内存回收
- 1.ThreadCache
- 2.CentralCache
- 3.PageCache
项目源代码:高并发内存池
1.ThreadCache
void ThreadCache::Deallocate(void* ptr, size_t size)
{assert(ptr);assert(size <= MAX_BYTES);//计算在哪号桶中,然后插入进去size_t index = SizeClass::Index(size);_freeLists[index].Push(ptr);//当链表长度大于一次批量申请的内存时就开始还一段list给central cacheif (_freeLists[index].Size() >= _freeLists[index].MaxSize()){ListTooLong(_freeLists[index], size);}
}void ThreadCache::ListTooLong(FreeList& list, size_t size)
{void* start = nullptr;void* end = nullptr;list.PopRang(start, end, list.MaxSize());CentralCache::GetInstance()->ReleaseListToSpans(start, size);
}
当闲置的内存超过一个批量单位大小的时候就开始回收,首先要计算出要回收到哪个桶的的内存,然后逐级往上回收。
2.CentralCache
void CentralCache::ReleaseListToSpans(void* start, size_t size)
{size_t index = SizeClass::Index(size);_spanLists[index]._mtx.lock();while (start){void* next = Nextobj(start);Span* span = PageCache::GetInstance()->MapObjectToSpan(start);Nextobj(start) = span->_freeList;span->_freeList = start;span->_usecount--;if (span->_usecount == 0)//说明span切分出去的内存小块都回收回来了,//这时这个span就可以再回收给page cache,page cache可以再尝试去做前后页的合并{_spanLists[index].Erase(span);span->_freeList = nullptr;span->_prev = nullptr;span->_next = nullptr;//释放span给page cache时,使用page cache的锁就可以了//所以需要先把桶锁解掉再加page cache的大锁_spanLists[index]._mtx.unlock();PageCache::GetInstance()->_pageMtx.lock();PageCache::GetInstance()->ReleaseSpanToPageCache(span);PageCache::GetInstance()->_pageMtx.unlock();_spanLists[index]._mtx.lock();}start = next;}_spanLists[index]._mtx.unlock();}
CentralCache回收回来还需要做前后页的合并,合成一个大的内存块,然后继续交给PageCache处理
3.PageCache
void PageCache::ReleaseSpanToPageCache(Span* span)
{//大于128页的span,直接还给堆if (span->_n > NPAGES -1){void* ptr = (void*)(span->_pageId << PAGE_SHIFT);SystemFree(ptr);//delete span;_spanPool.Delete(span);return;}//对span前后的页,尝试进行合并,缓解内存碎片问题(外碎片)//对前后的页进行合并while (1){PAGE_ID prevId = span->_pageId - 1;//auto ret = _idSpanMap.find(prevId);前面的页号没有找到,不进行合并//if (ret == _idSpanMap.end())//{// break;//}auto ret = (Span*)_idSpanMap.get(prevId);if (ret == nullptr){break;}//前面相邻页的span在使用,不进行合并Span* prevSpan = ret;if (prevSpan->_isUse == true){break;}//合并出超过128的span没办法管理,就不能继续合并if (prevSpan->_n + span->_n > NPAGES - 1){break;}//合并span->_pageId = prevSpan->_pageId;span->_n += prevSpan->_n;_spanList[prevSpan->_n].Erase(prevSpan);//delete prevSpan;_spanPool.Delete(prevSpan);}//向后合并while (1){PAGE_ID nextId = span->_pageId + span->_n;/*auto ret = _idSpanMap.find(nextId);if (ret == _idSpanMap.end()){break;}*/auto ret = (Span*)_idSpanMap.get(nextId);if (ret == nullptr){break;}Span* nextSpan = ret;if (nextSpan->_isUse == true){break;}if (span->_n + nextSpan->_n > NPAGES - 1){break;}span->_n += nextSpan->_n;_spanList[nextSpan->_n].Erase(nextSpan);//delete nextSpan;_spanPool.Delete(nextSpan);}_spanList[span->_n].PushFront(span);span->_isUse = false;//_idSpanMap[span->_pageId] = span;_idSpanMap.set(span->_pageId, span);//_idSpanMap[span->_pageId + span->_n - 1] = span;_idSpanMap.set(span->_pageId + span->_n - 1, span);
}
PageCache需要将一页一一页的小块内存何合并成一张大页的内存,来解决内存碎片问题,因为大的可以切成小的,而当申请的内存大于小块的内存碎片时,就会向堆中申请,造成内存浪费。
点赞支持~