1 /*
2 * Licensed to the Apache Software Foundation (ASF) under one or more
3 * contributor license agreements. See the NOTICE file distributed with
4 * this work for additional information regarding copyright ownership.
5 * The ASF licenses this file to You under the Apache License, Version 2.0
6 * (the "License"); you may not use this file except in compliance with
7 * the License. You may obtain a copy of the License at
8 *
9 * http://www.apache.org/licenses/LICENSE-2.0
10 *
11 * Unless required by applicable law or agreed to in writing, software
12 * distributed under the License is distributed on an "AS IS" BASIS,
13 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 * See the License for the specific language governing permissions and
15 * limitations under the License.
16 */
17 package org.apache.commons.collections4.bloomfilter;
18
19 import java.util.Objects;
20 import java.util.function.IntPredicate;
21
22 /**
23 * A Hasher that implements combinatorial hashing as described by
24 * <a href="https://www.eecs.harvard.edu/~michaelm/postscripts/tr-02-05.pdf">Krisch and Mitzenmacher</a> using the enhanced double hashing technique
25 * described in the wikipedia article <a href="https://en.wikipedia.org/wiki/Double_hashing#Enhanced_double_hashing">Double Hashing</a>.
26 * <p>
27 * Common use for this hasher is to generate bit indices from a byte array output of a hashing
28 * or MessageDigest algorithm.</p>
29 *
30 * <h2>Thoughts on the hasher input</h2>
31 *
32 *<p>Note that it is worse to create smaller numbers for the {@code initial} and {@code increment}. If the {@code initial} is smaller than
33 * the number of bits in a filter then hashing will start at the same point when the size increases; likewise the {@code increment} will be
34 * the same if it remains smaller than the number of bits in the filter and so the first few indices will be the same if the number of bits
35 * changes (but is still larger than the {@code increment}). In a worse case scenario with small {@code initial} and {@code increment} for
36 * all items, hashing may not create indices that fill the full region within a much larger filter. Imagine hashers created with {@code initial}
37 * and {@code increment} values less than 255 with a filter size of 30000 and number of hash functions as 5. Ignoring the
38 * tetrahedral addition (a maximum of 20 for k=5) the max index is 255 * 4 + 255 = 1275, this covers 4.25% of the filter. This also
39 * ignores the negative wrapping but the behavior is the same, some bits cannot be reached.
40 * </p><p>
41 * So this needs to be avoided as the filter probability assumptions will be void. If the {@code initial} and {@code increment} are larger
42 * than the number of bits then the modulus will create a 'random' position and increment within the size.
43 * </p>
44 *
45 * @since 4.5
46 */
47 public class EnhancedDoubleHasher implements Hasher {
48
49 /**
50 * Convert bytes to big-endian long filling with zero bytes as necessary..
51 * @param byteArray the byte array to extract the values from.
52 * @param offset the offset to start extraction from.
53 * @param len the length of the extraction, may be longer than 8.
54 * @return
55 */
56 private static long toLong(final byte[] byteArray, final int offset, final int len) {
57 long val = 0;
58 int shift = Long.SIZE;
59 final int end = offset + Math.min(len, Long.BYTES);
60 for (int i = offset; i < end; i++) {
61 shift -= Byte.SIZE;
62 val |= (long) (byteArray[i] & 0xFF) << shift;
63 }
64 return val;
65 }
66
67 /**
68 * The initial hash value.
69 */
70 private final long initial;
71
72 /**
73 * The value to increment the hash value by.
74 */
75 private final long increment;
76
77 /**
78 * Constructs the EnhancedDoubleHasher from a byte array.
79 * <p>
80 * This method simplifies the conversion from a Digest or hasher algorithm output
81 * to the two values used by the EnhancedDoubleHasher.</p>
82 * <p>The byte array is split in 2 and the first 8 bytes of each half are interpreted as a big-endian long value.
83 * Excess bytes are ignored.
84 * If there are fewer than 16 bytes the following conversions are made.
