快手在2020年中旬开源了一个线上OOM监控上报的框架:KOOM,这里简单研究下。
项目地址:https://github.com/KwaiAppTeam/KOOM/tree/v1.0.5
一、官方项目介绍
1.1 描述:
KOOM是快手性能优化团队在处理移动端OOM问题的过程中沉淀出的一套完整解决方案。其中Android Java内存部分在LeakCanary的基础上进行了大量优化,解决了线上内存监控的性能问题,在不影响用户体验的前提下线上采集内存镜像并解析。从 2020 年春节后在快手主APP上线至今解决了大量OOM问题,其性能和稳定性经受住了海量用户与设备的考验,因此决定开源以回馈社区。
1.2 特点:
- 比leakCanary更丰富的泄漏场景检测;
- 比leakCanary更好的检测性能;
- 功能全面的支持线上大规模部署的闭环监控系统;
1.3 KOOM框架
1.4 快手KOOM核心流程包括:
- 配置下发决策;
- 监控内存状态;
- 采集内存镜像;
- 解析镜像文件(以下简称hprof)生成报告并上传;
- 问题聚合报警与分配跟进。
1.5 泄漏检测触发机制优化:
泄漏检测触发机制leakCanary做法是GC过后对象WeakReference一直不被加入 ReferenceQueue,它可能存在内存泄漏。这个过程会主动触发GC做确认,可能会造成用户可感知的卡顿,而KOOM采用内存阈值监控来触发镜像采集,将对象是否泄漏的判断延迟到了解析时,阈值监控只要在子线程定期获取关注的几个内存指标即可,性能损耗很低。
1.6 heap dump优化:
传统方案会冻结应用几秒,KOOM会fork新进程来执行dump操作,对父进程的正常执行没有影响。暂停虚拟机需要调用虚拟机的art::Dbg::SuspendVM函数,谷歌从Android 7.0开始对调用系统库做了限制,快手自研了kwai-linker组件,通过caller address替换和dl_iterate_phdr解析绕过了这一限制。
随机采集线上真实用户的内存镜像,普通dump和fork子进程dump阻塞用户使用的耗时如下:
而从官方给出的测试数据来看,效果似乎是非常好的。
二、官方demo演示
这里就直接跑下官方提供的koom-demo
点击按钮,经过dump heap -> heap analysis -> report cache/koom/report/三个流程(heap analysis时间会比较长,但是完全不影响应用的正常操作),最终在应用的cache/koom/report里生成json报告:
cepheus:/data/data/com.kwai.koom.demo/cache/koom/report # ls
2020-12-08_15-23-32.json
模拟一个最简单的单例CommonUtils持有LeakActivity实例的内存泄漏,看下json最终上报的内容是个啥:
{
"analysisDone":true,
"classInfos":[
{
"className":"android.app.Activity",
"instanceCount":4,
"leakInstanceCount":3
},
{
"className":"android.app.Fragment",
"instanceCount":4,
"leakInstanceCount":3
},
{
"className":"android.graphics.Bitmap",
"instanceCount":115,
"leakInstanceCount":0
},
{
"className":"libcore.util.NativeAllocationRegistry",
"instanceCount":1513,
"leakInstanceCount":0
},
{
"className":"android.view.Window",
"instanceCount":4,
"leakInstanceCount":0
}
],
"gcPaths":[
{
"gcRoot":"Local variable in native code",
"instanceCount":1,
"leakReason":"Activity Leak",
"path":[
{
"declaredClass":"java.lang.Thread",
"reference":"android.os.HandlerThread.contextClassLoader",
"referenceType":"INSTANCE_FIELD"
},
{
"declaredClass":"java.lang.ClassLoader",
"reference":"dalvik.system.PathClassLoader.runtimeInternalObjects",
"referenceType":"INSTANCE_FIELD"
},
{
"declaredClass":"",
"reference":"java.lang.Object[]",
"referenceType":"ARRAY_ENTRY"
},
{
"declaredClass":"com.kwai.koom.demo.CommonUtils",
"reference":"com.kwai.koom.demo.CommonUtils.context",
"referenceType":"STATIC_FIELD"
},
{
"reference":"com.kwai.koom.demo.LeakActivity",
"referenceType":"instance"
}
],
"signature":"378fc01daea06b6bb679bd61725affd163d026a8"
}
],
"runningInfo":{
"analysisReason":"RIGHT_NOW",
"appVersion":"1.0",
"buildModel":"MI 9 Transparent Edition",
"currentPage":"LeakActivity",
"dumpReason":"MANUAL_TRIGGER",
"jvmMax":512,
"jvmUsed":2,
"koomVersion":1,
"manufacture":"Xiaomi",
"nowTime":"2020-12-08_16-07-34",
"pss":32,
"rss":123,
"sdkInt":29,
"threadCount":17,
