简介
在java已经实现了通过jvm对内存空间的管理后，netty为什么还需要进行内存分配管理?因为jvm管理的内存对象大多数堆内内存，而对于堆外内存，jvm也就是通过保留堆外内存的直接引用对象来进行管理，而对堆外内存并没有直接进行管理，所以为了及时释放堆外内存，避免多次重复通过malloc()系统调用申请内存造成的性能损失，所以需要设置内存池来进行内存块复用，这点其实和连接池作用相似。
netty的内存管理机制其实主要是借鉴jemalloc的内存管理方案；
内存管理思路
内存管理其实和物流管理也是差不了太多的，内存块有大有小，物流商品也有大有小，内存块需要就近取用，避免线程竞争，物流也会为顾客减少取件时间而设置驿站，所以内存管理需要考虑对申请内存和释放内存进行如下考虑：
申请内存：
- 对于小型内存块，申请次数较多的，需要避免线程竞争，设置线程私用内存块tcache；
- 对于tcache内存块如果已经无法满足需求了，则需求建立一个公共区域，允许多个线程共享，则就有了arena；
而arena内存块也需要对内存块大小进行分类管理分别为small allocation和large allocation:- small allocation: 申请次数较多的，而且大小不一，需要划分不同档位，那么面对不同申请需要，避免内存空间浪费；
- large allocation: 申请次数较少，则尽量一次分配完成，避免重复申请；
- 对于超大性内存块，则是直接从内存空间分配，分配直接交付使用；
释放内存：
- 尽量复用最近使用的内存块，从最低地址分配内存，则长时间未使用的内存将跑到高地址，可以进行清理
- 将使用时间跨度较大的内存块清理掉
PooledByteBufAllocator内存分配实现
属性如下：
private static final int DEFAULT_NUM_HEAP_ARENA;//heap arena默认数量
private static final int DEFAULT_NUM_DIRECT_ARENA;//direct arena默认数量
private static final int DEFAULT_PAGE_SIZE;//页默认大小为8192b,8KiB
//default_max_order用来管理chunk的大小，因为chunk是以平衡二叉树的形式管理所有的page，树的深度决定chunk的大小
//defualt_max_order默认为11，则chunk的大小约为pageSize*2^11
private static final int DEFAULT_MAX_ORDER; // 8192 << 11 = 16 MiB per chunk
private static final int DEFAULT_TINY_CACHE_SIZE;//默认tiny caches数量->512
private static final int DEFAULT_SMALL_CACHE_SIZE;//默认small caches数量->256
private static final int DEFAULT_NORMAL_CACHE_SIZE;//默认normal caches数量->64
private static final int DEFAULT_MAX_CACHED_BUFFER_CAPACITY;//默认最大缓存容量
private static final int DEFAULT_CACHE_TRIM_INTERVAL;//默认缓存移除间隔，默认是8192次分配后，将释放掉不常用内存
private static final boolean DEFAULT_USE_CACHE_FOR_ALL_THREADS;//是否默认为所有线程共享内存块,默认为true
private static final int DEFAULT_DIRECT_MEMORY_CACHE_ALIGNMENT;//默认直接内存分配
private static final int MIN_PAGE_SIZE = 4096;//最小页大小
private static final int MAX_CHUNK_SIZE = (int) (((long) Integer.MAX_VALUE + 1) / 2);//chunk最大不得超过2^30也就是1G
其具体初始化如下:
static {
//默认pageSize为8192
int defaultPageSize = SystemPropertyUtil.getInt("io.netty.allocator.pageSize", 8192);
Throwable pageSizeFallbackCause = null;
try {//计算defaultPageSize是否大于min_page_size=4096且为2的整数次幂
validateAndCalculatePageShifts(defaultPageSize);
} catch (Throwable t) {
pageSizeFallbackCause = t;
defaultPageSize = 8192;
}
DEFAULT_PAGE_SIZE = defaultPageSize;
//计算chunk大小
int defaultMaxOrder = SystemPropertyUtil.getInt("io.netty.allocator.maxOrder", 11);
Throwable maxOrderFallbackCause = null;
try {
validateAndCalculateChunkSize(DEFAULT_PAGE_SIZE, defaultMaxOrder);
} catch (Throwable t) {
maxOrderFallbackCause = t;
defaultMaxOrder = 11;
}
DEFAULT_MAX_ORDER = defaultMaxOrder;
// Determine reasonable default for nHeapArena and nDirectArena.决定Arena合理的默认值，
// 需要保证每个arena有三个chunk，则整个arena不能超过最大内存的50%
// Assuming each arena has 3 chunks, the pool should not consume more than 50% of max memory.
final Runtime runtime = Runtime.getRuntime();
/*
* We use 2 * available processors by default to reduce contention as we use 2 * available processors for the
* number of EventLoops in NIO and EPOLL as well. If we choose a smaller number we will run into hot spots as
* allocation and de-allocation needs to be synchronized on the PoolArena.
