c9a5e48762
Summary: Fix build warnings on MSVC. siying Pull Request resolved: https://github.com/facebook/rocksdb/pull/6309 Differential Revision: D19455012 Pulled By: ltamasi fbshipit-source-id: 940739f2c92de60e47cc2bed8dd7f921459545a9
224 lines
8.4 KiB
C++
224 lines
8.4 KiB
C++
// Copyright (c) 2011-present, Facebook, Inc. All rights reserved.
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// This source code is licensed under both the GPLv2 (found in the
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// COPYING file in the root directory) and Apache 2.0 License
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// (found in the LICENSE.Apache file in the root directory).
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//
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// Copyright (c) 2011 The LevelDB Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style license that can be
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// found in the LICENSE file. See the AUTHORS file for names of contributors.
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//
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#ifdef GFLAGS
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#include "db_stress_tool/db_stress_common.h"
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#include <cmath>
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rocksdb::DbStressEnvWrapper* db_stress_env = nullptr;
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enum rocksdb::CompressionType compression_type_e = rocksdb::kSnappyCompression;
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enum rocksdb::CompressionType bottommost_compression_type_e =
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rocksdb::kSnappyCompression;
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enum rocksdb::ChecksumType checksum_type_e = rocksdb::kCRC32c;
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enum RepFactory FLAGS_rep_factory = kSkipList;
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std::vector<double> sum_probs(100001);
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int64_t zipf_sum_size = 100000;
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namespace rocksdb {
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// Zipfian distribution is generated based on a pre-calculated array.
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// It should be used before start the stress test.
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// First, the probability distribution function (PDF) of this Zipfian follows
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// power low. P(x) = 1/(x^alpha).
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// So we calculate the PDF when x is from 0 to zipf_sum_size in first for loop
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// and add the PDF value togetger as c. So we get the total probability in c.
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// Next, we calculate inverse CDF of Zipfian and store the value of each in
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// an array (sum_probs). The rank is from 0 to zipf_sum_size. For example, for
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// integer k, its Zipfian CDF value is sum_probs[k].
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// Third, when we need to get an integer whose probability follows Zipfian
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// distribution, we use a rand_seed [0,1] which follows uniform distribution
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// as a seed and search it in the sum_probs via binary search. When we find
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// the closest sum_probs[i] of rand_seed, i is the integer that in
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// [0, zipf_sum_size] following Zipfian distribution with parameter alpha.
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// Finally, we can scale i to [0, max_key] scale.
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// In order to avoid that hot keys are close to each other and skew towards 0,
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// we use Rando64 to shuffle it.
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void InitializeHotKeyGenerator(double alpha) {
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double c = 0;
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for (int64_t i = 1; i <= zipf_sum_size; i++) {
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c = c + (1.0 / std::pow(static_cast<double>(i), alpha));
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}
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c = 1.0 / c;
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sum_probs[0] = 0;
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for (int64_t i = 1; i <= zipf_sum_size; i++) {
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sum_probs[i] =
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sum_probs[i - 1] + c / std::pow(static_cast<double>(i), alpha);
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}
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}
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// Generate one key that follows the Zipfian distribution. The skewness
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// is decided by the parameter alpha. Input is the rand_seed [0,1] and
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// the max of the key to be generated. If we directly return tmp_zipf_seed,
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// the closer to 0, the higher probability will be. To randomly distribute
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// the hot keys in [0, max_key], we use Random64 to shuffle it.
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int64_t GetOneHotKeyID(double rand_seed, int64_t max_key) {
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int64_t low = 1, mid, high = zipf_sum_size, zipf = 0;
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while (low <= high) {
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mid = (low + high) / 2;
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if (sum_probs[mid] >= rand_seed && sum_probs[mid - 1] < rand_seed) {
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zipf = mid;
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break;
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} else if (sum_probs[mid] >= rand_seed) {
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high = mid - 1;
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} else {
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low = mid + 1;
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}
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}
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int64_t tmp_zipf_seed = zipf * max_key / zipf_sum_size;
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Random64 rand_local(tmp_zipf_seed);
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return rand_local.Next() % max_key;
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}
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void PoolSizeChangeThread(void* v) {
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assert(FLAGS_compaction_thread_pool_adjust_interval > 0);
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ThreadState* thread = reinterpret_cast<ThreadState*>(v);
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SharedState* shared = thread->shared;
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while (true) {
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{
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MutexLock l(shared->GetMutex());
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if (shared->ShouldStopBgThread()) {
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shared->IncBgThreadsFinished();
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if (shared->BgThreadsFinished()) {
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shared->GetCondVar()->SignalAll();
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}
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return;
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}
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}
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auto thread_pool_size_base = FLAGS_max_background_compactions;
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auto thread_pool_size_var = FLAGS_compaction_thread_pool_variations;
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int new_thread_pool_size =
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thread_pool_size_base - thread_pool_size_var +
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thread->rand.Next() % (thread_pool_size_var * 2 + 1);
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if (new_thread_pool_size < 1) {
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new_thread_pool_size = 1;
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}
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db_stress_env->SetBackgroundThreads(new_thread_pool_size,
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rocksdb::Env::Priority::LOW);
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// Sleep up to 3 seconds
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db_stress_env->SleepForMicroseconds(
