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iOS Out-Of-Memory 原理阐述及方案调研

什么是 OOM?

OOM 的全称是 Out-Of-Memory,是由于 iOS 的 Jetsam 机制造成的一种“另类” Crash,它不同于常规的 Crash,通过 Signal 捕获等 Crash 监控方案无法捕获到 OOM 事件。

为什么会发生 oom?

目前猜测两种情况会造成 OOM,

  1. 系统整体内存使用较高,系统基于优先级杀死优先级较低的 App
  2. 当前使用的 App 达到了 “high water mark”,也就是达到了系统对单个 App 的内存限制,系统会将你 Kill

验证方案 1 :

XNU 中 opensource.apple.com/source/xnu/… 、opensource.apple.com/source/xnu/… 提供了一些函数和宏,我们可以在 root 权限下使用这些宏和函数来获取当前状态下的所有 App 的 oom 内存阈值,并且基于 PID 甚至可以修改进程的 内存阈值,达到增大 oom内存阈值的效果。

对我们最有用的信息如下:

// 获取进程的 pid、优先级、状态、内存阈值等信息
typedef struct memorystatus_priority_entry {
    pid_t pid;
    int32_t priority;
    uint64_t user_data;
    int32_t limit;
    uint32_t state;
} memorystatus_priority_entry_t;
 
 
// 基于下面这些宏可以达到查询内存阈值等信息,也可以修改内存阈值等
/* Commands */
#define MEMORYSTATUS_CMD_GET_PRIORITY_LIST            1
#define MEMORYSTATUS_CMD_SET_PRIORITY_PROPERTIES      2
#define MEMORYSTATUS_CMD_GET_JETSAM_SNAPSHOT          3
#define MEMORYSTATUS_CMD_GET_PRESSURE_STATUS          4
#define MEMORYSTATUS_CMD_SET_JETSAM_HIGH_WATER_MARK   5    /* Set active memory limit = inactive memory limit, both non-fatal   */
#define MEMORYSTATUS_CMD_SET_JETSAM_TASK_LIMIT        6    /* Set active memory limit = inactive memory limit, both fatal   */
#define MEMORYSTATUS_CMD_SET_MEMLIMIT_PROPERTIES      7    /* Set memory limits plus attributes independently           */
#define MEMORYSTATUS_CMD_GET_MEMLIMIT_PROPERTIES      8    /* Get memory limits plus attributes                 */
#define MEMORYSTATUS_CMD_PRIVILEGED_LISTENER_ENABLE   9    /* Set the task's status as a privileged listener w.r.t memory notifications  */
#define MEMORYSTATUS_CMD_PRIVILEGED_LISTENER_DISABLE  10   /* Reset the task's status as a privileged listener w.r.t memory notifications  */
/* Commands that act on a group of processes */
#define MEMORYSTATUS_CMD_GRP_SET_PROPERTIES           100

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我们可以创建一个如下代码的程序

#include <stdlib.h>
#include <string.h>
#include <stdio.h>
#include "kern_memorystatus.h"

#define NUM_ENTRIES 1024

char *state_to_text(int State)
{
    // Convert kMemoryStatus constants to a textual representation

    static char returned[80];

    sprintf (returned, "0x%02x ",State);

    if (State & kMemorystatusSuspended) strcat(returned,"Suspended,");

    if (State & kMemorystatusFrozen) strcat(returned,"Frozen,");

    if (State & kMemorystatusWasThawed) strcat(returned,"WasThawed,");

    if (State & kMemorystatusTracked) strcat(returned,"Tracked,");

    if (State & kMemorystatusSupportsIdleExit) strcat(returned,"IdleExit,");

    if (State & kMemorystatusDirty) strcat(returned,"Dirty,");

    if (returned[strlen(returned) -1] == ',')

        returned[strlen(returned) -1] = '\0';

    return (returned);
}

int main (int argc, char **argv)
{
    struct memorystatus_priority_entry memstatus[NUM_ENTRIES];

    size_t  count = sizeof(struct memorystatus_priority_entry) * NUM_ENTRIES;

    // call memorystatus_control

    int rc = memorystatus_control (MEMORYSTATUS_CMD_GET_PRIORITY_LIST,    // 1 - only supported command on OS X

