k is the number of hash functions used. |
| 67 | */ |
| 68 | public BloomFilter(double c, int n, int k) { |
| 69 | this.expectedNumberOfFilterElements = n; |
| 70 | this.k = k; |
| 71 | this.bitsPerElement = c; |
| 72 | this.bitSetSize = (int)Math.ceil(c * n); |
| 73 | numberOfAddedElements = 0; |
| 74 | this.bitset = new BitSet(bitSetSize); |
| 75 | } |
| 76 | |
| 77 | /** |
| 78 | * Constructs an empty Bloom filter. The optimal number of hash functions (k) is estimated from the total size of the Bloom |
| 79 | * and the number of expected elements. |
| 80 | * |
| 81 | * @param bitSetSize defines how many bits should be used in total for the filter. |
| 82 | * @param expectedNumberOElements defines the maximum number of elements the filter is expected to contain. |
| 83 | */ |
| 84 | public BloomFilter(int bitSetSize, int expectedNumberOElements) { |
| 85 | this(bitSetSize / (double)expectedNumberOElements, |
| 86 | expectedNumberOElements, |
| 87 | (int) Math.round((bitSetSize / (double)expectedNumberOElements) * Math.log(2.0))); |
| 88 | } |
| 89 | |
| 90 | /** |
| 91 | * Constructs an empty Bloom filter with a given false positive probability. The number of bits per |
| 92 | * element and the number of hash functions is estimated |
| 93 | * to match the false positive probability. |
| 94 | * |
| 95 | * @param falsePositiveProbability is the desired false positive probability. |
| 96 | * @param expectedNumberOfElements is the expected number of elements in the Bloom filter. |
| 97 | */ |
| 98 | public BloomFilter(double falsePositiveProbability, int expectedNumberOfElements) { |
| 99 | this(Math.ceil(-(Math.log(falsePositiveProbability) / Math.log(2))) / Math.log(2), // c = k / ln(2) |
| 100 | expectedNumberOfElements, |
| 101 | (int)Math.ceil(-(Math.log(falsePositiveProbability) / Math.log(2)))); // k = ceil(-log_2(false prob.)) |
| 102 | } |
| 103 | |
| 104 | /** |
| 105 | * Construct a new Bloom filter based on existing Bloom filter data. |
| 106 | * |
| 107 | * @param bitSetSize defines how many bits should be used for the filter. |
| 108 | * @param expectedNumberOfFilterElements defines the maximum number of elements the filter is expected to contain. |
| 109 | * @param actualNumberOfFilterElements specifies how many elements have been inserted into the <code>filterData</code> BitSet. |
| 110 | * @param filterData a BitSet representing an existing Bloom filter. |
| 111 | */ |
| 112 | public BloomFilter(int bitSetSize, int expectedNumberOfFilterElements, int actualNumberOfFilterElements, BitSet filterData) { |
| 113 | this(bitSetSize, expectedNumberOfFilterElements); |
| 114 | this.bitset = filterData; |
| 115 | this.numberOfAddedElements = actualNumberOfFilterElements; |
| 116 | } |
| 117 | |
| 118 | /** |
| 119 | * Generates a digest based on the contents of a String. |
| 120 | * |
| 121 | * @param val specifies the input data. |
| 122 | * @param charset specifies the encoding of the input data. |
| 123 | * @return digest as long. |
| 124 | */ |
| 125 | public static long createHash(String val, Charset charset) { |
| 126 | return createHash(val.getBytes(charset)); |
| 127 | } |
| 128 | |
| 129 | /** |
| 130 | * Generates a digest based on the contents of a String. |
| 131 | * |
| 132 | * @param val specifies the input data. The encoding is expected to be UTF-8. |
| 133 | * @return digest as long. |
| 134 | */ |
| 135 | public static long createHash(String val) { |
| 136 | return createHash(val, charset); |
| 137 | } |
| 138 | |
| 139 | /** |
| 140 | * Generates a digest based on the contents of an array of bytes. |
| 141 | * |
| 142 | * @param data specifies input data. |
| 143 | * @return digest as long. |
| 144 | */ |
| 145 | public static long createHash(byte[] data) { |
| 146 | long h = 0; |
| 147 | byte[] res; |
| 148 | |
| 149 | synchronized (digestFunction) { |
| 150 | res = digestFunction.digest(data); |
| 151 | } |
| 152 | |
| 153 | for (int i = 0; i < 4; i++) { |
| 154 | h <<= 8; |
| 155 | h |= ((int) res[i]) & 0xFF; |
| 156 | } |
| 157 | return h; |
| 158 | } |
| 159 | |
| 160 | /** |
| 161 | * Compares the contents of two instances to see if they are equal. |
| 162 | * |
| 163 | * @param obj is the object to compare to. |
| 164 | * @return True if the contents of the objects are equal. |