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thread->rand.Next() % FLAGS_compaction_thread_pool_adjust_interval *
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1000 +
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1);
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}
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}
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void DbVerificationThread(void* v) {
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assert(FLAGS_continuous_verification_interval > 0);
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auto* thread = reinterpret_cast<ThreadState*>(v);
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SharedState* shared = thread->shared;
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StressTest* stress_test = shared->GetStressTest();
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assert(stress_test != nullptr);
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while (true) {
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{
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MutexLock l(shared->GetMutex());
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if (shared->ShouldStopBgThread()) {
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shared->IncBgThreadsFinished();
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if (shared->BgThreadsFinished()) {
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shared->GetCondVar()->SignalAll();
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}
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return;
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}
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}
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if (!shared->HasVerificationFailedYet()) {
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stress_test->ContinuouslyVerifyDb(thread);
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}
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db_stress_env->SleepForMicroseconds(
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thread->rand.Next() % FLAGS_continuous_verification_interval * 1000 +
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1);
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}
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}
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void PrintKeyValue(int cf, uint64_t key, const char* value, size_t sz) {
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if (!FLAGS_verbose) {
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return;
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}
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std::string tmp;
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tmp.reserve(sz * 2 + 16);
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char buf[4];
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for (size_t i = 0; i < sz; i++) {
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snprintf(buf, 4, "%X", value[i]);
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tmp.append(buf);
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}
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fprintf(stdout, "[CF %d] %" PRIi64 " == > (%" ROCKSDB_PRIszt ") %s\n", cf,
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key, sz, tmp.c_str());
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}
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// Note that if hot_key_alpha != 0, it generates the key based on Zipfian
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// distribution. Keys are randomly scattered to [0, FLAGS_max_key]. It does
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// not ensure the order of the keys being generated and the keys does not have
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// the active range which is related to FLAGS_active_width.
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int64_t GenerateOneKey(ThreadState* thread, uint64_t iteration) {
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const double completed_ratio =
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static_cast<double>(iteration) / FLAGS_ops_per_thread;
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const int64_t base_key = static_cast<int64_t>(
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completed_ratio * (FLAGS_max_key - FLAGS_active_width));
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int64_t rand_seed = base_key + thread->rand.Next() % FLAGS_active_width;
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int64_t cur_key = rand_seed;
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if (FLAGS_hot_key_alpha != 0) {
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// If set the Zipfian distribution Alpha to non 0, use Zipfian
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double float_rand =
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(static_cast<double>(thread->rand.Next() % FLAGS_max_key)) /
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FLAGS_max_key;
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cur_key = GetOneHotKeyID(float_rand, FLAGS_max_key);
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}
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return cur_key;
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}
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// Note that if hot_key_alpha != 0, it generates the key based on Zipfian
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// distribution. Keys being generated are in random order.
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// If user want to generate keys based on uniform distribution, user needs to
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// set hot_key_alpha == 0. It will generate the random keys in increasing
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// order in the key array (ensure key[i] >= key[i+1]) and constrained in a
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// range related to FLAGS_active_width.
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std::vector<int64_t> GenerateNKeys(ThreadState* thread, int num_keys,
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uint64_t iteration) {
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const double completed_ratio =
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static_cast<double>(iteration) / FLAGS_ops_per_thread;
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const int64_t base_key = static_cast<int64_t>(
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completed_ratio * (FLAGS_max_key - FLAGS_active_width));
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std::vector<int64_t> keys;
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keys.reserve(num_keys);
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int64_t next_key = base_key + thread->rand.Next() % FLAGS_active_width;
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keys.push_back(next_key);
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for (int i = 1; i < num_keys; ++i) {
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// Generate the key follows zipfian distribution
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if (FLAGS_hot_key_alpha != 0) {
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double float_rand =
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(static_cast<double>(thread->rand.Next() % FLAGS_max_key)) /
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FLAGS_max_key;
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next_key = GetOneHotKeyID(float_rand, FLAGS_max_key);
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} else {
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// This may result in some duplicate keys
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next_key = next_key + thread->rand.Next() %
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(FLAGS_active_width - (next_key - base_key));
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}
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keys.push_back(next_key);
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}
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return keys;
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}
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size_t GenerateValue(uint32_t rand, char* v, size_t max_sz) {
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size_t value_sz =
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((rand % kRandomValueMaxFactor) + 1) * FLAGS_value_size_mult;
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assert(value_sz <= max_sz && value_sz >= sizeof(uint32_t));
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(void)max_sz;
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*((uint32_t*)v) = rand;
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for (size_t i = sizeof(uint32_t); i < value_sz; i++) {
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v[i] = (char)(rand ^ i);
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}
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v[value_sz] = '\0';
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return value_sz; // the size of the value set.
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}
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} // namespace rocksdb
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#endif // GFLAGS
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