【chunkserver & ut】split read-write thread and add localut.sh #75
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ilixiaocui
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coverage/test.py
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| @@ -0,0 +1,20 @@ | |||
| #!/usr/bin/env python | |||
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| * @param[in] args: param to excute task | ||
| */ | ||
| template<class F, class... Args> | ||
| bool Push(uint64_t key, CHUNK_OP_TYPE optype, F&& f, Args&&... args) { |
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| namespace chunkserver { | ||
| namespace concurrent { | ||
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| enum ThreadPoolType { |
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| void InitThreadPool(ThreadPoolType type, int concorrent, int depth); | ||
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| inline int Hash(uint64_t key, int concurrent) { |
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| * @param[in] rconcurrentsizee: num of read threads | ||
| * @param[in] wqueuedephth: depth of read queue in every thread | ||
| */ | ||
| bool Init(int wconcurrentsize, int wqueuedepth, |
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| wapplyMap_[i]->th = std::move( | ||
| std::thread(&ConcurrentApplyModule::Run, this, type, i)); | ||
| break; | ||
| } |
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| } | ||
| } | ||
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| void ConcurrentApplyModule::Stop() { |
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这里的Stop没有等待TaskQueue中的任务全部执行完成，就直接退出了。
可以不用处理这种场景吗？
或者退出的时候，不会出现队列中还有任务的情况？
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这里stop的时候不需要等任务完成，如果有需求在stop之前需要调用flush。
xu-chaojie
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Sep 17, 2020
| WRITE | ||
| }; | ||
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| class CURVE_CACHELINE_ALIGNMENT ConcurrentApplyModule { |
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读和写的逻辑几乎是完全一样的，这里的代码也是读写各复制了一份，为什么不复用同一个ConcurrentApplyModule，然后读和写是这个类的两个对象，而不是在一个类中实现读和写。读pool和写pool仅仅是线程数不一样而已啊。
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那外面的对象数会增加，要维护的代码会散落在各处
| void ConcurrentApplyModule::Flush() { | ||
| std::atomic<bool>* signal = new (std::nothrow) std::atomic<bool>[wconcurrentsize_]; //NOLINT | ||
| std::mutex* mtx = new (std::nothrow) std::mutex[wconcurrentsize_]; | ||
| std::condition_variable* cv= new (std::nothrow) std::condition_variable[wconcurrentsize_]; //NOLINT |
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这个地方可以改成CountDown优化下，而且在同一个函数中delete了就不需要new，直接临时对象就可以了吧
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