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211 lines
6.8 KiB
C++
211 lines
6.8 KiB
C++
#pragma once
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#include <deque>
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#include <functional>
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#include <atomic>
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#include <mutex>
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#include <future>
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#include <condition_variable>
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#include <set>
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#include <iostream>
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#include <boost/circular_buffer.hpp>
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#include <base/shared_ptr_helper.h>
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#include <base/logger_useful.h>
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#include <Common/ThreadPool.h>
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#include <Common/Stopwatch.h>
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#include <Storages/MergeTree/IExecutableTask.h>
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namespace DB
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{
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namespace ErrorCodes
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{
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extern const int LOGICAL_ERROR;
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}
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struct TaskRuntimeData;
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using TaskRuntimeDataPtr = std::shared_ptr<TaskRuntimeData>;
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/**
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* Has RAII class to determine how many tasks are waiting for the execution and executing at the moment.
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* Also has some flags and primitives to wait for current task to be executed.
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*/
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struct TaskRuntimeData
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{
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TaskRuntimeData(ExecutableTaskPtr && task_, CurrentMetrics::Metric metric_)
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: task(std::move(task_))
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, increment(std::move(metric_))
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{}
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ExecutableTaskPtr task;
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CurrentMetrics::Increment increment;
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std::atomic_bool is_currently_deleting{false};
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/// Actually autoreset=false is needed only for unit test
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/// where multiple threads could remove tasks corresponding to the same storage
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/// This scenario in not possible in reality.
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Poco::Event is_done{/*autoreset=*/false};
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/// This is equal to task->getPriority() not to do useless virtual calls in comparator
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UInt64 priority{0};
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/// By default priority queue will have max element at top
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static bool comparePtrByPriority(const TaskRuntimeDataPtr & lhs, const TaskRuntimeDataPtr & rhs)
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{
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return lhs->priority > rhs->priority;
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}
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};
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class OrdinaryRuntimeQueue
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{
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public:
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TaskRuntimeDataPtr pop()
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{
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auto result = std::move(queue.front());
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queue.pop_front();
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return result;
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}
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void push(TaskRuntimeDataPtr item) { queue.push_back(std::move(item));}
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void remove(StorageID id)
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{
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auto it = std::remove_if(queue.begin(), queue.end(),
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[&] (auto item) -> bool { return item->task->getStorageID() == id; });
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queue.erase(it, queue.end());
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}
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void setCapacity(size_t count) { queue.set_capacity(count); }
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bool empty() { return queue.empty(); }
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private:
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boost::circular_buffer<TaskRuntimeDataPtr> queue{0};
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};
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/// Uses a heap to pop a task with minimal priority
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class MergeMutateRuntimeQueue
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{
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public:
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TaskRuntimeDataPtr pop()
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{
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std::pop_heap(buffer.begin(), buffer.end(), TaskRuntimeData::comparePtrByPriority);
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auto result = std::move(buffer.back());
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buffer.pop_back();
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return result;
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}
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void push(TaskRuntimeDataPtr item)
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{
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item->priority = item->task->getPriority();
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buffer.push_back(std::move(item));
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std::push_heap(buffer.begin(), buffer.end(), TaskRuntimeData::comparePtrByPriority);
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}
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void remove(StorageID id)
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{
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auto it = std::remove_if(buffer.begin(), buffer.end(),
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[&] (auto item) -> bool { return item->task->getStorageID() == id; });
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buffer.erase(it, buffer.end());
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std::make_heap(buffer.begin(), buffer.end(), TaskRuntimeData::comparePtrByPriority);
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}
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void setCapacity(size_t count) { buffer.reserve(count); }
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bool empty() { return buffer.empty(); }
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private:
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std::vector<TaskRuntimeDataPtr> buffer{};
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};
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/**
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* Executor for a background MergeTree related operations such as merges, mutations, fetches an so on.
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* It can execute only successors of ExecutableTask interface.
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* Which is a self-written coroutine. It suspends, when returns true from executeStep() method.
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*
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* There are two queues of a tasks: pending (main queue for all the tasks) and active (currently executing).
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* Pending queue is needed since the number of tasks will be more than thread to execute.
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* Pending tasks are tasks that successfully scheduled to an executor or tasks that have some extra steps to execute.
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* There is an invariant, that task may occur only in one of these queue. It can occur in both queues only in critical sections.
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*
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* Pending: Active:
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*
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* |s| |s| |s| |s| |s| |s| |s| |s| |s| |s| |s|
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* |s| |s| |s| |s| |s| |s| |s| |s| |s| |s|
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* |s| |s| |s| |s| |s| |s| |s|
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* |s| |s| |s| |s|
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* |s| |s|
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* |s|
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*
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* Each task is simply a sequence of steps. Heavier tasks have longer sequences.
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* When a step of a task is executed, we move tasks to pending queue. And take another from the queue's head.
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* With these architecture all small merges / mutations will be executed faster, than bigger ones.
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*
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* We use boost::circular_buffer as a container for queues not to do any allocations.
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*
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* Another nuisance that we faces with is than background operations always interact with an associated Storage.
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* So, when a Storage want to shutdown, it must wait until all its background operaions are finished.
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*/
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template <class Queue>
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class MergeTreeBackgroundExecutor final : public shared_ptr_helper<MergeTreeBackgroundExecutor<Queue>>
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{
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public:
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MergeTreeBackgroundExecutor(
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String name_,
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size_t threads_count_,
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size_t max_tasks_count_,
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CurrentMetrics::Metric metric_)
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: name(name_)
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, threads_count(threads_count_)
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, max_tasks_count(max_tasks_count_)
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, metric(metric_)
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{
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if (max_tasks_count == 0)
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throw Exception(ErrorCodes::LOGICAL_ERROR, "Task count for MergeTreeBackgroundExecutor must not be zero");
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pending.setCapacity(max_tasks_count);
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active.set_capacity(max_tasks_count);
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pool.setMaxThreads(std::max(1UL, threads_count));
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pool.setMaxFreeThreads(std::max(1UL, threads_count));
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pool.setQueueSize(std::max(1UL, threads_count));
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for (size_t number = 0; number < threads_count; ++number)
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pool.scheduleOrThrowOnError([this] { threadFunction(); });
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}
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~MergeTreeBackgroundExecutor()
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{
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wait();
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}
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bool trySchedule(ExecutableTaskPtr task);
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void removeTasksCorrespondingToStorage(StorageID id);
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void wait();
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private:
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String name;
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size_t threads_count{0};
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size_t max_tasks_count{0};
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CurrentMetrics::Metric metric;
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void routine(TaskRuntimeDataPtr item);
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void threadFunction();
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/// Initially it will be empty
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Queue pending{};
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boost::circular_buffer<TaskRuntimeDataPtr> active{0};
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std::mutex mutex;
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std::condition_variable has_tasks;
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std::atomic_bool shutdown{false};
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ThreadPool pool;
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};
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extern template class MergeTreeBackgroundExecutor<MergeMutateRuntimeQueue>;
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extern template class MergeTreeBackgroundExecutor<OrdinaryRuntimeQueue>;
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using MergeMutateBackgroundExecutor = MergeTreeBackgroundExecutor<MergeMutateRuntimeQueue>;
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using OrdinaryBackgroundExecutor = MergeTreeBackgroundExecutor<OrdinaryRuntimeQueue>;
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}
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