001 /*
002 * Copyright (C) 2011 The Guava Authors
003 *
004 * Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
005 * in compliance with the License. You may obtain a copy of the License at
006 *
007 * http://www.apache.org/licenses/LICENSE-2.0
008 *
009 * Unless required by applicable law or agreed to in writing, software distributed under the License
010 * is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
011 * or implied. See the License for the specific language governing permissions and limitations under
012 * the License.
013 */
014
015 package com.google.common.hash;
016
017 import static com.google.common.base.Preconditions.checkArgument;
018 import static com.google.common.base.Preconditions.checkNotNull;
019
020 import com.google.common.annotations.Beta;
021 import com.google.common.annotations.VisibleForTesting;
022 import com.google.common.base.Preconditions;
023 import com.google.common.hash.BloomFilterStrategies.BitArray;
024
025 import java.io.Serializable;
026
027 /**
028 * A Bloom filter for instances of {@code T}. A Bloom filter offers an approximate containment test
029 * with one-sided error: if it claims that an element is contained in it, this might be in error,
030 * but if it claims that an element is <i>not</i> contained in it, then this is definitely true.
031 *
032 * <p>If you are unfamiliar with Bloom filters, this nice
033 * <a href="http://llimllib.github.com/bloomfilter-tutorial/">tutorial</a> may help you understand
034 * how they work.
035 *
036 *
037 * @param <T> the type of instances that the {@code BloomFilter} accepts
038 * @author Dimitris Andreou
039 * @author Kevin Bourrillion
040 * @since 11.0
041 */
042 @Beta
043 public final class BloomFilter<T> implements Serializable {
044 /**
045 * A strategy to translate T instances, to {@code numHashFunctions} bit indexes.
046 *
047 * <p>Implementations should be collections of pure functions (i.e. stateless).
048 */
049 interface Strategy extends java.io.Serializable {
050
051 /**
052 * Sets {@code numHashFunctions} bits of the given bit array, by hashing a user element.
053 *
054 * <p>Returns whether any bits changed as a result of this operation.
055 */
056 <T> boolean put(T object, Funnel<? super T> funnel, int numHashFunctions, BitArray bits);
057
058 /**
059 * Queries {@code numHashFunctions} bits of the given bit array, by hashing a user element;
060 * returns {@code true} if and only if all selected bits are set.
061 */
062 <T> boolean mightContain(
063 T object, Funnel<? super T> funnel, int numHashFunctions, BitArray bits);
064
065 /**
066 * Identifier used to encode this strategy, when marshalled as part of a BloomFilter.
067 * Only values in the [-128, 127] range are valid for the compact serial form.
068 * Non-negative values are reserved for enums defined in BloomFilterStrategies;
069 * negative values are reserved for any custom, stateful strategy we may define
070 * (e.g. any kind of strategy that would depend on user input).
071 */
072 int ordinal();
073 }
074
075 /** The bit set of the BloomFilter (not necessarily power of 2!)*/
076 private final BitArray bits;
077
078 /** Number of hashes per element */
079 private final int numHashFunctions;
080
081 /** The funnel to translate Ts to bytes */
082 private final Funnel<T> funnel;
083
084 /**
085 * The strategy we employ to map an element T to {@code numHashFunctions} bit indexes.
086 */
087 private final Strategy strategy;
088
089 /**
090 * Creates a BloomFilter.
091 */
092 private BloomFilter(BitArray bits, int numHashFunctions, Funnel<T> funnel,
093 Strategy strategy) {
094 Preconditions.checkArgument(numHashFunctions > 0, "numHashFunctions zero or negative");
095 this.bits = checkNotNull(bits);
096 this.numHashFunctions = numHashFunctions;
097 this.funnel = checkNotNull(funnel);
098 this.strategy = strategy;
099
100 /*
101 * This only exists to forbid BFs that cannot use the compact persistent representation.
102 * If it ever throws, at a user who was not intending to use that representation, we should
103 * reconsider
104 */
105 if (numHashFunctions > 255) {
106 throw new AssertionError("Currently we don't allow BloomFilters that would use more than" +
107 "255 hash functions, please contact the guava team");
108 }
109 }
110
111 /**
112 * Creates a new {@code BloomFilter} that's a copy of this instance. The new instance is equal to
113 * this instance but shares no mutable state.