| 165 | */ |
| 166 | @Override |
| 167 | public boolean equals(Object obj) { |
| 168 | if (obj == null) { |
| 169 | return false; |
| 170 | } |
| 171 | if (getClass() != obj.getClass()) { |
| 172 | return false; |
| 173 | } |
| 174 | final BloomFilter<E> other = (BloomFilter<E>) obj; |
| 175 | if (this.expectedNumberOfFilterElements != other.expectedNumberOfFilterElements) { |
| 176 | return false; |
| 177 | } |
| 178 | if (this.k != other.k) { |
| 179 | return false; |
| 180 | } |
| 181 | if (this.bitSetSize != other.bitSetSize) { |
| 182 | return false; |
| 183 | } |
| 184 | if (this.bitset != other.bitset && (this.bitset == null || !this.bitset.equals(other.bitset))) { |
| 185 | return false; |
| 186 | } |
| 187 | return true; |
| 188 | } |
| 189 | |
| 190 | /** |
| 191 | * Calculates a hash code for this class. |
| 192 | * @return hash code representing the contents of an instance of this class. |
| 193 | */ |
| 194 | @Override |
| 195 | public int hashCode() { |
| 196 | int hash = 7; |
| 197 | hash = 61 * hash + (this.bitset != null ? this.bitset.hashCode() : 0); |
| 198 | hash = 61 * hash + this.expectedNumberOfFilterElements; |
| 199 | hash = 61 * hash + this.bitSetSize; |
| 200 | hash = 61 * hash + this.k; |
| 201 | return hash; |
| 202 | } |
| 203 | |
| 204 | |
| 205 | /** |
| 206 | * Calculates the expected probability of false positives based on |
| 207 | * the number of expected filter elements and the size of the Bloom filter. |
| 208 | * <br /><br /> |
| 209 | * The value returned by this method is the <i>expected</i> rate of false |
| 210 | * positives, assuming the number of inserted elements equals the number of |
| 211 | * expected elements. If the number of elements in the Bloom filter is less |
| 212 | * than the expected value, the true probability of false positives will be lower. |
| 213 | * |
| 214 | * @return expected probability of false positives. |
| 215 | */ |
| 216 | public double expectedFalsePositiveProbability() { |
| 217 | return getFalsePositiveProbability(expectedNumberOfFilterElements); |
| 218 | } |
| 219 | |
| 220 | /** |
| 221 | * Calculate the probability of a false positive given the specified |
| 222 | * number of inserted elements. |
| 223 | * |
| 224 | * @param numberOfElements number of inserted elements. |
| 225 | * @return probability of a false positive. |
| 226 | */ |
| 227 | public double getFalsePositiveProbability(double numberOfElements) { |
| 228 | // (1 - e^(-k * n / m)) ^ k |
| 229 | return Math.pow((1 - Math.exp(-k * (double) numberOfElements |
| 230 | / (double) bitSetSize)), k); |
| 231 | |
| 232 | } |
| 233 | |
| 234 | /** |
| 235 | * Get the current probability of a false positive. The probability is calculated from |
| 236 | * the size of the Bloom filter and the current number of elements added to it. |
| 237 | * |
| 238 | * @return probability of false positives. |
| 239 | */ |
| 240 | public double getFalsePositiveProbability() { |
| 241 | return getFalsePositiveProbability(numberOfAddedElements); |
| 242 | } |
| 243 | |
| 244 | |
| 245 | /** |
| 246 | * Returns the value chosen for K.<br /> |
| 247 | * <br /> |
| 248 | * K is the optimal number of hash functions based on the size |
| 249 | * of the Bloom filter and the expected number of inserted elements. |
| 250 | * |
| 251 | * @return optimal k. |
| 252 | */ |
| 253 | public int getK() { |
| 254 | return k; |
| 255 | } |
| 256 | |
| 257 | /** |
| 258 | * Sets all bits to false in the Bloom filter. |
| 259 | */ |
| 260 | public void clear() { |
| 261 | bitset.clear(); |
| 262 | numberOfAddedElements = 0; |
| 263 | } |
| 264 | |
| 265 | /** |
| 266 | * Adds an object to the Bloom filter. The output from the object's |
| 267 | * toString() method is used as input to the hash functions. |
| 268 | * |
| 269 | * @param element is an element to register in the Bloom filter. |
| 270 | */ |
| 271 | public void add(E element) { |
| 272 | long hash; |
| 273 | String valString = element.toString(); |
| 274 | for (int x = 0; x < k; x++) { |
| 275 | hash = createHash(valString + Integer.toString(x)); |
| 276 | hash = hash % (long)bitSetSize; |
| 277 | bitset.set(Math.abs((int)hash), true); |
| 278 | } |
| 279 | numberOfAddedElements ++; |
| 280 | } |
| 281 | |
| 282 | /** |
