【lesson11】高并发内存池性能优化

文章目录

高并发内存池性能问题
基数树优化性能
- 代码
一层基数树替代map

高并发内存池性能问题

我们知道，我们实现的高并发内存池存在大量的申请锁和，释放锁 ，而这样就会导致我们的性能比不上原来的malloc 。

性能分析：

通过报告，我们发现性能差的很大原因是因为MapObjectToSpan。

而MapObjectToSpan耗费性能的原因是因为锁的问题，频繁的申请锁和释放锁会很耗费性能。

cpp 复制代码

// 获取从对象到span的映射
Span* PageCache::MapObjectToSpan(void* obj)
{
	PAGE_ID id = ((PAGE_ID)obj >> PAGE_SHIFT);

	std::unique_lock<std::mutex> lock(_pageMtx);
	auto ret = _idSpanMap.find(id);
	if (ret != _idSpanMap.end())
	{
		return ret->second;
	}
	else
	{
		assert(false);
		return nullptr;
	}
}

而这是我们就要对其进行优化，我们查看tcmalloc发现，他用一个叫基数树的数据结构 解决了这方面的问题。
基数树也是存储id和span的映射关系。

基数树优化性能

代码

一层基数树

cpp 复制代码

#pragma once
#include"Common.h"
// Single-level array
template <int BITS>
class TCMalloc_PageMap1 {
private:
	static const int LENGTH = 1 << BITS;
	void** array_;

public:
	typedef uintptr_t Number;

	//explicit TCMalloc_PageMap1(void* (*allocator)(size_t)) {
	explicit TCMalloc_PageMap1() {
		//array_ = reinterpret_cast<void**>((*allocator)(sizeof(void*) << BITS));
		size_t size = sizeof(void*) << BITS;
		size_t alignSize = SizeClass::_RoundUp(size, 1<<PAGE_SHIFT);
		array_ = (void**)SystemAlloc(alignSize>>PAGE_SHIFT);
		memset(array_, 0, sizeof(void*) << BITS);
	}

	// Return the current value for KEY.  Returns NULL if not yet set,
	// or if k is out of range.
	void* get(Number k) const {
		if ((k >> BITS) > 0) {
			return NULL;
		}
		return array_[k];
	}

	// REQUIRES "k" is in range "[0,2^BITS-1]".
	// REQUIRES "k" has been ensured before.
	//
	// Sets the value 'v' for key 'k'.
	void set(Number k, void* v) {
		array_[k] = v;
	}
};

一层基数树，是在映射之前直接开辟2^19^个指针大小的空间。

所以每个位置都能存储指针 ，而要存的_pageid直接映射到桶对应的下标处 。

两层基数树

cpp 复制代码

#pragma once
#include"Common.h"
// Two-level radix tree
template <int BITS>
class TCMalloc_PageMap2 {
private:
	// Put 32 entries in the root and (2^BITS)/32 entries in each leaf.
	static const int ROOT_BITS = 5;
	static const int ROOT_LENGTH = 1 << ROOT_BITS;

	static const int LEAF_BITS = BITS - ROOT_BITS;
	static const int LEAF_LENGTH = 1 << LEAF_BITS;

	// Leaf node
	struct Leaf {
		void* values[LEAF_LENGTH];
	};

	Leaf* root_[ROOT_LENGTH];             // Pointers to 32 child nodes
	void* (*allocator_)(size_t);          // Memory allocator

public:
	typedef uintptr_t Number;

	//explicit TCMalloc_PageMap2(void* (*allocator)(size_t)) {
	explicit TCMalloc_PageMap2() {
		//allocator_ = allocator;
		memset(root_, 0, sizeof(root_));