*
* See https://github.com/netty/netty/issues/3888.
*/
final int defaultMinNumArena = NettyRuntime.availableProcessors() * 2;
final int defaultChunkSize = DEFAULT_PAGE_SIZE << DEFAULT_MAX_ORDER;
// 计算PoolAreana的个数 PoolArena默认为:cpu核心线程数与最大堆内存/2/(3*chunkSize)这两个数中的较小者
// 这里的除以2是为了确保系统分配的所有PoolArena占用的内存不超过系统可用内存的一半，这里的除以3是为了保证每个PoolArena至少可以由3个PoolChunk组成
// 用户可以通过io.netty.allocator.numHeapArenas／numDirectArenas来进行修改
DEFAULT_NUM_HEAP_ARENA = Math.max(0,
SystemPropertyUtil.getInt(
"io.netty.allocator.numHeapArenas",
(int) Math.min(
defaultMinNumArena,
runtime.maxMemory() / defaultChunkSize / 2 / 3)));
DEFAULT_NUM_DIRECT_ARENA = Math.max(0,
SystemPropertyUtil.getInt(
"io.netty.allocator.numDirectArenas",
(int) Math.min(
defaultMinNumArena,
PlatformDependent.maxDirectMemory() / defaultChunkSize / 2 / 3)));
// cache sizes
DEFAULT_TINY_CACHE_SIZE = SystemPropertyUtil.getInt("io.netty.allocator.tinyCacheSize", 512);
DEFAULT_SMALL_CACHE_SIZE = SystemPropertyUtil.getInt("io.netty.allocator.smallCacheSize", 256);
DEFAULT_NORMAL_CACHE_SIZE = SystemPropertyUtil.getInt("io.netty.allocator.normalCacheSize", 64);
// 32 kb is the default maximum capacity of the cached buffer. Similar to what is explained in
// 'Scalable memory allocation using jemalloc'
DEFAULT_MAX_CACHED_BUFFER_CAPACITY = SystemPropertyUtil.getInt(
"io.netty.allocator.maxCachedBufferCapacity", 32 * 1024);
// the number of threshold of allocations when cached entries will be freed up if not frequently used
DEFAULT_CACHE_TRIM_INTERVAL = SystemPropertyUtil.getInt(
"io.netty.allocator.cacheTrimInterval", 8192);
DEFAULT_USE_CACHE_FOR_ALL_THREADS = SystemPropertyUtil.getBoolean(
"io.netty.allocator.useCacheForAllThreads", true);
DEFAULT_DIRECT_MEMORY_CACHE_ALIGNMENT = SystemPropertyUtil.getInt(
"io.netty.allocator.directMemoryCacheAlignment", 0);
}
PooledByteBufAllocator构造初始化如下:
public PooledByteBufAllocator(boolean preferDirect, int nHeapArena, int nDirectArena, int pageSize, int maxOrder,
int tinyCacheSize, int smallCacheSize, int normalCacheSize,
boolean useCacheForAllThreads, int directMemoryCacheAlignment) {
super(preferDirect);
threadCache = new PoolThreadLocalCache(useCacheForAllThreads);
this.tinyCacheSize = tinyCacheSize;
this.smallCacheSize = smallCacheSize;
this.normalCacheSize = normalCacheSize;
chunkSize = validateAndCalculateChunkSize(pageSize, maxOrder);
...........................节省空间---------------
int pageShifts = validateAndCalculatePageShifts(pageSize);
if (nHeapArena > 0) {
heapArenas = newArenaArray(nHeapArena);
List metrics = new ArrayList(heapArenas.length);
for (int i = 0; i < heapArenas.length; i ++) {
PoolArena.HeapArena arena = new PoolArena.HeapArena(this,
