1 //  Copyright (c) 2011-present, Facebook, Inc.  All rights reserved.
2 //  This source code is licensed under both the GPLv2 (found in the
3 //  COPYING file in the root directory) and Apache 2.0 License
4 //  (found in the LICENSE.Apache file in the root directory).
5 //
6 // Copyright (c) 2011 The LevelDB Authors. All rights reserved.
7 // Use of this source code is governed by a BSD-style license that can be
8 // found in the LICENSE file. See the AUTHORS file for names of contributors.
9 
10 #pragma once
11 #include <stdint.h>
12 #include <algorithm>
13 #include <random>
14 
15 #include "rocksdb/rocksdb_namespace.h"
16 
17 namespace ROCKSDB_NAMESPACE {
18 
19 // A very simple random number generator.  Not especially good at
20 // generating truly random bits, but good enough for our needs in this
21 // package.
22 class Random {
23  private:
24   enum : uint32_t {
25     M = 2147483647L  // 2^31-1
26   };
27   enum : uint64_t {
28     A = 16807  // bits 14, 8, 7, 5, 2, 1, 0
29   };
30 
31   uint32_t seed_;
32 
GoodSeed(uint32_t s)33   static uint32_t GoodSeed(uint32_t s) { return (s & M) != 0 ? (s & M) : 1; }
34 
35  public:
36   // This is the largest value that can be returned from Next()
37   enum : uint32_t { kMaxNext = M };
38 
Random(uint32_t s)39   explicit Random(uint32_t s) : seed_(GoodSeed(s)) {}
40 
Reset(uint32_t s)41   void Reset(uint32_t s) { seed_ = GoodSeed(s); }
42 
Next()43   uint32_t Next() {
44     // We are computing
45     //       seed_ = (seed_ * A) % M,    where M = 2^31-1
46     //
47     // seed_ must not be zero or M, or else all subsequent computed values
48     // will be zero or M respectively.  For all other values, seed_ will end
49     // up cycling through every number in [1,M-1]
50     uint64_t product = seed_ * A;
51 
52     // Compute (product % M) using the fact that ((x << 31) % M) == x.
53     seed_ = static_cast<uint32_t>((product >> 31) + (product & M));
54     // The first reduction may overflow by 1 bit, so we may need to
55     // repeat.  mod == M is not possible; using > allows the faster
56     // sign-bit-based test.
57     if (seed_ > M) {
58       seed_ -= M;
59     }
60     return seed_;
61   }
62 
63   // Returns a uniformly distributed value in the range [0..n-1]
64   // REQUIRES: n > 0
Uniform(int n)65   uint32_t Uniform(int n) { return Next() % n; }
66 
67   // Randomly returns true ~"1/n" of the time, and false otherwise.
68   // REQUIRES: n > 0
OneIn(int n)69   bool OneIn(int n) { return Uniform(n) == 0; }
70 
71   // "Optional" one-in-n, where 0 or negative always returns false
72   // (may or may not consume a random value)
OneInOpt(int n)73   bool OneInOpt(int n) { return n > 0 && OneIn(n); }
74 
75   // Returns random bool that is true for the given percentage of
76   // calls on average. Zero or less is always false and 100 or more
77   // is always true (may or may not consume a random value)
PercentTrue(int percentage)78   bool PercentTrue(int percentage) {
79     return static_cast<int>(Uniform(100)) < percentage;
80   }
81 
82   // Skewed: pick "base" uniformly from range [0,max_log] and then
83   // return "base" random bits.  The effect is to pick a number in the
84   // range [0,2^max_log-1] with exponential bias towards smaller numbers.
Skewed(int max_log)85   uint32_t Skewed(int max_log) {
86     return Uniform(1 << Uniform(max_log + 1));
87   }
88 
89   // Returns a random string of length "len"
90   std::string RandomString(int len);
91 
92   // Generates a random string of len bytes using human-readable characters
93   std::string HumanReadableString(int len);
94 
95   // Generates a random binary data
96   std::string RandomBinaryString(int len);
97 
98   // Returns a Random instance for use by the current thread without
99   // additional locking
100   static Random* GetTLSInstance();
101 };
102 
103 // A good 32-bit random number generator based on std::mt19937.