"usageSeconds":40,
"vss":5674
}
}
这里主要分三个部分:类信息、gc引用路径、运行基本信息。这里从gcPaths中能看出LeakActivity被CommonUtils持有了引用。
框架使用这里参考官方接入文档即可,这里不赘述:
https://github.com/KwaiAppTeam/KOOM/blob/master/README.zh-CN.md
三、框架解析
3.1 类图
3.2 时序图
KOOM初始化流程
KOOM执行初始化方法,10秒延迟之后会在threadHandler子线程中先通过check状态判断是否开始工作,工作内容是先检查是不是有未完成分析的文件,如果有就就触发解析,没有则监控内存。
heap dump流程
HeapDumpTrigger
- startTrack:监控自动触发dump hprof操作。开启内存监控,子线程5s触发一次检测,看当前是否满足触发heap dump的条件。条件是由一系列阀值组织,这部分后面详细分析。满足阀值后会通过监听回调给HeapDumpTrigger去执行trigger。
- trigger:主动触发dump hprof操作。这里是fork子进程来处理的,这部分也到后面详细分析。dump完成之后通过监听回调触发HeapAnalysisTrigger.startTrack触发heap分析流程。
heap analysis流程
HeapAnalysisTrigger
- startTrack 根据策略触发hprof文件分析。
- trigger 直接触发hprof文件分析。由单独起进程的service来处理,工作内容主要分内存泄漏检测(activity/fragment/bitmap/window)和泄漏数据整理缓存为json文件以供上报。
四、核心源码解析
经过前面的分析,基本上对框架的使用和结构有了一个宏观了解,这部分就打算对一些实现细节进行简单分析。
4.1 内存监控触发dump规则
这里主要是研究HeapMonitor中isTrigger规则,每隔5S都会循环判断该触发条件。
com/kwai/koom/javaoom/monitor/HeapMonitor.java
@Override
public boolean isTrigger() {
if (!started) {
return false;
}
HeapStatus heapStatus = currentHeapStatus();
if (heapStatus.isOverThreshold) {
if (heapThreshold.ascending()) {
if (lastHeapStatus == null || heapStatus.used >= lastHeapStatus.used) {
currentTimes++;
} else {
currentTimes = 0;
}
} else {
currentTimes++;
}
} else {
currentTimes = 0;
}
lastHeapStatus = heapStatus;
return currentTimes >= heapThreshold.overTimes();
}
private HeapStatus lastHeapStatus;
private HeapStatus currentHeapStatus() {
HeapStatus heapStatus = new HeapStatus();
heapStatus.max = Runtime.getRuntime().maxMemory();
heapStatus.used = Runtime.getRuntime().totalMemory() - Runtime.getRuntime().freeMemory();
heapStatus.isOverThreshold = 100.0f * heapStatus.used / heapStatus.max > heapThreshold.value();
return heapStatus;
}
com/kwai/koom/javaoom/common/KConstants.java
public static class HeapThreshold {
public static int VM_512_DEVICE = 510;
public static int VM_256_DEVICE = 250;
public static int VM_128_DEVICE = 128;
public static float PERCENT_RATIO_IN_512_DEVICE = 80;
public static float PERCENT_RATIO_IN_256_DEVICE = 85;
public static float PERCENT_RATIO_IN_128_DEVICE = 90;
public static float getDefaultPercentRation() {
int maxMem = (int) (Runtime.getRuntime().maxMemory() / MB);
if (maxMem >= VM_512_DEVICE) {
return KConstants.HeapThreshold.PERCENT_RATIO_IN_512_DEVICE;
} else if (maxMem >= VM_256_DEVICE) {
return KConstants.HeapThreshold.PERCENT_RATIO_IN_256_DEVICE;
} else if (maxMem >= VM_128_DEVICE) {
return KConstants.HeapThreshold.PERCENT_RATIO_IN_128_DEVICE;
}
return KConstants.HeapThreshold.PERCENT_RATIO_IN_512_DEVICE;
}
public static int OVER_TIMES = 3;
public static int POLL_INTERVAL = 5000;
}
这里就是针对不同内存大小做了不同的阀值比例:
- 应用内存>512M 80%
- 应用内存>256M 85%
- 应用内存>128M 90%
- 低于128M的默认按80%
应用已使用内存/最大内存超过该比例则会触发heapStatus.isOverThreshold。连续满足3次触发heap dump,但是这个过程会考虑内存增长性,3次范围内出现了使用内存下降或者使用内存/最大内存低于对应阀值了则清零。