		PreallocateMoreMemory();
	}

	void* get(Number k) const {
		const Number i1 = k >> LEAF_BITS;
		const Number i2 = k & (LEAF_LENGTH - 1);
		if ((k >> BITS) > 0 || root_[i1] == NULL) {
			return NULL;
		}
		return root_[i1]->values[i2];
	}

	void set(Number k, void* v) {
		const Number i1 = k >> LEAF_BITS;
		const Number i2 = k & (LEAF_LENGTH - 1);
		ASSERT(i1 < ROOT_LENGTH);
		root_[i1]->values[i2] = v;
	}

	bool Ensure(Number start, size_t n) {
		for (Number key = start; key <= start + n - 1;) {
			const Number i1 = key >> LEAF_BITS;

			// Check for overflow
			if (i1 >= ROOT_LENGTH)
				return false;

			// Make 2nd level node if necessary
			if (root_[i1] == NULL) {
				//Leaf* leaf = reinterpret_cast<Leaf*>((*allocator_)(sizeof(Leaf)));
				//if (leaf == NULL) return false;
				static ObjectPool<Leaf>	leafPool;
				Leaf* leaf = (Leaf*)leafPool.New();

				memset(leaf, 0, sizeof(*leaf));
				root_[i1] = leaf;
			}

			// Advance key past whatever is covered by this leaf node
			key = ((key >> LEAF_BITS) + 1) << LEAF_BITS;
		}
		return true;
	}

	void PreallocateMoreMemory() {
		// Allocate enough to keep track of all possible pages
		Ensure(0, 1 << BITS);
	}
};

两层基数树和一层基数树，有所不同，
一层基数树是直接无脑开2^19^个指针大小的空间，无论存不存在映射关系或，也不管映射关系的多与少。

而两层基数树则是先开2^5^个指针大小的空间

然后这时如果有映射关系，要插入其中，我们再开辟2^19-5^个指针大小的空间也就是2^14^个。

这样我们就比之前节省了一些空间。

三层基数树

cpp 复制代码

#pragma once
#include"Common.h"
// Three-level radix tree
template <int BITS>
class TCMalloc_PageMap3 {
private:
	// How many bits should we consume at each interior level
	static const int INTERIOR_BITS = (BITS + 2) / 3; // Round-up
	static const int INTERIOR_LENGTH = 1 << INTERIOR_BITS;

	// How many bits should we consume at leaf level
	static const int LEAF_BITS = BITS - 2 * INTERIOR_BITS;
	static const int LEAF_LENGTH = 1 << LEAF_BITS;

	// Interior node
	struct Node {
		Node* ptrs[INTERIOR_LENGTH];
	};

	// Leaf node
	struct Leaf {
		void* values[LEAF_LENGTH];
	};

	Node* root_;                          // Root of radix tree
	void* (*allocator_)(size_t);          // Memory allocator

	Node* NewNode() {
		Node* result = reinterpret_cast<Node*>((*allocator_)(sizeof(Node)));
		if (result != NULL) {
			memset(result, 0, sizeof(*result));
		}
		return result;
	}

public:
	typedef uintptr_t Number;

	explicit TCMalloc_PageMap3(void* (*allocator)(size_t)) {
		allocator_ = allocator;
		root_ = NewNode();
	}

	void* get(Number k) const {
		const Number i1 = k >> (LEAF_BITS + INTERIOR_BITS);
		const Number i2 = (k >> LEAF_BITS) & (INTERIOR_LENGTH - 1);
		const Number i3 = k & (LEAF_LENGTH - 1);
		if ((k >> BITS) > 0 ||
			root_->ptrs[i1] == NULL || root_->ptrs[i1]->ptrs[i2] == NULL) {
			return NULL;
		}
		return reinterpret_cast<Leaf*>(root_->ptrs[i1]->ptrs[i2])->values[i3];
	}

	void set(Number k, void* v) {
		ASSERT(k >> BITS == 0);
		const Number i1 = k >> (LEAF_BITS + INTERIOR_BITS);
		const Number i2 = (k >> LEAF_BITS) & (INTERIOR_LENGTH - 1);
		const Number i3 = k & (LEAF_LENGTH - 1);
		reinterpret_cast<Leaf*>(root_->ptrs[i1]->ptrs[i2])->values[i3] = v;
	}

	bool Ensure(Number start, size_t n) {
		for (Number key = start; key <= start + n - 1;) {
			const Number i1 = key >> (LEAF_BITS + INTERIOR_BITS);
			const Number i2 = (key >> LEAF_BITS) & (INTERIOR_LENGTH - 1);