pageSize, maxOrder, pageShifts, chunkSize,
directMemoryCacheAlignment);
heapArenas[i] = arena;
metrics.add(arena);
}
heapArenaMetrics = Collections.unmodifiableList(metrics);
} else {
heapArenas = null;
heapArenaMetrics = Collections.emptyList();
}
//堆外内存初始化
if (nDirectArena > 0) {
directArenas = newArenaArray(nDirectArena);//创建Arena数组
List metrics = new ArrayList(directArenas.length);
for (int i = 0; i < directArenas.length; i ++) {//初始化Arena
PoolArena.DirectArena arena = new PoolArena.DirectArena(
this, pageSize, maxOrder, pageShifts, chunkSize, directMemoryCacheAlignment);
directArenas[i] = arena;
metrics.add(arena);
}
directArenaMetrics = Collections.unmodifiableList(metrics);
} else {
directArenas = null;
directArenaMetrics = Collections.emptyList();
}
metric = new PooledByteBufAllocatorMetric(this);
}
PoolArena源码解析
基本域属性，如下图:
//将Subpage划分为3类
enum SizeClass {
Tiny,
Small,
Normal
}
//设置tiny subpagePools数量
static final int numTinySubpagePools = 512 >>> 4;
final PooledByteBufAllocator parent;
//arena管理subpage平衡二叉树深度
private final int maxOrder;
//页大小
final int pageSize;
//页偏移量
final int pageShifts;
//chunk大小
final int chunkSize;
final int subpageOverflowMask;
//smallSubpagePools数量即大小在512到8192区间的内存块，划分为[512,1024],[1024,2048],[2048,4096],[4096,8192]
final int numSmallSubpagePools;
final int directMemoryCacheAlignment;
final int directMemoryCacheAlignmentMask;
private final PoolSubpage[] tinySubpagePools;
private final PoolSubpage[] smallSubpagePools;
//存储内存使用率在50%-100%的chunk
private final PoolChunkList q050;
//存储内存使用率在25%-75%的chunk
private final PoolChunkList q025;
//存储内存使用率在0-50%的chunk
private final PoolChunkList q000;
//存储内存使用率在0-25%的chunk
private final PoolChunkList qInit;
//存储内存使用率在75-100%左右的chunk
private final PoolChunkList q075;
//存储内存使用率为100%左右的chunk
private final PoolChunkList q100;
private final List chunkListMetrics;
// Metrics for allocations and deallocations
private long allocationsNormal;
// We need to use the LongCounter here as this is not guarded via synchronized block.
private final LongCounter allocationsTiny = PlatformDependent.newLongCounter();
private final LongCounter allocationsSmall = PlatformDependent.newLongCounter();
private final LongCounter allocationsHuge = PlatformDependent.newLongCounter();
private final LongCounter activeBytesHuge = PlatformDependent.newLongCounter();
private long deallocationsTiny;
private long deallocationsSmall;
private long deallocationsNormal;
// We need to use the LongCounter here as this is not guarded via synchronized block.
private final LongCounter deallocationsHuge = PlatformDependent.newLongCounter();
// Number of thread caches backed by this arena.
