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rocksdb/db_stress_tool/db_stress_common.cc

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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.
//
#ifdef GFLAGS
#include "db_stress_tool/db_stress_common.h"
#include <cmath>
rocksdb::DbStressEnvWrapper* db_stress_env = nullptr;
enum rocksdb::CompressionType compression_type_e = rocksdb::kSnappyCompression;
enum rocksdb::CompressionType bottommost_compression_type_e =
rocksdb::kSnappyCompression;
enum rocksdb::ChecksumType checksum_type_e = rocksdb::kCRC32c;
enum RepFactory FLAGS_rep_factory = kSkipList;
std::vector<double> sum_probs(100001);
int64_t zipf_sum_size = 100000;
namespace rocksdb {
// Zipfian distribution is generated based on a pre-calculated array.
// It should be used before start the stress test.
// First, the probability distribution function (PDF) of this Zipfian follows
// power low. P(x) = 1/(x^alpha).
// So we calculate the PDF when x is from 0 to zipf_sum_size in first for loop
// and add the PDF value togetger as c. So we get the total probability in c.
// Next, we calculate inverse CDF of Zipfian and store the value of each in
// an array (sum_probs). The rank is from 0 to zipf_sum_size. For example, for
// integer k, its Zipfian CDF value is sum_probs[k].
// Third, when we need to get an integer whose probability follows Zipfian
// distribution, we use a rand_seed [0,1] which follows uniform distribution
// as a seed and search it in the sum_probs via binary search. When we find
// the closest sum_probs[i] of rand_seed, i is the integer that in
// [0, zipf_sum_size] following Zipfian distribution with parameter alpha.
// Finally, we can scale i to [0, max_key] scale.
// In order to avoid that hot keys are close to each other and skew towards 0,
// we use Rando64 to shuffle it.
void InitializeHotKeyGenerator(double alpha) {
double c = 0;
for (int64_t i = 1; i <= zipf_sum_size; i++) {
c = c + (1.0 / std::pow(static_cast<double>(i), alpha));
}
c = 1.0 / c;
sum_probs[0] = 0;
for (int64_t i = 1; i <= zipf_sum_size; i++) {
sum_probs[i] =
sum_probs[i - 1] + c / std::pow(static_cast<double>(i), alpha);
}
}
// Generate one key that follows the Zipfian distribution. The skewness
// is decided by the parameter alpha. Input is the rand_seed [0,1] and
// the max of the key to be generated. If we directly return tmp_zipf_seed,
// the closer to 0, the higher probability will be. To randomly distribute
// the hot keys in [0, max_key], we use Random64 to shuffle it.
int64_t GetOneHotKeyID(double rand_seed, int64_t max_key) {
int64_t low = 1, mid, high = zipf_sum_size, zipf = 0;
while (low <= high) {
mid = (low + high) / 2;
if (sum_probs[mid] >= rand_seed && sum_probs[mid - 1] < rand_seed) {
zipf = mid;
break;
} else if (sum_probs[mid] >= rand_seed) {
high = mid - 1;
} else {
low = mid + 1;
}
}
int64_t tmp_zipf_seed = zipf * max_key / zipf_sum_size;
Random64 rand_local(tmp_zipf_seed);
return rand_local.Next() % max_key;
}
void PoolSizeChangeThread(void* v) {
assert(FLAGS_compaction_thread_pool_adjust_interval > 0);
ThreadState* thread = reinterpret_cast<ThreadState*>(v);
SharedState* shared = thread->shared;
while (true) {
{
MutexLock l(shared->GetMutex());
if (shared->ShouldStopBgThread()) {
shared->IncBgThreadsFinished();
if (shared->BgThreadsFinished()) {
shared->GetCondVar()->SignalAll();
}
return;
}
}
auto thread_pool_size_base = FLAGS_max_background_compactions;
auto thread_pool_size_var = FLAGS_compaction_thread_pool_variations;
int new_thread_pool_size =
thread_pool_size_base - thread_pool_size_var +
thread->rand.Next() % (thread_pool_size_var * 2 + 1);
if (new_thread_pool_size < 1) {
new_thread_pool_size = 1;
}
db_stress_env->SetBackgroundThreads(new_thread_pool_size,
rocksdb::Env::Priority::LOW);