85 *</p>
86 * <ol>
87 * <li>If there is an odd number of bytes the excess byte is assigned to the increment value</li>
88 * <li>The bytes alloted are read in big-endian order any byte not populated is set to zero.</li>
89 * </ol>
90 * <p>
91 * This ensures that small arrays generate the largest possible increment and initial values.
92 * </p>
93 * @param buffer the buffer to extract the longs from.
94 * @throws IllegalArgumentException is buffer length is zero.
95 */
96 public EnhancedDoubleHasher(final byte[] buffer) {
97 if (buffer.length == 0) {
98 throw new IllegalArgumentException("buffer length must be greater than 0");
99 }
100 // divide by 2
101 final int segment = buffer.length / 2;
102 this.initial = toLong(buffer, 0, segment);
103 this.increment = toLong(buffer, segment, buffer.length - segment);
104 }
105
106 /**
107 * Constructs the EnhancedDoubleHasher from 2 longs. The long values will be interpreted as unsigned values.
108 * @param initial The initial value for the hasher.
109 * @param increment The value to increment the hash by on each iteration.
110 */
111 public EnhancedDoubleHasher(final long initial, final long increment) {
112 this.initial = initial;
113 this.increment = increment;
114 }
115
116 /**
117 * Gets the increment value for the hash calculation.
118 * @return the increment value for the hash calculation.
119 */
120 long getIncrement() {
121 return increment;
122 }
123
124 /**
125 * Gets the initial value for the hash calculation.
126 * @return the initial value for the hash calculation.
127 */
128 long getInitial() {
129 return initial;
130 }
131
132 @Override
133 public IndexProducer indices(final Shape shape) {
134 Objects.requireNonNull(shape, "shape");
135
136 return new IndexProducer() {
137
138 @Override
139 public int[] asIndexArray() {
140 final int[] result = new int[shape.getNumberOfHashFunctions()];
141 final int[] idx = new int[1];
142
143 // This method needs to return duplicate indices
144
145 forEachIndex(i -> {
146 result[idx[0]++] = i;
147 return true;
148 });
149 return result;
150 }
151
152 @Override
153 public boolean forEachIndex(final IntPredicate consumer) {
154 Objects.requireNonNull(consumer, "consumer");
155 final int bits = shape.getNumberOfBits();
156 // Enhanced double hashing:
157 // hash[i] = ( h1(x) + i*h2(x) + (i*i*i - i)/6 ) mod bits
158 // See: https://en.wikipedia.org/wiki/Double_hashing#Enhanced_double_hashing
159 //
160 // Essentially this is computing a wrapped modulus from a start point and an
161 // increment and an additional term as a tetrahedral number.
162 // You only need two modulus operations before the loop. Within the loop
163 // the modulus is handled using the sign bit to detect wrapping to ensure:
164 // 0 <= index < bits
165 // 0 <= inc < bits
166 // The final hash is:
167 // hash[i] = ( h1(x) - i*h2(x) - (i*i*i - i)/6 ) wrapped in [0, bits)
168
169 int index = BitMap.mod(initial, bits);
170 int inc = BitMap.mod(increment, bits);
171
172 final int k = shape.getNumberOfHashFunctions();
173 if (k > bits) {
174 for (int j = k; j > 0;) {
175 // handle k > bits
176 final int block = Math.min(j, bits);
177 j -= block;
178 for (int i = 0; i < block; i++) {
179 if (!consumer.test(index)) {
180 return false;
181 }
182 // Update index and handle wrapping
183 index -= inc;
184 index = index < 0 ? index + bits : index;
185
186 // Incorporate the counter into the increment to create a
187 // tetrahedral number additional term, and handle wrapping.
188 inc -= i;
189 inc = inc < 0 ? inc + bits : inc;
190 }
191 }
192 } else {
193 for (int i = 0; i < k; i++) {
194 if (!consumer.test(index)) {
195 return false;
196 }
197 // Update index and handle wrapping
198 index -= inc;
199 index = index < 0 ? index + bits : index;
200
201 // Incorporate the counter into the increment to create a
202 // tetrahedral number additional term, and handle wrapping.
203 inc -= i;
204 inc = inc < 0 ? inc + bits : inc;
205 }
206 }
207 return true;
208 }
209 };
210 }
211 }