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// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
// This source code is licensed under both the GPLv2 (found in the
// COPYING file in the root directory) and Apache 2.0 License
// (found in the LICENSE.Apache file in the root directory).
//
// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file. See the AUTHORS file for names of contributors.
#pragma once
#include <stdint.h>
#include <random>
#include "rocksdb/rocksdb_namespace.h"
namespace ROCKSDB_NAMESPACE {
// A very simple random number generator. Not especially good at
// generating truly random bits, but good enough for our needs in this
// package.
class Random {
private:
enum : uint32_t {
M = 2147483647L // 2^31-1
};
enum : uint64_t {
A = 16807 // bits 14, 8, 7, 5, 2, 1, 0
};
uint32_t seed_;
static uint32_t GoodSeed(uint32_t s) { return (s & M) != 0 ? (s & M) : 1; }
public:
// This is the largest value that can be returned from Next()
enum : uint32_t { kMaxNext = M };
explicit Random(uint32_t s) : seed_(GoodSeed(s)) {}
void Reset(uint32_t s) { seed_ = GoodSeed(s); }
uint32_t Next() {
// We are computing
// seed_ = (seed_ * A) % M, where M = 2^31-1
//
// seed_ must not be zero or M, or else all subsequent computed values
// will be zero or M respectively. For all other values, seed_ will end
// up cycling through every number in [1,M-1]
uint64_t product = seed_ * A;
// Compute (product % M) using the fact that ((x << 31) % M) == x.
seed_ = static_cast<uint32_t>((product >> 31) + (product & M));
// The first reduction may overflow by 1 bit, so we may need to
// repeat. mod == M is not possible; using > allows the faster
// sign-bit-based test.
if (seed_ > M) {
seed_ -= M;
}
return seed_;
}
// Returns a uniformly distributed value in the range [0..n-1]
// REQUIRES: n > 0
uint32_t Uniform(int n) { return Next() % n; }
// Randomly returns true ~"1/n" of the time, and false otherwise.
// REQUIRES: n > 0
bool OneIn(int n) { return Uniform(n) == 0; }
// "Optional" one-in-n, where 0 or negative always returns false
// (may or may not consume a random value)
bool OneInOpt(int n) { return n > 0 && OneIn(n); }
// Returns random bool that is true for the given percentage of
// calls on average. Zero or less is always false and 100 or more
// is always true (may or may not consume a random value)
bool PercentTrue(int percentage) {
return static_cast<int>(Uniform(100)) < percentage;
}
// Skewed: pick "base" uniformly from range [0,max_log] and then
// return "base" random bits. The effect is to pick a number in the
// range [0,2^max_log-1] with exponential bias towards smaller numbers.
uint32_t Skewed(int max_log) {
return Uniform(1 << Uniform(max_log + 1));
}
// Returns a Random instance for use by the current thread without
// additional locking
static Random* GetTLSInstance();
};
// A good 32-bit random number generator based on std::mt19937.
// This exists in part to avoid compiler variance in warning about coercing
// uint_fast32_t from mt19937 to uint32_t.
class Random32 {
private:
std::mt19937 generator_;
public:
explicit Random32(uint32_t s) : generator_(s) {}
// Generates the next random number
uint32_t Next() { return static_cast<uint32_t>(generator_()); }
// Returns a uniformly distributed value in the range [0..n-1]
// REQUIRES: n > 0
uint32_t Uniform(uint32_t n) {
return static_cast<uint32_t>(
std::uniform_int_distribution<std::mt19937::result_type>(
0, n - 1)(generator_));
}
// Returns an *almost* uniformly distributed value in the range [0..n-1].
// Much faster than Uniform().
// REQUIRES: n > 0
uint32_t Uniformish(uint32_t n) {
// fastrange (without the header)
return static_cast<uint32_t>((uint64_t(generator_()) * uint64_t(n)) >> 32);
}
// Randomly returns true ~"1/n" of the time, and false otherwise.
// REQUIRES: n > 0
bool OneIn(uint32_t n) { return Uniform(n) == 0; }
// Skewed: pick "base" uniformly from range [0,max_log] and then
// return "base" random bits. The effect is to pick a number in the
// range [0,2^max_log-1] with exponential bias towards smaller numbers.
uint32_t Skewed(int max_log) {
return Uniform(uint32_t{1} << Uniform(max_log + 1));
}
// Reset the seed of the generator to the given value
void Seed(uint32_t new_seed) { generator_.seed(new_seed); }
};
// A good 64-bit random number generator based on std::mt19937_64
class Random64 {
private:
std::mt19937_64 generator_;
public:
explicit Random64(uint64_t s) : generator_(s) { }
// Generates the next random number
uint64_t Next() { return generator_(); }
// Returns a uniformly distributed value in the range [0..n-1]
// REQUIRES: n > 0
uint64_t Uniform(uint64_t n) {
return std::uniform_int_distribution<uint64_t>(0, n - 1)(generator_);
}
// Randomly returns true ~"1/n" of the time, and false otherwise.
// REQUIRES: n > 0
bool OneIn(uint64_t n) { return Uniform(n) == 0; }
// Skewed: pick "base" uniformly from range [0,max_log] and then
// return "base" random bits. The effect is to pick a number in the
// range [0,2^max_log-1] with exponential bias towards smaller numbers.
uint64_t Skewed(int max_log) {
return Uniform(uint64_t(1) << Uniform(max_log + 1));
}
};
} // namespace ROCKSDB_NAMESPACE
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