MAT :

怎么加载/这里边的一些概念 分别对应分析什么问题(泄露,线程,类加载器导致的泄露, 对象空间情况/

domain tree : 最大对象及谁持有它,保持存活的

histogram : 每个类数量和大小

• outgoing reference

• incoming reference

• group by (class,superclass, ClassLoader, package ) 主要分析哪里可能泄露了

leak suspect : 泄露分析 和系统视图

path to gc roots :

• These include for example the thread objects of the threads currently running, objects currently on the call stack and classes loaded by the system class loader.

栈视图 : 查看调用栈和栈详细信息

问题分析 :

• Heap Dump Overview

• Leak Suspects

• Top Components

Heap Dump Overview

• 就是整个堆的概括情况，例如：堆内存大小、对象个数、类的个数、类加载器的个数、GC root的个数、堆内存文件的格式、文件的创建时间、位置等信息。这个页面还开一个看一些系统属性、线程概览、Top内存耗费组件、类直方图等信息。

Top Components

• 针对那些占用堆内存超过整个堆内存1%大小的组件做一系列的分析，例如：Top Consumers、保留集合、潜在的内存浪费问题等其他问题。

Shallow heap 对象本身空间占用/Retained set对象集合,集合被回收则其元素也被回收/Retained heap 对象集合中所有对象占用空间综合

修改MAT内存大小 : /Applications/mat.app/Contents/Eclipse/MemoryAnalyzer.ini

除了直接导入dump文件还可以直接获取正在运行的进程的

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模拟oom killer :

• 关闭 swap

• dd 占用内存空间

• java不断开辟空间

-- 关闭swap :

swapoff -a

dd if=/dev/zero of=swapfile bs=1024 count=655360

mkswap swapfile

swapon swapfile

-- 执行命令 (注意参数放在前边 否则不生效)

java -Xms3g -Xmx3g -XX:+HeapDumpOnOutOfMemoryError -XX:HeapDumpPath=/root/ -Xloggc:/root/gc-myapp.log 编译后你的类名

-- 被杀检测 :

tail -100f /var/log/messages

dmesg 或 dmesg|grep Kill

-- 查看得分 得分越高 越容易被kill

more /proc/19668/oom_adj

more /proc/19668/oom_score_adj

-- 可用内存 :

cat /proc/meminfo | grep MemAvailable

free -m

ps aux --sort -pmem

top -o %MEM

— java code :

public static List<Object> outOfHeadMem = new ArrayList<>();public static void main(String[] args) {allocateOutOfHeapMem();}public static void allocateOutOfHeapMem() {while (true) {try{Thread.sleep(100L);}catch (Exception ignored) {};int size = 1024 * 1024;System.out.printf("%s : capacity = %s\n", System.currentTimeMillis(), size);outOfHeadMem.add(ByteBuffer.allocateDirect(size));}}

是否允许超过物理内存:

echo 1 > /proc/sys/vm/overcommit_memory

overcommit_memory

Defines the conditions that determine whether a large memory request is accepted or denied. There are three possible values for this parameter:

0 — The default setting. The kernel performs heuristic memory overcommit handling by estimating the amount of memory available and failing requests that are blatantly invalid. Unfortunately, since memory is allocated using a heuristic rather than a precise algorithm, this setting can sometimes allow available memory on the system to be overloaded.

1 — The kernel performs no memory overcommit handling. Under this setting, the potential for memory overload is increased, but so is performance for memory-intensive tasks.

2 — The kernel denies requests for memory equal to or larger than the sum of total available swap and the percentage of physical RAM specified in overcommit_ratio. This setting is best if you want a lesser risk of memory overcommitment.

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