114 *
115 * @since 12.0
116 */
117 public BloomFilter<T> copy() {
118 return new BloomFilter<T>(bits.copy(), numHashFunctions, funnel, strategy);
119 }
120
121 /**
122 * Returns {@code true} if the element <i>might</i> have been put in this Bloom filter,
123 * {@code false} if this is <i>definitely</i> not the case.
124 */
125 public boolean mightContain(T object) {
126 return strategy.mightContain(object, funnel, numHashFunctions, bits);
127 }
128
129 /**
130 * Puts an element into this {@code BloomFilter}. Ensures that subsequent invocations of
131 * {@link #mightContain(Object)} with the same element will always return {@code true}.
132 *
133 * @return true if the bloom filter's bits changed as a result of this operation. If the bits
134 * changed, this is <i>definitely</i> the first time {@code object} has been added to the
135 * filter. If the bits haven't changed, this <i>might</i> be the first time {@code object}
136 * has been added to the filter. Note that {@code put(t)} always returns the
137 * <i>opposite</i> result to what {@code mightContain(t)} would have returned at the time
138 * it is called."
139 * @since 12.0 (present in 11.0 with {@code void} return type})
140 */
141 public boolean put(T object) {
142 return strategy.put(object, funnel, numHashFunctions, bits);
143 }
144
145 /**
146 * Returns the probability that {@linkplain #mightContain(Object)} will erroneously return
147 * {@code true} for an object that has not actually been put in the {@code BloomFilter}.
148 *
149 * <p>Ideally, this number should be close to the {@code falsePositiveProbability} parameter
150 * passed in {@linkplain #create(Funnel, int, double)}, or smaller. If it is
151 * significantly higher, it is usually the case that too many elements (more than
152 * expected) have been put in the {@code BloomFilter}, degenerating it.
153 */
154 public double expectedFalsePositiveProbability() {
155 return Math.pow((double) bits.bitCount() / bits.size(), numHashFunctions);
156 }
157
158 /**
159 * {@inheritDoc}
160 *
161 * <p>This implementation uses reference equality to compare funnels.
162 */
163 @Override public boolean equals(Object o) {
164 if (o instanceof BloomFilter) {
165 BloomFilter<?> that = (BloomFilter<?>) o;
166 return this.numHashFunctions == that.numHashFunctions
167 && this.bits.equals(that.bits)
168 && this.funnel == that.funnel
169 && this.strategy == that.strategy;
170 }
171 return false;
172 }
173
174 @Override public int hashCode() {
175 return bits.hashCode();
176 }
177
178 @VisibleForTesting int getHashCount() {
179 return numHashFunctions;
180 }
181
182 /**
183 * Creates a {@code Builder} of a {@link BloomFilter BloomFilter<T>}, with the expected number
184 * of insertions and expected false positive probability.
185 *
186 * <p>Note that overflowing a {@code BloomFilter} with significantly more elements
187 * than specified, will result in its saturation, and a sharp deterioration of its
188 * false positive probability.
189 *
190 * <p>The constructed {@code BloomFilter<T>} will be serializable if the provided
191 * {@code Funnel<T>} is.
192 *
193 * <p>It is recommended the funnel is implemented as a Java enum. This has the benefit of ensuring
194 * proper serialization and deserialization, which is important since {@link #equals} also relies
195 * on object identity of funnels.
196 *
197 * @param funnel the funnel of T's that the constructed {@code BloomFilter<T>} will use
198 * @param expectedInsertions the number of expected insertions to the constructed
199 * {@code BloomFilter<T>}; must be positive
200 * @param falsePositiveProbability the desired false positive probability (must be positive and
201 * less than 1.0)
202 * @return a {@code BloomFilter}
203 */
204 public static <T> BloomFilter<T> create(Funnel<T> funnel, int expectedInsertions /* n */,
205 double falsePositiveProbability) {
206 checkNotNull(funnel);
207 checkArgument(expectedInsertions >= 0, "Expected insertions cannot be negative");
208 checkArgument(falsePositiveProbability > 0.0 & falsePositiveProbability < 1.0,
209 "False positive probability in (0.0, 1.0)");
210 if (expectedInsertions == 0) {
211 expectedInsertions = 1;
212 }
213 /*
214 * andreou: I wanted to put a warning in the javadoc about tiny fpp values,
215 * since the resulting size is proportional to -log(p), but there is not
216 * much of a point after all, e.g. optimalM(1000, 0.0000000000000001) = 76680
217 * which is less that 10kb. Who cares!
