三方库源码笔记(5)- LeakCanary 源码详解

对于 Android Developer 来说,很多开源库都是属于开发必备的知识点,从使用方式到实现原理再到源码解析,这些都需要我们有一定程度的了解和运用能力。所以我打算来写一系列关于开源库源码解析实战演练的文章,初定的目标是 EventBus、ARouter、LeakCanary、Retrofit、Glide、OkHttp、Coil 等七个知名开源库,希望对你有所帮助

LeakCanary 是由 Square 公司开源的用于 Android 的内存泄漏检测工具,可以帮助开发者发现内存泄露情况并且找出泄露源头,有助于减少 OutOfMemoryError 情况的发生。在目前的应用开发中也算作是性能优化的一个重要实现途径,很多面试官在考察性能优化时都会问到 LeakCanary 的实现原理

本文就来对其实现原理进行分析,具体的 Git 版本节点是:9f62126e,来了解 LeakCanary 的整体运行流程和实现原理

一、支持的内存泄露类型

我们经常说 LeakCanary 能检测到应用内发生的内存泄露,那么它到底具体支持什么类型的内存泄露情况呢?LeakCanary 官网有对此进行介绍:

LeakCanary automatically detects leaks of the following objects:

  • destroyed Activity instances
  • destroyed Fragment instances
  • destroyed fragment View instances
  • cleared ViewModel instances

我们也可以从 LeakCanary 的 AppWatcher.Config 这个类找到答案。Config 类用于配置是否开启内存检测,从其配置项就可以看出来 leakcanary 支持:Activity、Fragment、FragmentView、ViewModel 等四种类型

data class Config(
    /**
     * Whether AppWatcher should automatically watch destroyed activity instances.
     *
     * Defaults to true.
     */
    val watchActivities: Boolean = true,

    /**
     * Whether AppWatcher should automatically watch destroyed fragment instances.
     *
     * Defaults to true.
     */
    val watchFragments: Boolean = true,

    /**
     * Whether AppWatcher should automatically watch destroyed fragment view instances.
     *
     * Defaults to true.
     */
    val watchFragmentViews: Boolean = true,

    /**
     * Whether AppWatcher should automatically watch cleared [androidx.lifecycle.ViewModel]
     * instances.
     *
     * Defaults to true.
     */
    val watchViewModels: Boolean = true,

    /**
     * How long to wait before reporting a watched object as retained.
     *
     * Default to 5 seconds.
     */
    val watchDurationMillis: Long = TimeUnit.SECONDS.toMillis(5),

    /**
     * Deprecated, this didn't need to be a part of the API.
     * Used to indicate whether AppWatcher should watch objects (by keeping weak references to
     * them). Currently a no-op.
     *
     * If you do need to stop watching objects, simply don't pass them to [objectWatcher].
     */
    @Deprecated("This didn't need to be a part of LeakCanary's API. No-Op.")
    val enabled: Boolean = true
  )

二、初始化

如今,我们在项目中引入 LeakCanary 只需要添加如下依赖即可,无须任何的初始化行为等附加操作,当应用启动时 LeakCanary 就会自动启动并开始监测了

dependencies {
  // debugImplementation because LeakCanary should only run in debug builds.
  debugImplementation 'com.squareup.leakcanary:leakcanary-android:2.4'
}

一般来说,像这类第三方库都是需要由外部传入一个 ApplicationContext 对象进行初始化并启动的,LeakCanary 的 1.x 版本也是如此,但在 2.x 版本中,LeakCanary 将初始过程交由 AppWatcherInstaller 这个 ContentProvider 来自动完成

internal sealed class AppWatcherInstaller : ContentProvider() {

    /**
     * [MainProcess] automatically sets up the LeakCanary code that runs in the main app process.
     */
    internal class MainProcess : AppWatcherInstaller()

    /**
     * When using the `leakcanary-android-process` artifact instead of `leakcanary-android`,
     * [LeakCanaryProcess] automatically sets up the LeakCanary code
     */
    internal class LeakCanaryProcess : AppWatcherInstaller()

    override fun onCreate(): Boolean {
        val application = context!!.applicationContext as Application
        AppWatcher.manualInstall(application)
        return true
    }

