Netty源码分析(八)—内存池分析

来源:互联网 发布:c语言程序实例代码 编辑:程序博客网 时间:2024/06/01 21:23

# Netty源码分析(八)—内存池分析

Netty内存池是将内存的分配管理起来减少内存碎片和避免内存浪费,Netty内存池参考了Slab分配和Buddy分配思想;Slab分配是将内存分割成大小不等的内存块,在用户线程请求时根据请求的内存大小分配最为贴近size的内存快,减少了内存碎片同时避免了内存浪费;Buddy分配是把一块内存块等量分割,回收时候进行合并,尽可能保证系统中有足够大的连续内存;

个人主页:tuzhenyu’s page
原文地址:Netty源码分析(八)—内存池分析

(0) 内存数据结构

  • 内存分级从上到下主要分为:Arena,ChunkList,Chunk,Page,SubPage五级;

这里写图片描述

  • PooledArena是一块连续的内存块,为了优化并发性能在Netty内存池中存在一个由多个Arena组成的数组,在多个线程进行内存分配时会按照轮询策略选择一个Arena进行内存分配;

    • 一个PoolArena内存块是由两个SubPagePools(用来存储零碎内存)和多个ChunkList组成,两个SubpagePools数组分别为tinySubpagePools和smallSubpagePools。每个ChunkList里包含多个Chunk按照双向链表排列,每个Chunk里包含多个Page(默认2048个),每个Page(默认大小为8k字节)由多个Subpage组成。

    • 每个ChunkList里包含的Chunk数量会动态变化,比如当该chunk的内存利用率变化时会向其它ChunkList里移动。

final PooledByteBufAllocator parent;private final int maxOrder;final int pageSize;final int pageShifts;final int chunkSize;final int subpageOverflowMask;final int numSmallSubpagePools;final int directMemoryCacheAlignment;final int directMemoryCacheAlignmentMask;private final PoolSubpage<T>[] tinySubpagePools;private final PoolSubpage<T>[] smallSubpagePools;private final PoolChunkList<T> q050;private final PoolChunkList<T> q025;private final PoolChunkList<T> q000;private final PoolChunkList<T> qInit;private final PoolChunkList<T> q075;private final PoolChunkList<T> q100;
  • 内存池内存分配规则

    • 对于小于PageSize大小的内存分配,会在tinySubPagePools和smallSubPagePools中分配,tinySubPagePools用来分配小于512字节的内存,smallSubPagePools用来分配大于512字节小于PageSize的内存;

    • 对于大于PageSize小于ChunkSize的内存分配,会在PoolChunkList中的Chunk中分配

    • 对于大于ChunkSize的内存分配,会之间直接创建非池化的Chunk来分配,并且该Chunk不会放在内存池中重用。

(1) 内存池的入口PoolByteBufAllocator

  • 内存池进行内存分配是通过PooledByteBufAllocator类的buffer()方法实现的
public static void main(String[] args) {    ByteBuf buf = PooledByteBufAllocator.DEFAULT.buffer(1024);    //默认直接内存    buf.writeBytes("hello".getBytes());    PooledByteBufAllocator p = new PooledByteBufAllocator(false);    //堆内存(false)或者直接内存    ByteBuf buf1 = p.buffer(1024);    buf1.writeBytes("world".getBytes());}
  • 判断创建的缓冲区的类型,直接缓冲区或者堆缓冲区,如果在创建PooledByteBufAllocator实例时参数是false则为堆缓冲区
public ByteBuf buffer(int initialCapacity) {    if (directByDefault) {        return directBuffer(initialCapacity);    }    return heapBuffer(initialCapacity);}
  • 通过newHeapBuffer()方法创建堆缓冲区
public ByteBuf heapBuffer(int initialCapacity) {    return heapBuffer(initialCapacity, DEFAULT_MAX_CAPACITY);}@Overridepublic ByteBuf heapBuffer(int initialCapacity, int maxCapacity) {    if (initialCapacity == 0 && maxCapacity == 0) {        return emptyBuf;    }    validate(initialCapacity, maxCapacity);    return newHeapBuffer(initialCapacity, maxCapacity);}
  • newHeapBuffer()方法首先从PoolThreadLocalCache中获取与线程绑定的缓存池PoolThreadCache,缓存池中保存着回收的内存;