// Sleep up to 3 seconds
db_stress_env->SleepForMicroseconds(
thread->rand.Next() % FLAGS_compaction_thread_pool_adjust_interval *
1000 +
1);
}
}
void DbVerificationThread(void* v) {
assert(FLAGS_continuous_verification_interval > 0);
auto* thread = reinterpret_cast<ThreadState*>(v);
SharedState* shared = thread->shared;
StressTest* stress_test = shared->GetStressTest();
assert(stress_test != nullptr);
while (true) {
{
MutexLock l(shared->GetMutex());
if (shared->ShouldStopBgThread()) {
shared->IncBgThreadsFinished();
if (shared->BgThreadsFinished()) {
shared->GetCondVar()->SignalAll();
}
return;
}
}
if (!shared->HasVerificationFailedYet()) {
stress_test->ContinuouslyVerifyDb(thread);
}
db_stress_env->SleepForMicroseconds(
thread->rand.Next() % FLAGS_continuous_verification_interval * 1000 +
1);
}
}
void PrintKeyValue(int cf, uint64_t key, const char* value, size_t sz) {
if (!FLAGS_verbose) {
return;
}
std::string tmp;
tmp.reserve(sz * 2 + 16);
char buf[4];
for (size_t i = 0; i < sz; i++) {
snprintf(buf, 4, "%X", value[i]);
tmp.append(buf);
}
fprintf(stdout, "[CF %d] %" PRIi64 " == > (%" ROCKSDB_PRIszt ") %s\n", cf,
key, sz, tmp.c_str());
}
// Note that if hot_key_alpha != 0, it generates the key based on Zipfian
// distribution. Keys are randomly scattered to [0, FLAGS_max_key]. It does
// not ensure the order of the keys being generated and the keys does not have
// the active range which is related to FLAGS_active_width.
int64_t GenerateOneKey(ThreadState* thread, uint64_t iteration) {
const double completed_ratio =
static_cast<double>(iteration) / FLAGS_ops_per_thread;
const int64_t base_key = static_cast<int64_t>(
completed_ratio * (FLAGS_max_key - FLAGS_active_width));
int64_t rand_seed = base_key + thread->rand.Next() % FLAGS_active_width;
int64_t cur_key = rand_seed;
if (FLAGS_hot_key_alpha != 0) {
// If set the Zipfian distribution Alpha to non 0, use Zipfian
double float_rand =
(static_cast<double>(thread->rand.Next() % FLAGS_max_key)) /
FLAGS_max_key;
cur_key = GetOneHotKeyID(float_rand, FLAGS_max_key);
}
return cur_key;
}
// Note that if hot_key_alpha != 0, it generates the key based on Zipfian
// distribution. Keys being generated are in random order.
// If user want to generate keys based on uniform distribution, user needs to
// set hot_key_alpha == 0. It will generate the random keys in increasing
// order in the key array (ensure key[i] >= key[i+1]) and constrained in a
// range related to FLAGS_active_width.
std::vector<int64_t> GenerateNKeys(ThreadState* thread, int num_keys,
uint64_t iteration) {
const double completed_ratio =
static_cast<double>(iteration) / FLAGS_ops_per_thread;
const int64_t base_key = static_cast<int64_t>(
completed_ratio * (FLAGS_max_key - FLAGS_active_width));
std::vector<int64_t> keys;
keys.reserve(num_keys);
int64_t next_key = base_key + thread->rand.Next() % FLAGS_active_width;
keys.push_back(next_key);
for (int i = 1; i < num_keys; ++i) {
// Generate the key follows zipfian distribution
if (FLAGS_hot_key_alpha != 0) {
double float_rand =
(static_cast<double>(thread->rand.Next() % FLAGS_max_key)) /
FLAGS_max_key;
next_key = GetOneHotKeyID(float_rand, FLAGS_max_key);
} else {
// This may result in some duplicate keys
next_key = next_key + thread->rand.Next() %
(FLAGS_active_width - (next_key - base_key));
}
keys.push_back(next_key);
}
return keys;
}
size_t GenerateValue(uint32_t rand, char* v, size_t max_sz) {
size_t value_sz =
((rand % kRandomValueMaxFactor) + 1) * FLAGS_value_size_mult;
assert(value_sz <= max_sz && value_sz >= sizeof(uint32_t));
(void)max_sz;
*((uint32_t*)v) = rand;
for (size_t i = sizeof(uint32_t); i < value_sz; i++) {
v[i] = (char)(rand ^ i);
}
v[value_sz] = '\0';
return value_sz; // the size of the value set.
}
} // namespace rocksdb
#endif // GFLAGS