			// Check for overflow
			if (i1 >= INTERIOR_LENGTH || i2 >= INTERIOR_LENGTH)
				return false;

			// Make 2nd level node if necessary
			if (root_->ptrs[i1] == NULL) {
				Node* n = NewNode();
				if (n == NULL) return false;
				root_->ptrs[i1] = n;
			}

			// Make leaf node if necessary
			if (root_->ptrs[i1]->ptrs[i2] == NULL) {
				Leaf* leaf = reinterpret_cast<Leaf*>((*allocator_)(sizeof(Leaf)));
				if (leaf == NULL) return false;
				memset(leaf, 0, sizeof(*leaf));
				root_->ptrs[i1]->ptrs[i2] = reinterpret_cast<Node*>(leaf);
			}

			// Advance key past whatever is covered by this leaf node
			key = ((key >> LEAF_BITS) + 1) << LEAF_BITS;
		}
		return true;
	}

	void PreallocateMoreMemory() {
	}
};

和两次思路一样。

这里我们只使用一层基数树代替map。其余有兴趣自己实现。

一层基数树替代map

用到存储map映射关系，和查找map映射关系的函数，都只在Page Cache中，所以我们只在Page Cache中修改即可。

PageCache.h

cpp 复制代码

#pragma once

#include "Common.h"
#include "ObjectPool.h"
#include "PageMap.h"

class PageCache
{
public:
	static PageCache* GetInstance()
	{
		return &_sInst;
	}

	// 获取从对象到span的映射
	Span* MapObjectToSpan(void* obj);

	// 释放空闲span回到Pagecache，并合并相邻的span
	void ReleaseSpanToPageCache(Span* span);

	// 获取一个K页的span
	Span* NewSpan(size_t k);

	std::mutex _pageMtx;
private:
	SpanList _spanLists[NPAGES];
	ObjectPool<Span> _spanPool;

	//std::unordered_map<PAGE_ID, Span*> _idSpanMap;
	//std::map<PAGE_ID, Span*> _idSpanMap;
	TCMalloc_PageMap1<32 - PAGE_SHIFT> _idSpanMap;

	PageCache()
	{}
	PageCache(const PageCache&) = delete;


	static PageCache _sInst;
};

PageCache.cpp

cpp 复制代码

#include "PageCache.h"

PageCache PageCache::_sInst;

// 获取一个K页的span
Span* PageCache::NewSpan(size_t k)
{
	assert(k > 0);

	// 大于128 page的直接向堆申请
	if (k > NPAGES-1)
	{
		void* ptr = SystemAlloc(k);
		//Span* span = new Span;
		Span* span = _spanPool.New();

		span->_pageId = (PAGE_ID)ptr >> PAGE_SHIFT;
		span->_n = k;

		//_idSpanMap[span->_pageId] = span;
		_idSpanMap.set(span->_pageId, span);

		return span;
	}

	// 先检查第k个桶里面有没有span
	if (!_spanLists[k].Empty())
	{
		Span* kSpan = _spanLists[k].PopFront();

		// 建立id和span的映射，方便central cache回收小块内存时，查找对应的span
		for (PAGE_ID i = 0; i < kSpan->_n; ++i)
		{
			//_idSpanMap[kSpan->_pageId + i] = kSpan;
			_idSpanMap.set(kSpan->_pageId + i, kSpan);
		}

		return kSpan;
	}

	// 检查一下后面的桶里面有没有span，如果有可以把他它进行切分
	for (size_t i = k+1; i < NPAGES; ++i)
	{
		if (!_spanLists[i].Empty())
		{
			Span* nSpan = _spanLists[i].PopFront();
			//Span* kSpan = new Span;
			Span* kSpan = _spanPool.New();