218 */
219 int numBits = optimalNumOfBits(expectedInsertions, falsePositiveProbability);
220 int numHashFunctions = optimalNumOfHashFunctions(expectedInsertions, numBits);
221 return new BloomFilter<T>(new BitArray(numBits), numHashFunctions, funnel,
222 BloomFilterStrategies.MURMUR128_MITZ_32);
223 }
224
225 /**
226 * Creates a {@code Builder} of a {@link BloomFilter BloomFilter<T>}, with the expected number
227 * of insertions, and a default expected false positive probability of 3%.
228 *
229 * <p>Note that overflowing a {@code BloomFilter} with significantly more elements
230 * than specified, will result in its saturation, and a sharp deterioration of its
231 * false positive probability.
232 *
233 * <p>The constructed {@code BloomFilter<T>} will be serializable if the provided
234 * {@code Funnel<T>} is.
235 *
236 * @param funnel the funnel of T's that the constructed {@code BloomFilter<T>} will use
237 * @param expectedInsertions the number of expected insertions to the constructed
238 * {@code BloomFilter<T>}; must be positive
239 * @return a {@code BloomFilter}
240 */
241 public static <T> BloomFilter<T> create(Funnel<T> funnel, int expectedInsertions /* n */) {
242 return create(funnel, expectedInsertions, 0.03); // FYI, for 3%, we always get 5 hash functions
243 }
244
245 /*
246 * Cheat sheet:
247 *
248 * m: total bits
249 * n: expected insertions
250 * b: m/n, bits per insertion
251
252 * p: expected false positive probability
253 *
254 * 1) Optimal k = b * ln2
255 * 2) p = (1 - e ^ (-kn/m))^k
256 * 3) For optimal k: p = 2 ^ (-k) ~= 0.6185^b
257 * 4) For optimal k: m = -nlnp / ((ln2) ^ 2)
258 */
259
260 private static final double LN2 = Math.log(2);
261 private static final double LN2_SQUARED = LN2 * LN2;
262
263 /**
264 * Computes the optimal k (number of hashes per element inserted in Bloom filter), given the
265 * expected insertions and total number of bits in the Bloom filter.
266 *
267 * See http://en.wikipedia.org/wiki/File:Bloom_filter_fp_probability.svg for the formula.
268 *
269 * @param n expected insertions (must be positive)
270 * @param m total number of bits in Bloom filter (must be positive)
271 */
272 @VisibleForTesting static int optimalNumOfHashFunctions(int n, int m) {
273 return Math.max(1, (int) Math.round(m / n * LN2));
274 }
275
276 /**
277 * Computes m (total bits of Bloom filter) which is expected to achieve, for the specified
278 * expected insertions, the required false positive probability.
279 *
280 * See http://en.wikipedia.org/wiki/Bloom_filter#Probability_of_false_positives for the formula.
281 *
282 * @param n expected insertions (must be positive)
283 * @param p false positive rate (must be 0 < p < 1)
284 */
285 @VisibleForTesting static int optimalNumOfBits(int n, double p) {
286 return (int) (-n * Math.log(p) / LN2_SQUARED);
287 }
288
289 private Object writeReplace() {
290 return new SerialForm<T>(this);
291 }
292
293 private static class SerialForm<T> implements Serializable {
294 final long[] data;
295 final int numHashFunctions;
296 final Funnel<T> funnel;
297 final Strategy strategy;
298
299 SerialForm(BloomFilter<T> bf) {
300 this.data = bf.bits.data;
301 this.numHashFunctions = bf.numHashFunctions;
302 this.funnel = bf.funnel;
303 this.strategy = bf.strategy;
304 }
305 Object readResolve() {
306 return new BloomFilter<T>(new BitArray(data), numHashFunctions, funnel, strategy);
307 }
308 private static final long serialVersionUID = 1;
309 }
310 }