Netty源码解析之如何理解内存对齐类SizeClasses

发布时间:2021-10-23 16:57:13 作者:iii
来源:亿速云 阅读:128

这篇文章主要介绍“Netty源码解析之如何理解内存对齐类SizeClasses”,在日常操作中,相信很多人在Netty源码解析之如何理解内存对齐类SizeClasses问题上存在疑惑,小编查阅了各式资料,整理出简单好用的操作方法,希望对大家解答”Netty源码解析之如何理解内存对齐类SizeClasses”的疑惑有所帮助!接下来,请跟着小编一起来学习吧!

在学习Netty内存池之前,我们先了解一下Netty的内存对齐类SizeClasses,它为Netty内存池中的内存块提供大小对齐,索引计算等服务方法。
源码分析基于Netty 4.1.52

Netty内存池中每个内存块size都符合如下计算公式
size = 1 << log2Group + nDelta * (1 << log2Delta)
log2Group:内存块分组
nDelta:增量乘数
log2Delta:增量大小的log2值

SizeClasses初始化后,将计算chunkSize(内存池每次向操作系统申请内存块大小)范围内每个size的值,保存到sizeClasses字段中。
sizeClasses是一个表格(二维数组),共有7列,含义如下
index:内存块size的索引
log2Group:内存块分组,用于计算对应的size
log2Delata:增量大小的log2值,用于计算对应的size
nDelta:增量乘数,用于计算对应的size
isMultipageSize:表示size是否为page的倍数
isSubPage:表示是否为一个subPage类型
log2DeltaLookup:如果size存在位图中的,记录其log2Delta,未使用

sizeClasses负责计算sizeClasses表格

private int sizeClasses() {
    int normalMaxSize = -1;

    int index = 0;
    int size = 0;
    // #1
    int log2Group = LOG2_QUANTUM;
    int log2Delta = LOG2_QUANTUM;
    int ndeltaLimit = 1 << LOG2_SIZE_CLASS_GROUP;

    // #2
    int nDelta = 0;
    while (nDelta < ndeltaLimit) {
        size = sizeClass(index++, log2Group, log2Delta, nDelta++);
    }
    log2Group += LOG2_SIZE_CLASS_GROUP;

    // #3
    while (size < chunkSize) {
        nDelta = 1;

        while (nDelta <= ndeltaLimit && size < chunkSize) {
            size = sizeClass(index++, log2Group, log2Delta, nDelta++);
            normalMaxSize = size;
        }

        log2Group++;
        log2Delta++;
    }

    //chunkSize must be normalMaxSize
    assert chunkSize == normalMaxSize;

    //return number of size index
    return index;
}

LOG2_QUANTUM=4
LOG2_SIZE_CLASS_GROUP=2
#1 log2Group,log2Delta都是从LOG2_QUANTUM开始
ndeltaLimit为2^LOG2_SIZE_CLASS_GROUP,即内存块size以4个为一组进行分组
#2 初始化第0组
nDelta从0开始
sizeClass方法计算sizeClasses每一行内容
注意:第0组后log2Group增加LOG2_SIZE_CLASS_GROUP,而log2Delta不变
#3 初始化后面的size
nDelta从1开始
每组log2Group+1,log2Delta+1

log2Group=log2Delta+LOG2_SIZE_CLASS_GROUP代入计算公式中,得到
size = 1 << (log2Delta+LOG2_SIZE_CLASS_GROUP) + nDelta * (1 << log2Delta)
size = (nDelta + 2 ^ LOG2_SIZE_CLASS_GROUP) * (1 << log2Delta)

可以看到,每个内存块size都是(1 << log2Delta)的倍数
从第二组开始,每组内这个倍数依次是5,6,7,8
每组内相邻行大小增量为(1 << log2Delta),相邻组之间(1 << log2Delta)翻倍。
Netty默认的配置一个page的大小是2^13,即为8KB,默认的一个chunk的大小为16777216,即16MB。sizeClasses表格内存如下:
Netty源码解析之如何理解内存对齐类SizeClasses

Netty内存池中管理了大小不同的内存块,对于这些不同大小的内存块,Netty划分为不同的等级Small,Normal,Huge。Huge是大于chunkSize的内存块,不在表格中,这里也不讨论。

sizeClasses表格可以分为两部分

  1. isSubPage为1的size为Small内存块,其他为Normal内存块。 分配Small内存块,需要找到对应的index 通过size2SizeIdx方法计算index 比如需要分配一个90字节的内存块,需要从sizeClasses表格找到第一个大于90的内存块size,即96,其index为5。