因此规则总结为:3次满足>阀值条件且内存一直处于上升期才触发。这样能减少无效的dump。
4.2 fork进程执行dump操作实现
目前项目中默认使用ForkJvmHeapDumper来执行dump。
com/kwai/koom/javaoom/dump/ForkJvmHeapDumper.java
@Override
public boolean dump(String path) {
boolean dumpRes = false;
try {
int pid = trySuspendVMThenFork();//暂停虚拟机,copy-on-write fork子进程
if (pid == 0) {//子进程中
Debug.dumpHprofData(path);//dump hprof
exitProcess();//_exit(0) 退出进程
} else {//父进程中
resumeVM();//resume当前虚拟机
dumpRes = waitDumping(pid);//waitpid异步等待pid进程结束
}
} catch (Exception e) {
e.printStackTrace();
}
return dumpRes;
}
谷歌从Android 7.0开始对调用系统库做了限制,快手自研了kwai-linker组件,通过caller address替换和dl_iterate_phdr解析绕过了这一限制,详细分析在后续的这篇文章有展开:KOOM V1.0.5 fork dump方案解析。
官方文档对限制的说明:
https://developer.android.google.cn/about/versions/nougat/android-7.0-changes
4.3 内存泄漏检测实现
内存泄漏检测核心代码在于SuspicionLeaksFinder.find
public Pair, List> find() {
boolean indexed = buildIndex();
if (!indexed) {
return null;
}
initLeakDetectors();
findLeaks();
return findPath();
}
4.3.1 buildIndex()
private boolean buildIndex() {
Hprof hprof = Hprof.Companion.open(hprofFile.file());
//选择可以作为gcroot的类类型
KClass[] gcRoots = new KClass[]{
Reflection.getOrCreateKotlinClass(GcRoot.JniGlobal.class),
//Reflection.getOrCreateKotlinClass(GcRoot.JavaFrame.class),
Reflection.getOrCreateKotlinClass(GcRoot.JniLocal.class),
//Reflection.getOrCreateKotlinClass(GcRoot.MonitorUsed.class),
Reflection.getOrCreateKotlinClass(GcRoot.NativeStack.class),
Reflection.getOrCreateKotlinClass(GcRoot.StickyClass.class),
Reflection.getOrCreateKotlinClass(GcRoot.ThreadBlock.class),
Reflection.getOrCreateKotlinClass(GcRoot.ThreadObject.class),
Reflection.getOrCreateKotlinClass(GcRoot.JniMonitor.class)};
//解析hprof文件为HeapGraph对象
heapGraph = HprofHeapGraph.Companion.indexHprof(hprof, null,
kotlin.collections.SetsKt.setOf(gcRoots));
return true;
}
fun indexHprof(
hprof: Hprof,
proguardMapping: ProguardMapping? = null,
indexedGcRootTypes: Set> = setOf(
JniGlobal::class,
JavaFrame::class,
JniLocal::class,
MonitorUsed::class,
NativeStack::class,
StickyClass::class,
ThreadBlock::class,
ThreadObject::class,
JniMonitor::class
)
): HeapGraph {
//确认对应的record的index
val index = HprofInMemoryIndex.createReadingHprof(hprof, proguardMapping, indexedGcRootTypes)
//HprofHeapGraph是HeapGraph的实现类
return HprofHeapGraph(hprof, index)
}
HprofInMemoryIndex.createReadingHprof核心逻辑:读取hprof文件,将不同内容封装为不同的record,然后将record转为索引化的index封装,之后查找内容可以通过index去索引到。
HprofReader.readHprofRecords() 封装record
- LoadClassRecord
- InstanceSkipContentRecord
- ObjectArraySkipContentRecord
- PrimitiveArraySkipContentRecord
HprofInMemoryIndex.onHprofRecord() 封装index:
- classIndex
- instanceIndex
- objectArrayIndex
- primitiveArrayIndex
class HprofHeapGraph internal constructor(
private val hprof: Hprof,
private val index: HprofInMemoryIndex
) : HeapGraph {
...