                                   0,    // pid

                                   0,    // flags

                                   memstatus, // buffer

                                   count); // buffersize

    if (rc < 0) { perror ("memorystatus_control"); exit(rc);}

    int entry = 0;

    for (; rc > 0; rc -= sizeof(struct memorystatus_priority_entry))
    {
        printf ("PID: %5d\tPriority:%2d\tUser Data: %llx\tLimit:%2d\tState:%s\n",

                memstatus[entry].pid,

                memstatus[entry].priority,

                memstatus[entry].user_data,

                memstatus[entry].limit,

                state_to_text(memstatus[entry].state));

        entry++;
    }
}
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然后通过 MonekyDev 提供的 Command-line Tool 工具将程序注入到越狱设备(当时的测试环境为5s、iOS 9.1)中去,通过 SSH 连接到设备,然后通过终端运行该程序。就可以得到 dump 的信息。如下所示:

PID:  9967	Priority: 3	User Data: 0	Limit: 6	State:0x38 Tracked,IdleExit,Dirty
PID: 11151	Priority: 3	User Data: 0	Limit: 6	State:0x38 Tracked,IdleExit,Dirty
PID: 11154	Priority: 3	User Data: 0	Limit:10	State:0x38 Tracked,IdleExit,Dirty
PID: 11165	Priority: 3	User Data: 0	Limit: 6	State:0x38 Tracked,IdleExit,Dirty
PID: 11499	Priority: 3	User Data: 0	Limit:18	State:0x28 Tracked,Dirty
PID: 10039	Priority: 4	User Data: 2100	Limit:108	State:0x00
PID:  9981	Priority: 7	User Data: 0	Limit:10	State:0x08 Tracked
PID:  9977	Priority: 7	User Data: 0	Limit:20	State:0x08 Tracked
PID:  9979	Priority: 7	User Data: 0	Limit:25	State:0x38 Tracked,IdleExit,Dirty
PID: 10021	Priority: 7	User Data: 0	Limit: 6	State:0x08 Tracked
PID: 11575	Priority:10	User Data: 10100	Limit:650	State:0x00
PID:   103	Priority:11	User Data: 0	Limit:96	State:0x08 Tracked
PID: 11442	Priority:11	User Data: 0	Limit:38	State:0x08 Tracked
PID:    67	Priority:12	User Data: 0	Limit:24	State:0x28 Tracked,Dirty
PID:    31	Priority:14	User Data: 0	Limit:650	State:0x08 Tracked
PID:    45	Priority:14	User Data: 0	Limit: 9	State:0x08 Tracked
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以上代码中,Priority:10 的进程就是我测试的 好好学习 App,此时 App 在前台并且活跃,所以优先级是 10,并且得到 oom 内存阈值是 650

验证方案 2 :

当我们的 App 由于 jetsam 被杀死的时候,在手机中会有系统日志,从手机设置-隐私-分析这条操作路径中,可以拿到JetsamEvent 开头的日志。这些日志中就可以获取一些关于 App 的内存信息,以我的 6s 为例,pageSize * rpages 的值获取的值便是阈值,同时日志中也表明原因是  "reason" : "per-process-limit" (并不是所有的  JetsamEvent 中都可以拿到准确的阈值,有的存在偏差。。。)

"pageSize" : 16384
{
    "uuid" : "b8d6682c-5903-3007-b9c2-561d1e6ca9d5",
    "states" : [
      "frontmost",
      "resume"
    ],
    "killDelta" : 18859,
    "genCount" : 0,
    "age" : 1775369503,
    "purgeable" : 0,
    "fds" : 50,
    "coalition" : 691,
    "rpages" : 89600,
    "reason" : "per-process-limit",
    "pid" : 960,
    "cpuTime" : 1.6920809999999999,
    "name" : "MemoryLimitTest",
    "lifetimeMax" : 34182
}
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验证方案 3:

可以通过大量的测试来寻找它的oom 内存阈值是多少,StackOverFlow 上已经存在一个清单,该清单列举了一些常见设备的 oom 阈值。该清单阈值和真实阈值存在偏差,我猜测原有有二,第一,它取内存的时机不可能完全和 oom 时机吻合,只能尽可能接近这个时机,第二,他取内存的方法和 XNU 中 jetsam 机制所用的内存获取方式不一致。正确获取内存的方式下面会阐述。