  2. Normal内存块必须是page的倍数。 将isMultipageSize为1的行取出组成另一个表格 Netty源码解析之如何理解内存对齐类SizeClasses

PoolChunk中分配Normal内存块需求查询对应的pageIdx。
比如要分配一个50000字节的内存块,需要从这个新表格找到第一个大于50000的内存块size,即57344,其pageIdx为6。
通过pages2pageIdxCompute方法计算pageIdx。

下面看一下具体的计算方法

public int size2SizeIdx(int size) {
    if (size == 0) {
        return 0;
    }
    // #1
    if (size > chunkSize) {
        return nSizes;
    }
    // #2
    if (directMemoryCacheAlignment > 0) {
        size = alignSize(size);
    }
    // #3
    if (size <= lookupMaxSize) {
        //size-1 / MIN_TINY
        return size2idxTab[size - 1 >> LOG2_QUANTUM];
    }
    // #4
    int x = log2((size << 1) - 1);
    // #5
    int shift = x < LOG2_SIZE_CLASS_GROUP + LOG2_QUANTUM + 1
            ? 0 : x - (LOG2_SIZE_CLASS_GROUP + LOG2_QUANTUM);

    int group = shift << LOG2_SIZE_CLASS_GROUP;
    // #6
    int log2Delta = x < LOG2_SIZE_CLASS_GROUP + LOG2_QUANTUM + 1
            ? LOG2_QUANTUM : x - LOG2_SIZE_CLASS_GROUP - 1;
    // #7
    int deltaInverseMask = -1 << log2Delta;
    int mod = (size - 1 & deltaInverseMask) >> log2Delta &
              (1 << LOG2_SIZE_CLASS_GROUP) - 1;

    return group + mod;
}

#1 大于chunkSize,就是返回nSizes代表申请的是Huge内存块。
#2 不使用sizeClasses表格,直接将申请内存大小转换为directMemoryCacheAlignment的倍数,directMemoryCacheAlignment默认为0。
#3 SizeClasses将一部分较小的size与对应index记录在size2idxTab作为位图,这里直接查询size2idxTab,避免重复计算
size2idxTab中保存了(size-1)/(2^LOG2_QUANTUM) --> idx的对应关系。
从sizeClasses方法可以看到,sizeClasses表格中每个size都是(2^LOG2_QUANTUM) 的倍数。
#4 对申请内存大小进行log2的向上取整,就是每组最后一个内存块size。-1是为了避免申请内存大小刚好等于2的指数次幂时被翻倍。
log2Group = log2Delta + LOG2_SIZE_CLASS_GROUPnDelta=2^LOG2_SIZE_CLASS_GROUP代入计算公式,可得
lastSize = 1 << (log2Group + 1)
x = log2Group + 1
#5 shift, 当前在第几组,从0开始(sizeClasses表格中0~3行为第0组,4~7行为第1组,以此类推,不是log2Group)
x < LOG2_SIZE_CLASS_GROUP + LOG2_QUANTUM + 1,即log2Group < LOG2_SIZE_CLASS_GROUP + LOG2_QUANTUM ,满足该条件的是第0组的size,这时shift固定是0。
从sizeClasses方法可以看到,除了第0组,都满足shift = log2Group - LOG2_QUANTUM - (LOG2_SIZE_CLASS_GROUP - 1)
shift << LOG2_SIZE_CLASS_GROUP就是该组第一个内存块size的索引

#6 计算log2Delta
第0组固定是LOG2_QUANTUM
除了第0组,将nDelta = 2^LOG2_SIZE_CLASS_GROUP代入计算公式
lastSize = ( 2^LOG2_SIZE_CLASS_GROUP + 2^LOG2_SIZE_CLASS_GROUP ) * (1 << log2Delta)
lastSize = (1 << log2Delta) << LOG2_SIZE_CLASS_GROUP << 1

#7 前面已经定位到第几组了,下面要找到申请内存大小应分配在该组第几位
这里要找到比申请内存大的最小size。

申请内存大小可以理解为上一个size加上一个不大于(1 << log2Delta)的值,即
(nDelta - 1 + 2^LOG2_SIZE_CLASS_GROUP) * (1 << log2Delta) + n, 备注:0 < n <= (1 << log2Delta)
注意,nDelta - 1就是mod

& deltaInverseMask,将申请内存大小最后log2Delta个bit位设置为0,可以理解为减去n
>> log2Delta,右移log2Delta个bit位,就是除以(1 << log2Delta),结果就是(nDelta - 1 + 2 ^ LOG2_SIZE_CLASS_GROUP)
& (1 << LOG2_SIZE_CLASS_GROUP) - 1, 取最后的LOG2_SIZE_CLASS_GROUP个bit位的值,结果就是mod

size - 1,是为了申请内存等于内存块size时避免分配到下一个内存块size中,即n == (1 << log2Delta)的场景。

疑问:既然右移log2Delta个bit位,那为什么前面要将log2Delta个bit位设置为0?