final AtomicInteger numThreadCaches = new AtomicInteger();
其构造函数如下：
protected PoolArena(PooledByteBufAllocator parent, int pageSize,
int maxOrder, int pageShifts, int chunkSize, int cacheAlignment) {
this.parent = parent;
this.pageSize = pageSize;
this.maxOrder = maxOrder;
this.pageShifts = pageShifts;
this.chunkSize = chunkSize;
directMemoryCacheAlignment = cacheAlignment;
directMemoryCacheAlignmentMask = cacheAlignment - 1;
subpageOverflowMask = ~(pageSize - 1);
tinySubpagePools = newSubpagePoolArray(numTinySubpagePools);
for (int i = 0; i < tinySubpagePools.length; i ++) {
tinySubpagePools[i] = newSubpagePoolHead(pageSize);
}
numSmallSubpagePools = pageShifts - 9;
smallSubpagePools = newSubpagePoolArray(numSmallSubpagePools);
for (int i = 0; i < smallSubpagePools.length; i ++) {
smallSubpagePools[i] = newSubpagePoolHead(pageSize);
}
q100 = new PoolChunkList(this, null, 100, Integer.MAX_VALUE, chunkSize);
q075 = new PoolChunkList(this, q100, 75, 100, chunkSize);
q050 = new PoolChunkList(this, q075, 50, 100, chunkSize);
q025 = new PoolChunkList(this, q050, 25, 75, chunkSize);
q000 = new PoolChunkList(this, q025, 1, 50, chunkSize);
qInit = new PoolChunkList(this, q000, Integer.MIN_VALUE, 25, chunkSize);
q100.prevList(q075);
q075.prevList(q050);
q050.prevList(q025);
q025.prevList(q000);
q000.prevList(null);
qInit.prevList(qInit);
List metrics = new ArrayList(6);
metrics.add(qInit);
metrics.add(q000);
metrics.add(q025);
metrics.add(q050);
metrics.add(q075);
metrics.add(q100);
chunkListMetrics = Collections.unmodifiableList(metrics);
}
从上可以看出PoolChunkList它们之间的关系如下图:
poolchunklist.png
内存分配过程如下：
private void allocate(PoolThreadCache cache, PooledByteBuf buf, final int reqCapacity) {
final int normCapacity = normalizeCapacity(reqCapacity);//将请求的内存大小规格化
if (isTinyOrSmall(normCapacity)) { // capacity < pageSize请求内存在PageSize以下
int tableIdx;
PoolSubpage[] table;
boolean tiny = isTiny(normCapacity);//如果是申请规格是tiny，小于512
if (tiny) { // < 512
if (cache.allocateTiny(this, buf, reqCapacity, normCapacity)) {//线程私有内存块是否能满足需求
// was able to allocate out of the cache so move on
return;
}
tableIdx = tinyIdx(normCapacity);//获取可分配内存索引
table = tinySubpagePools;
} else {
if (cache.allocateSmall(this, buf, reqCapacity, normCapacity)) {//如果是small，判断线程私有内存块是否满足
// was able to allocate out of the cache so move on
return;
}
tableIdx = smallIdx(normCapacity);
table = smallSubpagePools;
}
final PoolSubpage 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) {//同步，避免内存分配冲突
final PoolSubpage 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) {//针对large 内存块申请
if (cache.allocateNormal(this, buf, reqCapacity, normCapacity)) {//查询线程私有内否满足
// was able to allocate out of the cache so move on
return;
}
synchronized (this) {//同步
allocateNormal(buf, reqCapacity, normCapacity);
++allocationsNormal;
}
} else {//巨大内存块申请，jvm内存池不会缓存该内存块
// Huge allocations are never served via the cache so just call allocateHuge
allocateHuge(buf, reqCapacity);
}
}
内存规格化源码分析:
int normalizeCapacity(int reqCapacity) {
if (reqCapacity < 0) {
throw new IllegalArgumentException("capacity: " + reqCapacity + " (expected: 0+)");
}
if (reqCapacity >= chunkSize) {
return directMemoryCacheAlignment == 0 ? reqCapacity : alignCapacity(reqCapacity);
}
if (!isTiny(reqCapacity)) { // >= 512
// Doubled
//这里通过右移确定其最高档位的大小,如果一个数位数小于16大于8位，如下
//1xxxxxxxxx右移一位进行或运算则为11xxxxxxxx;
//11xxxxxxxx右移两位再或运算则为1111xxxxxx;
//1111xxxxxx右移4位再或运算则为11111111xxxx;
//11111111xxxx右移8位再或运算则为11111111111;
//11111111111在右移16为再或运算还是11111111111；
//再进行+1操作则为100000000000
int normalizedCapacity = reqCapacity;
normalizedCapacity --;
normalizedCapacity |= normalizedCapacity >>> 1;
normalizedCapacity |= normalizedCapacity >>> 2;
normalizedCapacity |= normalizedCapacity >>> 4;
normalizedCapacity |= normalizedCapacity >>> 8;
normalizedCapacity |= normalizedCapacity >>> 16;
normalizedCapacity ++;
if (normalizedCapacity < 0) {
normalizedCapacity >>>= 1;
}
assert directMemoryCacheAlignment == 0 || (normalizedCapacity & directMemoryCacheAlignmentMask) == 0;
return normalizedCapacity;
}
if (directMemoryCacheAlignment > 0) {
return alignCapacity(reqCapacity);
}
// Quantum-spaced
if ((reqCapacity & 15) == 0) {
return reqCapacity;
}
return (reqCapacity & ~15) + 16;
}