    ···
}

由于 ContentProvider 会在 Application 被创建之前就由系统调用其 onCreate() 方法来完成初始化,所以 LeakCanary 通过 AppWatcherInstaller 就可以拿到 Context 来完成初始化并随应用一起启动,通过这种方式就简化了使用者的引入成本。而且由于我们的引用方式是 debugImplementation,所以正式版本会自动移除对 LeakCanary 的所有引用,进一步简化了引入成本

Jetpack 也包含了一个组件来实现通过 ContentProvider 来完成初始化的逻辑:AppStartup。在实现思路上两者很类似,但是如果每个三方库都通过自定义 ContentProvider 来实现初始化的话,那么应用的启动速度就会很感人了吧 :joy:,所以 Jetpack 官方推出的 AppStartup 应该是以后的主流才对

AppWatcherInstaller 最终会将 Application 对象传给 InternalAppWatcherinstall(Application) 方法

/**
 * Note: this object must load fine in a JUnit environment
 */
internal object InternalAppWatcher {

  ···
    
  val objectWatcher = ObjectWatcher(
      clock = clock,
      checkRetainedExecutor = checkRetainedExecutor,
      isEnabled = { true }
  )

  fun install(application: Application) {
    //检测是否在 main 线程
    checkMainThread()
    //避免重复初始化
    if (this::application.isInitialized) {
      return
    }
    InternalAppWatcher.application = application
    if (isDebuggableBuild) {
      SharkLog.logger = DefaultCanaryLog()
    }
    //拿到默认配置,默认四种类型都进行检测
    val configProvider = { AppWatcher.config }
    //检测 Activity
    ActivityDestroyWatcher.install(application, objectWatcher, configProvider)
    //检测 Fragment、FragmentView、ViewModel
    FragmentDestroyWatcher.install(application, objectWatcher, configProvider)
    onAppWatcherInstalled(application)
  }

  ···
      
}

LeakCanary 具体进行内存泄露检测的逻辑可以分为三类:

  • ObjectWatcher。检测 Object 的内存泄露情况
  • ActivityDestroyWatcher。检测 Activity 的内存泄露情况
  • FragmentDestroyWatcher。检测 Fragment、FragmentView、ViewModel 的内存泄露情况

当中,ActivityDestroyWatcherFragmentDestroyWatcher 都需要依靠 ObjectWatcher 来完成,因为 Activity、Fragment、FragmentView、ViewModel 本质上都属于不同类型的 Object

三、ObjectWatcher:检测任意对象

我们知道,当一个对象不再被我们引用时,如果该对象由于代码错误或者其它原因导致迟迟无法被系统回收,此时就是发生了内存泄露。那么 LeakCanary 是怎么知道应用是否发生了内存泄露呢?

这个可以依靠引用队列 ReferenceQueue 来实现。先来看个小例子

/**
 * @Author: leavesCZY
 * @Github:https://github.com/leavesCZY
 */
fun main() {
    val referenceQueue = ReferenceQueue?>()
    var pair: Pair? = Pair("name", 24)
    val weakReference = WeakReference(pair, referenceQueue)

    println(referenceQueue.poll()) //null

    pair = null

    System.gc()
    //GC 后休眠一段时间,等待 pair 被回收
    Thread.sleep(4000)

    println(referenceQueue.poll()) //java.lang.ref.WeakReference@d716361
}

可以看到,在 GC 过后 referenceQueue.poll() 的返回值变成了非 null,这是由于 WeakReferenceReferenceQueue 的一个组合特性导致的:在声明一个 WeakReference 对象时如果同时传入了 ReferenceQueue 作为构造参数的话,那么当 WeakReference 持有的对象被 GC 回收时,JVM 就会把这个弱引用存入与之关联的引用队列之中。依靠这个特性,我们就可以实现内存泄露的检测了