第0组由于log2Group等于log2Delta,代入计算公式如下
1 << log2Delta + (nDelta - 1) * (1 << log2Delta) + n, 备注:0 < n <= (1 << log2Delta)
nDelta * (1 << log2Delta) + n
所以第0组nDelta从0开始,mod = nDelta

pages2pageIdxCompute方法计算pageIdx逻辑与size2SizeIdx方法类似,只是将LOG2_QUANTUM变量换成了pageShifts,这里不再重复。

SizeClasses是给PoolArena(内存池),PoolChunk(内存块)提供服务的,建议大家结合后面分析PoolArena,PoolChunk的文章一起理解。
如果大家对SizeClasses具体算法不感兴趣,只有理解SizeClasses类中利用sizeClasses表格,为PoolArena,PoolChunk提供计算index,pageIdx索引的方法,也可以帮助大家理解后面解析PoolArena,PoolChunk的文章。

下面贴出sizeClasses完整表格(可复制到Excle,以|分列)

| index  | log2Group  | log2Delta  | nDelta  | isMultiPageSize  | isSubPage  | log2DeltaLookup  | size      | usize  |
| 0      | 4          | 4          | 0       | 0                | 1          | 4                | 16        |        |
| 1      | 4          | 4          | 1       | 0                | 1          | 4                | 32        |        |
| 2      | 4          | 4          | 2       | 0                | 1          | 4                | 48        |        |
| 3      | 4          | 4          | 3       | 0                | 1          | 4                | 64        |        |
| 4      | 6          | 4          | 1       | 0                | 1          | 4                | 80        |        |
| 5      | 6          | 4          | 2       | 0                | 1          | 4                | 96        |        |
| 6      | 6          | 4          | 3       | 0                | 1          | 4                | 112       |        |
| 7      | 6          | 4          | 4       | 0                | 1          | 4                | 128       |        |
| 8      | 7          | 5          | 1       | 0                | 1          | 5                | 160       |        |
| 9      | 7          | 5          | 2       | 0                | 1          | 5                | 192       |        |
| 10     | 7          | 5          | 3       | 0                | 1          | 5                | 224       |        |
| 11     | 7          | 5          | 4       | 0                | 1          | 5                | 256       |        |
| 12     | 8          | 6          | 1       | 0                | 1          | 6                | 320       |        |
| 13     | 8          | 6          | 2       | 0                | 1          | 6                | 384       |        |
| 14     | 8          | 6          | 3       | 0                | 1          | 6                | 448       |        |
| 15     | 8          | 6          | 4       | 0                | 1          | 6                | 512       |        |
| 16     | 9          | 7          | 1       | 0                | 1          | 7                | 640       |        |
| 17     | 9          | 7          | 2       | 0                | 1          | 7                | 768       |        |
| 18     | 9          | 7          | 3       | 0                | 1          | 7                | 896       |        |
| 19     | 9          | 7          | 4       | 0                | 1          | 7                | 1024      | 1K     |
| 20     | 10         | 8          | 1       | 0                | 1          | 8                | 1280      | 1.25K  |
| 21     | 10         | 8          | 2       | 0                | 1          | 8                | 1536      | 1.5K   |
| 22     | 10         | 8          | 3       | 0                | 1          | 8                | 1792      | 1.75K  |
| 23     | 10         | 8          | 4       | 0                | 1          | 8                | 2048      | 2K     |
| 24     | 11         | 9          | 1       | 0                | 1          | 9                | 2560      | 2.5K   |
| 25     | 11         | 9          | 2       | 0                | 1          | 9                | 3072      | 3K     |
| 26     | 11         | 9          | 3       | 0                | 1          | 9                | 3584      | 3.5K   |
| 27     | 11         | 9          | 4       | 0                | 1          | 9                | 4096      | 4K     |
| 28     | 12         | 10         | 1       | 0                | 1          | 0                | 5120      | 5K     |
| 29     | 12         | 10         | 2       | 0                | 1          | 0                | 6144      | 6K     |
| 30     | 12         | 10         | 3       | 0                | 1          | 0                | 7168      | 7K     |
| 31     | 12         | 10         | 4       | 1                | 1          | 0                | 8192      | 8K     |
| 32     | 13         | 11         | 1       | 0                | 1          | 0                | 10240     | 10K    |
| 33     | 13         | 11         | 2       | 0                | 1          | 0                | 12288     | 12K    |
| 34     | 13         | 11         | 3       | 0                | 1          | 0                | 14336     | 14K    |