			// 在nSpan的头部切一个k页下来
			// k页span返回
			// nSpan再挂到对应映射的位置
			kSpan->_pageId = nSpan->_pageId;
			kSpan->_n = k;

			nSpan->_pageId += k;
			nSpan->_n -= k;

			_spanLists[nSpan->_n].PushFront(nSpan);
			// 存储nSpan的首位页号跟nSpan映射，方便page cache回收内存时
			// 进行的合并查找
			//_idSpanMap[nSpan->_pageId] = nSpan;
			//_idSpanMap[nSpan->_pageId + nSpan->_n - 1] = nSpan;
			_idSpanMap.set(nSpan->_pageId, nSpan);
			_idSpanMap.set(nSpan->_pageId + nSpan->_n - 1, nSpan);

			// 建立id和span的映射，方便central cache回收小块内存时，查找对应的span
			for (PAGE_ID i = 0; i < kSpan->_n; ++i)
			{
				//_idSpanMap[kSpan->_pageId + i] = kSpan;
				_idSpanMap.set(kSpan->_pageId + i, kSpan);
			}

			return kSpan;
		}
	}

	// 走到这个位置就说明后面没有大页的span了
	// 这时就去找堆要一个128页的span
	//Span* bigSpan = new Span;
	Span* bigSpan = _spanPool.New();
	void* ptr = SystemAlloc(NPAGES - 1);
	bigSpan->_pageId = (PAGE_ID)ptr >> PAGE_SHIFT;
	bigSpan->_n = NPAGES - 1;

	_spanLists[bigSpan->_n].PushFront(bigSpan);

	return NewSpan(k);
}

Span* PageCache::MapObjectToSpan(void* obj)
{
	PAGE_ID id = ((PAGE_ID)obj >> PAGE_SHIFT);

	/*std::unique_lock<std::mutex> lock(_pageMtx);
	auto ret = _idSpanMap.find(id);
	if (ret != _idSpanMap.end())
	{
		return ret->second;
	}
	else
	{
		assert(false);
		return nullptr;
	}*/
	auto ret = (Span*)_idSpanMap.get(id);
	assert(ret != nullptr);
	return ret;
}

void PageCache::ReleaseSpanToPageCache(Span* span)
{
	// 大于128 page的直接还给堆
	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
	while (1)
	{
		PAGE_ID prevId = span->_pageId - 1;
		//auto ret = _idSpanMap.find(prevId);
		 前面的页号没有，不合并了
		//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，不合并了
		Span* prevSpan = ret;
		if (prevSpan->_isUse == true)
		{
			break;
		}

		// 合并出超过128页的span没办法管理，不合并了
		if (prevSpan->_n + span->_n > NPAGES-1)
		{
			break;
		}

		span->_pageId = prevSpan->_pageId;
		span->_n += prevSpan->_n;

		_spanLists[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 (nextSpan->_n + span->_n > NPAGES-1)
		{
			break;
		}

		span->_n += nextSpan->_n;

		_spanLists[nextSpan->_n].Erase(nextSpan);
		//delete nextSpan;
		_spanPool.Delete(nextSpan);
	}

	_spanLists[span->_n].PushFront(span);
	span->_isUse = false;
	//_idSpanMap[span->_pageId] = span;
	//_idSpanMap[span->_pageId+span->_n-1] = span;

	_idSpanMap.set(span->_pageId, span);
	_idSpanMap.set(span->_pageId + span->_n - 1, span);
}

基数树线程安全的原因

为什么基数树是线程安全的不用加锁？

Realese下再次对比性能：