例如,当用户按返回键退出 Activity 时,正常情况下该 Activity 对象应该在不久后就被系统回收,我们可以监听 Activity 的 onDestroy 回调,在回调时把 Activity 对象保存到和 ReferenceQueue 关联的 WeakReference 中,在一段时间后(可以主动触发几次 GC)检测 ReferenceQueue 中是否有值,如果一直为 null 的话就说明发生了内存泄露。LeakCanary 就是通过这种方法来实现的

ObjectWatcher 中就封装了上述逻辑,这里来看看其实现逻辑

ObjectWatcher 的起始方法是 watch(Any, String),该方法就用于监听指定对象

/**
 * References passed to [watch].
 * 用于保存要监听的对象,mapKey 是该对象的唯一标识、mapValue 是该对象的弱引用
 */
private val watchedObjects = mutableMapOf()

//KeyedWeakReference 关联的引用队列
private val queue = ReferenceQueue()

/**
 * Watches the provided [watchedObject].
 *
 * @param description Describes why the object is watched.
 */
@Synchronized
fun watch(watchedObject: Any, description: String) {
    if (!isEnabled()) {
        return
    }
    removeWeaklyReachableObjects()
    //为 watchedObject 生成一个唯一标识
    val key = UUID.randomUUID().toString()
    val watchUptimeMillis = clock.uptimeMillis()
    //创建 watchedObject 关联的弱引用
    val reference = KeyedWeakReference(watchedObject, key, description, watchUptimeMillis, queue)
    ···
    watchedObjects[key] = reference
    checkRetainedExecutor.execute {
        moveToRetained(key)
    }
}

watch() 方法的主要逻辑:

  1. 为每个 watchedObject 生成一个唯一标识 key,通过该 key 构建一个 watchedObject 的弱引用 KeyedWeakReference,将该弱引用保存到 watchedObjects 中。ObjectWatcher 可以先后监测多个对象,每个对象都会先被存入到 watchedObjects
  2. 外部通过传入的 checkRetainedExecutor 来指定检测内存泄露的触发时机,通过 moveToRetained 方法来判断是否真的发生了内存泄露

KeyedWeakReference 是一个自定义的 WeakReference 子类,包含一个唯一 key 来标识特定对象,也包含一个 retainedUptimeMillis 字段用来标记是否发生了内存泄露

class KeyedWeakReference(
        referent: Any,
        val key: String,
        val description: String,
        val watchUptimeMillis: Long,
        referenceQueue: ReferenceQueue
) : WeakReference(
        referent, referenceQueue
) {
    /**
     * Time at which the associated object ([referent]) was considered retained, or -1 if it hasn't
     * been yet.
     * 用于标记 referent 是否还未被回收,是的话则值不为 -1
     */
    @Volatile
    var retainedUptimeMillis = -1L

    companion object {
        @Volatile
        @JvmStatic
        var heapDumpUptimeMillis = 0L
    }

}

moveToRetained 方法就用于判断指定 key 关联的对象是否已经泄露,如果没有泄露则移除对该对象的弱引用,有泄露的话则更新其 retainedUptimeMillis 值,以此来标记其发生了泄露,并同时通过回调 onObjectRetainedListeners 来分析内存泄露链

@Synchronized
private fun moveToRetained(key: String) {
    removeWeaklyReachableObjects()
    val retainedRef = watchedObjects[key]
    if (retainedRef != null) {
        //记录当前时间
        retainedRef.retainedUptimeMillis = clock.uptimeMillis()
        onObjectRetainedListeners.forEach { it.onObjectRetained() }
    }
}

//如果判断到一个对象没有发生内存泄露,那么就移除对该对象的弱引用
//此方法会先后调用多次
private fun removeWeaklyReachableObjects() {
    // WeakReferences are enqueued as soon as the object to which they point to becomes weakly
    // reachable. This is before finalization or garbage collection has actually happened.
    var ref: KeyedWeakReference?
    do {
        ref = queue.poll() as KeyedWeakReference?
        if (ref != null) {
            //如果 ref 不为 null,说明 ref 关联的对象没有发生内存泄露,那么就移除对该对象的引用
            watchedObjects.remove(ref.key)
        }
    } while (ref != null)
}