| 35     | 13         | 11         | 4       | 1                | 1          | 0                | 16384     | 16K    |
| 36     | 14         | 12         | 1       | 0                | 1          | 0                | 20480     | 20K    |
| 37     | 14         | 12         | 2       | 1                | 1          | 0                | 24576     | 24K    |
| 38     | 14         | 12         | 3       | 0                | 1          | 0                | 28672     | 28K    |
| 39     | 14         | 12         | 4       | 1                | 0          | 0                | 32768     | 32K    |
| 40     | 15         | 13         | 1       | 1                | 0          | 0                | 40960     | 40K    |
| 41     | 15         | 13         | 2       | 1                | 0          | 0                | 49152     | 48K    |
| 42     | 15         | 13         | 3       | 1                | 0          | 0                | 57344     | 56K    |
| 43     | 15         | 13         | 4       | 1                | 0          | 0                | 65536     | 64K    |
| 44     | 16         | 14         | 1       | 1                | 0          | 0                | 81920     | 80K    |
| 45     | 16         | 14         | 2       | 1                | 0          | 0                | 98304     | 96K    |
| 46     | 16         | 14         | 3       | 1                | 0          | 0                | 114688    | 112K   |
| 47     | 16         | 14         | 4       | 1                | 0          | 0                | 131072    | 128K   |
| 48     | 17         | 15         | 1       | 1                | 0          | 0                | 163840    | 160K   |
| 49     | 17         | 15         | 2       | 1                | 0          | 0                | 196608    | 192K   |
| 50     | 17         | 15         | 3       | 1                | 0          | 0                | 229376    | 224K   |
| 51     | 17         | 15         | 4       | 1                | 0          | 0                | 262144    | 256K   |
| 52     | 18         | 16         | 1       | 1                | 0          | 0                | 327680    | 320K   |
| 53     | 18         | 16         | 2       | 1                | 0          | 0                | 393216    | 384K   |
| 54     | 18         | 16         | 3       | 1                | 0          | 0                | 458752    | 448K   |
| 55     | 18         | 16         | 4       | 1                | 0          | 0                | 524288    | 512K   |
| 56     | 19         | 17         | 1       | 1                | 0          | 0                | 655360    | 640K   |
| 57     | 19         | 17         | 2       | 1                | 0          | 0                | 786432    | 768K   |
| 58     | 19         | 17         | 3       | 1                | 0          | 0                | 917504    | 896K   |
| 59     | 19         | 17         | 4       | 1                | 0          | 0                | 1048576   | 1M     |
| 60     | 20         | 18         | 1       | 1                | 0          | 0                | 1310720   | 1.25M  |
| 61     | 20         | 18         | 2       | 1                | 0          | 0                | 1572864   | 1.5M   |
| 62     | 20         | 18         | 3       | 1                | 0          | 0                | 1835008   | 1.75M  |
| 63     | 20         | 18         | 4       | 1                | 0          | 0                | 2097152   | 2M     |
| 64     | 21         | 19         | 1       | 1                | 0          | 0                | 2621440   | 2.5M   |
| 65     | 21         | 19         | 2       | 1                | 0          | 0                | 3145728   | 3M     |
| 66     | 21         | 19         | 3       | 1                | 0          | 0                | 3670016   | 3.5M   |
| 67     | 21         | 19         | 4       | 1                | 0          | 0                | 4194304   | 4M     |
| 68     | 22         | 20         | 1       | 1                | 0          | 0                | 5242880   | 5M     |
| 69     | 22         | 20         | 2       | 1                | 0          | 0                | 6291456   | 6M     |
| 70     | 22         | 20         | 3       | 1                | 0          | 0                | 7340032   | 7M     |
| 71     | 22         | 20         | 4       | 1                | 0          | 0                | 8388608   | 8M     |
| 72     | 23         | 21         | 1       | 1                | 0          | 0                | 10485760  | 10M    |
| 73     | 23         | 21         | 2       | 1                | 0          | 0                | 12582912  | 12M    |
| 74     | 23         | 21         | 3       | 1                | 0          | 0                | 14680064  | 14M    |
| 75     | 23         | 21         | 4       | 1                | 0          | 0                | 16777216  | 16M    |

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