override val gcRoots: List
get() = index.gcRoots()
override val objects: Sequence
get() {
return index.indexedObjectSequence().map {wrapIndexedObject(it.second, it.first)}
}
override val classes: Sequence
get() {
return index.indexedClassSequence().map {val objectId = it.first
val indexedObject = it.second
HeapClass(this, indexedObject, objectId)
}
}
override val instances: Sequence
get() {
return index.indexedInstanceSequence().map {val objectId = it.first
val indexedObject = it.second
val isPrimitiveWrapper = index.primitiveWrapperTypes.contains(indexedObject.classId)
HeapInstance(this, indexedObject, objectId, isPrimitiveWrapper)
}
}
override val objectArrays: Sequence
get() = index.indexedObjectArraySequence().map {val objectId = it.first
val indexedObject = it.second
val isPrimitiveWrapper = index.primitiveWrapperTypes.contains(indexedObject.arrayClassId)
HeapObjectArray(this, indexedObject, objectId, isPrimitiveWrapper)
}
override val primitiveArrays: Sequence
get() = index.indexedPrimitiveArraySequence().map {val objectId = it.first
val indexedObject = it.second
HeapPrimitiveArray(this, indexedObject, objectId)
}
Hprof 经过层层转换最终封装为HprofHeapGraph。
简而言之,这部分功能主要是将Hrpof文件按照扫描的格式解析为结构化的索引关系图,索引化后的内容封装为HprofHeapGraph,由它去通过对应的起始索引去定位每类数据。没有细抠这部分的实现细节,实现这个功能的库之前是squere的HAHA,现在改为shark,但是提供的功能大同小异。
4.3.2 initLeakDetectors() 与findLeaks()
初始化泄漏检测者:
private void initLeakDetectors() {
addDetector(new ActivityLeakDetector(heapGraph));
addDetector(new FragmentLeakDetector(heapGraph));
addDetector(new BitmapLeakDetector(heapGraph));
addDetector(new NativeAllocationRegistryLeakDetector(heapGraph));
addDetector(new WindowLeakDetector(heapGraph));
ClassHierarchyFetcher.initComputeGenerations(computeGenerations);
leakReasonTable = new HashMap<>();
}
初始化各类型泄漏的检测者,主要包含Activity、Fragment、Bitmap+NativeAllocationRegistry、window的泄漏检测。
其次是梳理以上几类对象类继承关系串,检测覆盖到他们的子类。
public void findLeaks() {
KLog.i(TAG, "start find leaks");
//从HprofHeapGraph中获取所有instance
Sequence instances = heapGraph.getInstances();
Iterator instanceIterator = instances.iterator();
while (instanceIterator.hasNext()) {
HeapObject.HeapInstance instance = instanceIterator.next();
if (instance.isPrimitiveWrapper()) {
continue;
}
ClassHierarchyFetcher.process(instance.getInstanceClassId(),
instance.getInstanceClass().getClassHierarchy());
for (LeakDetector leakDetector : leakDetectors) {
//是检测对象的子类&满足对应泄漏条件
if (leakDetector.isSubClass(instance.getInstanceClassId())
&& leakDetector.isLeak(instance)) {
ClassCounter classCounter = leakDetector.instanceCount();
if (classCounter.leakInstancesCount <=
SAME_CLASS_LEAK_OBJECT_GC_PATH_THRESHOLD) {
leakingObjects.add(instance.getObjectId());
leakReasonTable.put(instance.getObjectId(), leakDetector.leakReason());
}
}
}
}
//关注class和对应instance数量,加入json
HeapAnalyzeReporter.addClassInfo(leakDetectors);
findPrimitiveArrayLeaks();
findObjectArrayLeaks();
}
这里重点看看各类型对象是如何判断泄漏的:
ActivityLeakDetector:
private static final String ACTIVITY_CLASS_NAME = "android.app.Activity";
private static final String FINISHED_FIELD_NAME = "mFinished";
private static final String DESTROYED_FIELD_NAME = "mDestroyed";
public boolean isLeak(HeapObject.HeapInstance instance) {
activityCounter.instancesCount++;
HeapField destroyField = instance.get(ACTIVITY_CLASS_NAME, DESTROYED_FIELD_NAME);
HeapField finishedField = instance.get(ACTIVITY_CLASS_NAME, FINISHED_FIELD_NAME);
assert destroyField != null;
assert finishedField != null;
boolean abnormal = destroyField.getValue().getAsBoolean() == null
|| finishedField.getValue().getAsBoolean() == null;
if (abnormal) {
return false;
}
boolean leak = destroyField.getValue().getAsBoolean()
|| finishedField.getValue().getAsBoolean();
if (leak) {
activityCounter.leakInstancesCount++;
}
return leak;
}
mDestroyed和mFinish字段为true,但是实例还存在的Activity是疑似泄漏对象。
FragmentLeakDetector:
private static final String NATIVE_FRAGMENT_CLASS_NAME = "android.app.Fragment";
// native android Fragment, deprecated as of API 28.
private static final String SUPPORT_FRAGMENT_CLASS_NAME = "android.support.v4.app.Fragment";
// pre-androidx, support library version of the Fragment implementation.