104 // This exists in part to avoid compiler variance in warning about coercing
105 // uint_fast32_t from mt19937 to uint32_t.
106 class Random32 {
107  private:
108   std::mt19937 generator_;
109 
110  public:
Random32(uint32_t s)111   explicit Random32(uint32_t s) : generator_(s) {}
112 
113   // Generates the next random number
Next()114   uint32_t Next() { return static_cast<uint32_t>(generator_()); }
115 
116   // Returns a uniformly distributed value in the range [0..n-1]
117   // REQUIRES: n > 0
Uniform(uint32_t n)118   uint32_t Uniform(uint32_t n) {
119     return static_cast<uint32_t>(
120         std::uniform_int_distribution<std::mt19937::result_type>(
121             0, n - 1)(generator_));
122   }
123 
124   // Returns an *almost* uniformly distributed value in the range [0..n-1].
125   // Much faster than Uniform().
126   // REQUIRES: n > 0
Uniformish(uint32_t n)127   uint32_t Uniformish(uint32_t n) {
128     // fastrange (without the header)
129     return static_cast<uint32_t>((uint64_t(generator_()) * uint64_t(n)) >> 32);
130   }
131 
132   // Randomly returns true ~"1/n" of the time, and false otherwise.
133   // REQUIRES: n > 0
OneIn(uint32_t n)134   bool OneIn(uint32_t n) { return Uniform(n) == 0; }
135 
136   // Skewed: pick "base" uniformly from range [0,max_log] and then
137   // return "base" random bits.  The effect is to pick a number in the
138   // range [0,2^max_log-1] with exponential bias towards smaller numbers.
Skewed(int max_log)139   uint32_t Skewed(int max_log) {
140     return Uniform(uint32_t{1} << Uniform(max_log + 1));
141   }
142 
143   // Reset the seed of the generator to the given value
Seed(uint32_t new_seed)144   void Seed(uint32_t new_seed) { generator_.seed(new_seed); }
145 };
146 
147 // A good 64-bit random number generator based on std::mt19937_64
148 class Random64 {
149  private:
150   std::mt19937_64 generator_;
151 
152  public:
Random64(uint64_t s)153   explicit Random64(uint64_t s) : generator_(s) { }
154 
155   // Generates the next random number
Next()156   uint64_t Next() { return generator_(); }
157 
158   // Returns a uniformly distributed value in the range [0..n-1]
159   // REQUIRES: n > 0
Uniform(uint64_t n)160   uint64_t Uniform(uint64_t n) {
161     return std::uniform_int_distribution<uint64_t>(0, n - 1)(generator_);
162   }
163 
164   // Randomly returns true ~"1/n" of the time, and false otherwise.
165   // REQUIRES: n > 0
OneIn(uint64_t n)166   bool OneIn(uint64_t n) { return Uniform(n) == 0; }
167 
168   // Skewed: pick "base" uniformly from range [0,max_log] and then
169   // return "base" random bits.  The effect is to pick a number in the
170   // range [0,2^max_log-1] with exponential bias towards smaller numbers.
Skewed(int max_log)171   uint64_t Skewed(int max_log) {
172     return Uniform(uint64_t(1) << Uniform(max_log + 1));
173   }
174 };
175 
176 // A seeded replacement for removed std::random_shuffle
177 template <class RandomIt>
RandomShuffle(RandomIt first,RandomIt last,uint32_t seed)178 void RandomShuffle(RandomIt first, RandomIt last, uint32_t seed) {
179   std::mt19937 rng(seed);
180   std::shuffle(first, last, rng);
181 }
182 
183 // A replacement for removed std::random_shuffle
184 template <class RandomIt>
RandomShuffle(RandomIt first,RandomIt last)185 void RandomShuffle(RandomIt first, RandomIt last) {
186   RandomShuffle(first, last, std::random_device{}());
187 }
188 
189 }  // namespace ROCKSDB_NAMESPACE
190