| 283 | * Adds all elements from a Collection to the Bloom filter. |
| 284 | * @param c Collection of elements. |
| 285 | */ |
| 286 | public void addAll(Collection<? extends E> c) { |
| 287 | for (E element : c) |
| 288 | add(element); |
| 289 | } |
| 290 | |
| 291 | /** |
| 292 | * Returns true if the element could have been inserted into the Bloom filter. |
| 293 | * Use getFalsePositiveProbability() to calculate the probability of this |
| 294 | * being correct. |
| 295 | * |
| 296 | * @param element element to check. |
| 297 | * @return true if the element could have been inserted into the Bloom filter. |
| 298 | */ |
| 299 | public boolean contains(E element) { |
| 300 | long hash; |
| 301 | String valString = element.toString(); |
| 302 | for (int x = 0; x < k; x++) { |
| 303 | hash = createHash(valString + Integer.toString(x)); |
| 304 | hash = hash % (long)bitSetSize; |
| 305 | if (!bitset.get(Math.abs((int)hash))) |
| 306 | return false; |
| 307 | } |
| 308 | return true; |
| 309 | } |
| 310 | |
| 311 | /** |
| 312 | * Returns true if all the elements of a Collection could have been inserted |
| 313 | * into the Bloom filter. Use getFalsePositiveProbability() to calculate the |
| 314 | * probability of this being correct. |
| 315 | * @param c elements to check. |
| 316 | * @return true if all the elements in c could have been inserted into the Bloom filter. |
| 317 | */ |
| 318 | public boolean containsAll(Collection<? extends E> c) { |
| 319 | for (E element : c) |
| 320 | if (!contains(element)) |
| 321 | return false; |
| 322 | return true; |
| 323 | } |
| 324 | |
| 325 | /** |
| 326 | * Read a single bit from the Bloom filter. |
| 327 | * @param bit the bit to read. |
| 328 | * @return true if the bit is set, false if it is not. |
| 329 | */ |
| 330 | public boolean getBit(int bit) { |
| 331 | return bitset.get(bit); |
| 332 | } |
| 333 | |
| 334 | /** |
| 335 | * Set a single bit in the Bloom filter. |
| 336 | * @param bit is the bit to set. |
| 337 | * @param value If true, the bit is set. If false, the bit is cleared. |
| 338 | */ |
| 339 | public void setBit(int bit, boolean value) { |
| 340 | bitset.set(bit, value); |
| 341 | } |
| 342 | |
| 343 | /** |
| 344 | * Return the bit set used to store the Bloom filter. |
| 345 | * @return bit set representing the Bloom filter. |
| 346 | */ |
| 347 | public BitSet getBitSet() { |
| 348 | return bitset; |
| 349 | } |
| 350 | |
| 351 | /** |
| 352 | * Returns the number of bits in the Bloom filter. Use count() to retrieve |
| 353 | * the number of inserted elements. |
| 354 | * |
| 355 | * @return the size of the bitset used by the Bloom filter. |
| 356 | */ |
| 357 | public int size() { |
| 358 | return this.bitSetSize; |
| 359 | } |
| 360 | |
| 361 | /** |
| 362 | * Returns the number of elements added to the Bloom filter after it |
| 363 | * was constructed or after clear() was called. |
| 364 | * |
| 365 | * @return number of elements added to the Bloom filter. |
| 366 | */ |
| 367 | public int count() { |
| 368 | return this.numberOfAddedElements; |
| 369 | } |
| 370 | |
| 371 | /** |
| 372 | * Returns the expected number of elements to be inserted into the filter. |
| 373 | * This value is the same value as the one passed to the constructor. |
| 374 | * |
| 375 | * @return expected number of elements. |
| 376 | */ |
| 377 | public int getExpectedNumberOfElements() { |
| 378 | return expectedNumberOfFilterElements; |
| 379 | } |
| 380 | |
| 381 | /** |
| 382 | * Get expected number of bits per element when the Bloom filter is full. This value is set by the constructor |
| 383 | * when the Bloom filter is created. See also getBitsPerElement(). |
| 384 | * |
| 385 | * @return expected number of bits per element. |
| 386 | */ |
| 387 | public double getExpectedBitsPerElement() { |
| 388 | return this.bitsPerElement; |
| 389 | } |
| 390 | |
| 391 | /** |
| 392 | * Get actual number of bits per element based on the number of elements that have currently been inserted and the length |
| 393 | * of the Bloom filter. See also getExpectedBitsPerElement(). |
| 394 | * |
| 395 | * @return number of bits per element. |
| 396 | */ |
| 397 | public double getBitsPerElement() { |
| 398 | return this.bitSetSize / (double)numberOfAddedElements; |
| 399 | } |
| 400 | } |