private static final String ANDROIDX_FRAGMENT_CLASS_NAME = "androidx.fragment.app.Fragment";
// androidx version of the Fragment implementation
private static final String FRAGMENT_MANAGER_FIELD_NAME = "mFragmentManager”;
private static final String FRAGMENT_MCALLED_FIELD_NAME = "mCalled”;//Used to verify that subclasses call through to super class.
public FragmentLeakDetector(HeapGraph heapGraph) {
HeapObject.HeapClass fragmentHeapClass =
heapGraph.findClassByName(ANDROIDX_FRAGMENT_CLASS_NAME);
fragmentClassName = ANDROIDX_FRAGMENT_CLASS_NAME;
if (fragmentHeapClass == null) {
fragmentHeapClass = heapGraph.findClassByName(NATIVE_FRAGMENT_CLASS_NAME);
fragmentClassName = NATIVE_FRAGMENT_CLASS_NAME;
}
if (fragmentHeapClass == null) {
fragmentHeapClass = heapGraph.findClassByName(SUPPORT_FRAGMENT_CLASS_NAME);
fragmentClassName = SUPPORT_FRAGMENT_CLASS_NAME;
}
assert fragmentHeapClass != null;
fragmentClassId = fragmentHeapClass.getObjectId();
fragmentCounter = new ClassCounter();
}
public boolean isLeak(HeapObject.HeapInstance instance) {
if (VERBOSE_LOG) {
KLog.i(TAG, "run isLeak");
}
fragmentCounter.instancesCount++;
boolean leak = false;
HeapField fragmentManager = instance.get(fragmentClassName, FRAGMENT_MANAGER_FIELD_NAME);
if (fragmentManager != null && fragmentManager.getValue().getAsObject() == null) {
HeapField mCalledField = instance.get(fragmentClassName, FRAGMENT_MCALLED_FIELD_NAME);
boolean abnormal = mCalledField == null || mCalledField.getValue().getAsBoolean() == null;
if (abnormal) {
KLog.e(TAG, "ABNORMAL mCalledField is null");
return false;
}
leak = mCalledField.getValue().getAsBoolean();
if (leak) {
if (VERBOSE_LOG) {
KLog.e(TAG, "fragment leak : " + instance.getInstanceClassName());
}
fragmentCounter.leakInstancesCount++;
}
}
return leak;
}
这里分了三种fragment:
- android.app.Fragment
- android.support.v4.app.Fragment
- androidx.fragment.app.Fragment
对应的FragmentManager实例为null(这表示fragment被remove了)且满足对应的mCalled为true,即非perform状态,而是对应生命周期被回调状态(onDestroy),但是实例还存在的Fragment是疑似泄漏对象。
BitmapLeakDetector
private static final String BITMAP_CLASS_NAME = "android.graphics.Bitmap”;
public boolean isLeak(HeapObject.HeapInstance instance) {
if (VERBOSE_LOG) {
KLog.i(TAG, "run isLeak");
}
bitmapCounter.instancesCount++;
HeapField fieldWidth = instance.get(BITMAP_CLASS_NAME, "mWidth");
HeapField fieldHeight = instance.get(BITMAP_CLASS_NAME, "mHeight");
assert fieldHeight != null;
assert fieldWidth != null;
boolean abnormal = fieldHeight.getValue().getAsInt() == null
|| fieldWidth.getValue().getAsInt() == null;
if (abnormal) {
KLog.e(TAG, "ABNORMAL fieldWidth or fieldHeight is null");
return false;
}
int width = fieldWidth.getValue().getAsInt();
int height = fieldHeight.getValue().getAsInt();
boolean suspicionLeak = width * height >= KConstants.BitmapThreshold.DEFAULT_BIG_BITMAP;
if (suspicionLeak) {
KLog.e(TAG, "bitmap leak : " + instance.getInstanceClassName() + " " +
"width:" + width + " height:" + height);
bitmapCounter.leakInstancesCount++;
}
return suspicionLeak;
}
这里是针对Bitmap size做判断,超过768*1366这个size的认为泄漏。
另外,NativeAllocationRegistryLeakDetector和WindowLeakDetector两类还没做具体泄漏判断规则,不参与对象泄漏检测,只是做了统计。
总结:
整体看下来,KOOM有两个值得借鉴的点:
1.触发内存泄漏检测,常规是watcher activity/fragment的onDestroy,而KOOM是定期轮询查看当前内存是否到达阀值;
2.dump hprof,常规是对应进程dump,而KOOM是fork进程dump。
参考:
快手自研OOM解决方案KOOM今日宣布开源