Results of testing with the utility Split wrote (link is in his answer):
device: (crash amount/total amount/percentage of total)
iPad1: 127MB/256MB/49%
iPad2: 275MB/512MB/53%
iPad3: 645MB/1024MB/62%
iPad4: 585MB/1024MB/57% (iOS 8.1)
iPad Mini 1st Generation: 297MB/512MB/58%
iPad Mini retina: 696MB/1024MB/68% (iOS 7.1)
iPad Air: 697MB/1024MB/68%
iPad Air 2: 1383MB/2048MB/68% (iOS 10.2.1)
iPad Pro 9.7": 1395MB/1971MB/71% (iOS 10.0.2 (14A456))
iPad Pro 10.5”: 3057/4000/76% (iOS 11 beta4) 
iPad Pro 12.9” (2015): 3058/3999/76% (iOS 11.2.1)
iPad Pro 12.9” (2017): 3057/3974/77% (iOS 11 beta4)
iPod touch 4th gen: 130MB/256MB/51% (iOS 6.1.1)
iPod touch 5th gen: 286MB/512MB/56% (iOS 7.0)
iPhone4: 325MB/512MB/63%
iPhone4s: 286MB/512MB/56%
iPhone5: 645MB/1024MB/62%
iPhone5s: 646MB/1024MB/63%
iPhone6: 645MB/1024MB/62% (iOS 8.x)
iPhone6+: 645MB/1024MB/62% (iOS 8.x)
iPhone6s: 1396MB/2048MB/68% (iOS 9.2)
iPhone6s+: 1392MB/2048MB/68% (iOS 10.2.1)
iPhoneSE: 1395MB/2048MB/69% (iOS 9.3)
iPhone7: 1395/2048MB/68% (iOS 10.2)
iPhone7+: 2040MB/3072MB/66% (iOS 10.2.1)
iPhone X: 1392/2785/50% (iOS 11.2.1)

https://stackoverflow.com/questions/5887248/ios-app-maximum-memory-budget/15200855#15200855
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如何正确度量 App 的使用内存

常见的获取 App 内存的方式是使用 resident_size 代码如下:

#import <mach/mach.h>

- (int64_t)memoryUsage {
    int64_t memoryUsageInByte = 0;
    struct task_basic_info taskBasicInfo;
    mach_msg_type_number_t size = sizeof(taskBasicInfo);
    kern_return_t kernelReturn = task_info(mach_task_self(), TASK_BASIC_INFO, (task_info_t) &taskBasicInfo, &size);

    if(kernelReturn == KERN_SUCCESS) {
        memoryUsageInByte = (int64_t) taskBasicInfo.resident_size;
        NSLog(@"Memory in use (in bytes): %lld", memoryUsageInByte);
    } else {
        NSLog(@"Error with task_info(): %s", mach_error_string(kernelReturn));
    }

    return memoryUsageInByte;
}
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而正确的方式应该是使用 phys_footprint,因为 Apple 就是用的这个指标,和 Apple 保持一致才能说明问题。可以看源码验证一下:opensource.apple.com/source/xnu/…

#import <mach/mach.h>

- (int64_t)memoryUsage {
    int64_t memoryUsageInByte = 0;
    task_vm_info_data_t vmInfo;
    mach_msg_type_number_t count = TASK_VM_INFO_COUNT;
    kern_return_t kernelReturn = task_info(mach_task_self(), TASK_VM_INFO, (task_info_t) &vmInfo, &count);
    if(kernelReturn == KERN_SUCCESS) {
        memoryUsageInByte = (int64_t) vmInfo.phys_footprint;
        NSLog(@"Memory in use (in bytes): %lld", memoryUsageInByte);
    } else {
        NSLog(@"Error with task_info(): %s", mach_error_string(kernelReturn));
    }

    return memoryUsageInByte;
}
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oom 定位的方案

方案1:

最早看到 oom 相关的方案是 FaceBook 的一篇博客中讲到的,code.facebook.com/posts/11469…,通过排除法来统计 OOM 率是多少。当然这种方案统计的结果多少会与实际数据存在误差,比如 ApplicationState 不准确,watchdog 也被统计在 oom 中之类的。

方案2:

近期腾讯也开源了自己的 OOM 定位方案,OOMDetector 组件:github.com/Tencent/OOM… 。这种方案通过利用 libmalloc 中的 malloc_logger 函数指针,可以通过堆栈来帮助开发定位大内存。但是也存在一些缺陷,就是频繁的 dump 堆栈对 App 性能造成了影响,只能灰度一小部分用户来进行数据统计和定位。

方案3:

基于近期的发现,可以在线下获取 App 的 high water mark,也就是 oom 内存阈值。 那么就产生了方案3

  • 监控内存增长,在达到  high water mark 附近的时候,dump 内存信息,获取对象名称、对象个数、各对象的内存值;如果稳定可以全量开启,不会有性能问题
  • OOMDetector 可以拿到分配内存的堆栈,对于定位到代码层面更加有效;可以灰度开放