    • PoolThreadLocalCache继承了FastThreadLocal保存线程与内存缓冲池(PoolThreadCache)的映射,在进行内存分配时先映射中取出缓存内存块Arena,再将内存分配委托给内存块Arena的allocate()方法;
protected ByteBuf newHeapBuffer(int initialCapacity, int maxCapacity) {    PoolThreadCache cache = threadCache.get();    PoolArena<byte[]> heapArena = cache.heapArena;    final ByteBuf buf;    if (heapArena != null) {        buf = heapArena.allocate(cache, initialCapacity, maxCapacity);    } else {        buf = PlatformDependent.hasUnsafe() ?                new UnpooledUnsafeHeapByteBuf(this, initialCapacity, maxCapacity) :                new UnpooledHeapByteBuf(this, initialCapacity, maxCapacity);    }    return toLeakAwareBuffer(buf);}
  • 如果不存在与线程对应的缓存则轮询分配一个Arean数组中的Arena内存块创建一个新的PoolThreadCache作为内存缓存
protected synchronized PoolThreadCache initialValue() {    final PoolArena<byte[]> heapArena = leastUsedArena(heapArenas);    final PoolArena<ByteBuffer> directArena = leastUsedArena(directArenas);    if (useCacheForAllThreads || Thread.currentThread() instanceof FastThreadLocalThread) {        return new PoolThreadCache(                heapArena, directArena, tinyCacheSize, smallCacheSize, normalCacheSize,                DEFAULT_MAX_CACHED_BUFFER_CAPACITY, DEFAULT_CACHE_TRIM_INTERVAL);    }    // No caching for non FastThreadLocalThreads.    return new PoolThreadCache(heapArena, directArena, 0, 0, 0, 0, 0);}

(2) 内存块PoolArena

  • 在应用层通过设置PooledByteBufAllocator来执行ByteBuf的分配,但是最终的内存分配工作被委托给PoolArena;由于Netty常用于高并发系统,所以各个线程进行内存分配时竞争不可避免,这可能会极大的影响内存分配的效率,为了缓解高并发时的线程竞争,Netty允许使用者创建多个分配器(Arena)来分离锁,提高内存分配效率,当然是以内存来作为代价的。

  • PoolByteBufAllocator将内存分配的任务委托给Arena进行,主要包括两步:一步是从Recycler对象池中获取复用的Buf对象,另外一步是为Buf对象分配内存;

PooledByteBuf<T> allocate(PoolThreadCache cache, int reqCapacity, int maxCapacity) {    PooledByteBuf<T> buf = newByteBuf(maxCapacity);    //获取复用对象    allocate(cache, buf, reqCapacity);    //分配内存    return buf;}
  • 调用allocate()方法从Arena内存块中分配内存

    • 判断需要分配的内存大小是否大于PageSize,如果小于PageSize则分配tiny内存或者small内存

      • 如果需要分配的内存小于PageSize,判断是否小于512,如果小于则调用allocateTiny()方法进行tiny内存分配,否则调用allocateSmall()方法进行small内存分配;
    • 如果需要分配的内存大于PageSize,再判断是否大于ChunkSize,如果小于ChunkSize则调用allocateNormal()方法进行normal内存分配;

    • 如果需要分配的内存大于ChunkSize,内存池无法分配需要JVM分配则调用allocateHuge()方法在池外进行分配;

private void allocate(PoolThreadCache cache, PooledByteBuf<T> buf, final int reqCapacity) {    final int normCapacity = normalizeCapacity(reqCapacity);    if (isTinyOrSmall(normCapacity)) { // capacity < pageSize        int tableIdx;        PoolSubpage<T>[] table;        boolean tiny = isTiny(normCapacity);        if (tiny) { // < 512            if (cache.allocateTiny(this, buf, reqCapacity, normCapacity)) {                // was able to allocate out of the cache so move on                return;            }            tableIdx = tinyIdx(normCapacity);            table = tinySubpagePools;        } else {            if (cache.allocateSmall(this, buf, reqCapacity, normCapacity)) {                // was able to allocate out of the cache so move on                return;            }            tableIdx = smallIdx(normCapacity);            table = smallSubpagePools;        }        final PoolSubpage<T> head = table[tableIdx];        /**         * Synchronize on the head. This is needed as {@link PoolChunk#allocateSubpage(int)} and         * {@link PoolChunk#free(long)} may modify the doubly linked list as well.         */        synchronized (head) {            final PoolSubpage<T> s = head.next;            if (s != head) {                assert s.doNotDestroy && s.elemSize == normCapacity;                long handle = s.allocate();                assert handle >= 0;                s.chunk.initBufWithSubpage(buf, handle, reqCapacity);                incTinySmallAllocation(tiny);                return;            }        }        synchronized (this) {            allocateNormal(buf, reqCapacity, normCapacity);        }        incTinySmallAllocation(tiny);        return;    }    if (normCapacity <= chunkSize) {        if (cache.allocateNormal(this, buf, reqCapacity, normCapacity)) {            // was able to allocate out of the cache so move on            return;        }        synchronized (this) {            allocateNormal(buf, reqCapacity, normCapacity);            ++allocationsNormal;        }    } else {        // Huge allocations are never served via the cache so just call allocateHuge        allocateHuge(buf, reqCapacity);    }}
  • 内存池的初始阶段,线程是没有内存缓存的,所以最开始的内存分配都需要在Chunk分配区进行分配;也就是说无论是tinySubpagePools还是smallSubpagePools成员,在内存池初始化时是不会预置内存的,所以最开始的内存分配都会进入PoolArena的allocateNormal方法:

    • 调用allocateNormal()方法从Chunk级别上分配内存,从PoolChunkList中查找可用PoolChunk并进行内存分配,如果没有可用的PoolChunk则创建一个并加入到PoolChunkList中,完成此次内存分配
private void allocateNormal(PooledByteBuf<T> buf, int reqCapacity, int normCapacity) {    if (q050.allocate(buf, reqCapacity, normCapacity) || q025.allocate(buf, reqCapacity, normCapacity) ||        q000.allocate(buf, reqCapacity, normCapacity) || qInit.allocate(buf, reqCapacity, normCapacity) ||        q075.allocate(buf, reqCapacity, normCapacity)) {        return;    }    // Add a new chunk.    PoolChunk<T> c = newChunk(pageSize, maxOrder, pageShifts, chunkSize);    long handle = c.allocate(normCapacity);    assert handle > 0;    c.initBuf(buf, handle, reqCapacity);    qInit.add(c);}
  • 从Arena中创建新的PoolChunk后根据其内存占用率放入相应的ChunkList中;
void add(PoolChunk<T> chunk) {    if (chunk.usage() >= maxUsage) {        nextList.add(chunk);        return;    }    chunk.parent = this;    if (head == null) {        head = chunk;        chunk.prev = null;        chunk.next = null;    } else {        chunk.prev = null;        chunk.next = head;        head.prev = chunk;        head = chunk;    }}

(3) 内存块分配基本单元PoolChunk

  • PoolChunk的几个重要参数

    • memory,物理内存,内存请求者千辛万苦拐弯抹角就是为了得到它,在HeapArena中它就是一个chunkSize大小的byte数组;默认PoolChunk是由11层二叉树构成,也就是大小为ChunkSize=2048*PageSize;

    • memoryMap数组,内存分配控制信息,数组元素是一个32位的整数

    • subpages数组,页分配信息,数组元素的个数等于chunk中page的数量。

  • 从Arena中创建PoolChunk后,通过调用PoolChunk.allocate()方法真正进行内存分配

    • 在Chunk中的内存分配是根据需要分配的内存大小将Page内存页划分为SunPage,并将多余的SubPage加入到SubPagePools缓存中,将被分配的Page和SubPage在控制数组中进行标记;
private long allocateSubpage(int normCapacity) {    PoolSubpage<T> head = arena.findSubpagePoolHead(normCapacity);    synchronized (head) {        int d = maxOrder; // subpages are only be allocated from pages i.e., leaves        int id = allocateNode(d);        if (id < 0) {            return id;        }        final PoolSubpage<T>[] subpages = this.subpages;        final int pageSize = this.pageSize;        freeBytes -= pageSize;        int subpageIdx = subpageIdx(id);        PoolSubpage<T> subpage = subpages[subpageIdx];        if (subpage == null) {            subpage = new PoolSubpage<T>(head, this, id, runOffset(id), pageSize, normCapacity);            subpages[subpageIdx] = subpage;        } else {            subpage.init(head, normCapacity);        }        return subpage.allocate();    }}

总结

  • 内存池主要是将内存分配管理起来不经过JVM的内存分配,有效减小内存碎片避免内存浪费,同时也能减少频繁GC带来的性能影响;

  • 内存池内存分配入口是PoolByteBufAllocator类,该类最终将内存分配委托给PoolArena进行;为了减少高并发下多线程内存分配碰撞带来的性能影响,PoolByteBufAllocator维护着一个PoolArena数组,线程通过轮询获取其中一个进行内存分配,进而实现锁分离;

  • 内存分配的基本单元是PoolChunk,从PoolArena中分配获取一个PoolChunk,一个PoolChunk包含多个Page内存页,通过完全二叉树维护多个内存页用于内存分配;

原创粉丝点击