四、ActivityDestroyWatcher:检测Activity

理解了 ObjectWatcher 的流程后来看 ActivityDestroyWatcher 就会比较简单了。ActivityDestroyWatcher 会向 Application 注册一个 ActivityLifecycleCallbacks 回调,当收到每个 Activity 执行了 onDestroy 的回调后,就会将将 Activity 对象转交由 ObjectWatcher 来进行监听

internal class ActivityDestroyWatcher private constructor(private val objectWatcher: ObjectWatcher, private val configProvider: () -> Config) {

    private val lifecycleCallbacks = object : Application.ActivityLifecycleCallbacks by noOpDelegate() {
        override fun onActivityDestroyed(activity: Activity) {
            if (configProvider().watchActivities) {
                objectWatcher.watch(activity, "${activity::class.java.name} received Activity#onDestroy() callback"
                )
            }
        }
    }

    companion object {
        fun install(application: Application, objectWatcher: ObjectWatcher, configProvider: () -> Config) {
            val activityDestroyWatcher = ActivityDestroyWatcher(objectWatcher, configProvider)
            application.registerActivityLifecycleCallbacks(activityDestroyWatcher.lifecycleCallbacks)
        }
    }

}

五、FragmentDestroyWatcher:检测Fragment

做 Android 应用开发的应该都知道,现在 Google 提供的基础依赖包分为了 SupportAndroidX 两种,Support 版本已经不再维护,主流的都是使用 AndroidX 了。而 LeakCanary 为了照顾老项目,就贴心的为这两种版本分别提供了 Fragment 的内存检测功能

FragmentDestroyWatcher 可以看做是一个分发器,它会根据外部环境的不同来选择不同的检测手段,其主要逻辑是:

  • 系统版本大于等于 8.0。使用 AndroidOFragmentDestroyWatcher 来检测 Fragment、FragmentView 的内存泄露
  • 开发者使用的是 Support 包。使用 AndroidSupportFragmentDestroyWatcher 来检测 Fragment、FragmentView 的内存泄露
  • 开发者使用的是 AndroidX 包。使用 AndroidXFragmentDestroyWatcher 来检测 Fragment、FragmentView、ViewModel 的内存泄露
  • 通过反射 Class.forName 来判断开发者使用的是 Support 包还是 AndroidX 包
  • 由于 Fragment 都需要被挂载在 Activity 上,所有向 Application 注册一个 ActivityLifecycleCallback,每当有 Activity 被创建时就监听该 Activity 内可能存在的 Fragment

这里令我很疑惑的一个点就是:当系统版本大于等于 8.0 时,AndroidOFragmentDestroyWatcher 不就会和 AndroidSupportFragmentDestroyWatcher 或者 AndroidXFragmentDestroyWatcher 重复了吗?这算咋回事:joy:

internal object FragmentDestroyWatcher {

  private const val ANDROIDX_FRAGMENT_CLASS_NAME = "androidx.fragment.app.Fragment"
  private const val ANDROIDX_FRAGMENT_DESTROY_WATCHER_CLASS_NAME =
    "leakcanary.internal.AndroidXFragmentDestroyWatcher"

  // Using a string builder to prevent Jetifier from changing this string to Android X Fragment
  @Suppress("VariableNaming", "PropertyName")
  private val ANDROID_SUPPORT_FRAGMENT_CLASS_NAME =
    StringBuilder("android.").append("support.v4.app.Fragment")
        .toString()
  private const val ANDROID_SUPPORT_FRAGMENT_DESTROY_WATCHER_CLASS_NAME =
    "leakcanary.internal.AndroidSupportFragmentDestroyWatcher"

  fun install(
    application: Application,
    objectWatcher: ObjectWatcher,
    configProvider: () -> AppWatcher.Config
  ) {
    val fragmentDestroyWatchers = mutableListOf<(Activity) -> Unit>()

    if (SDK_INT >= O) {
      fragmentDestroyWatchers.add(
          AndroidOFragmentDestroyWatcher(objectWatcher, configProvider)
      )
    }

    //AndroidX 
    getWatcherIfAvailable(
        ANDROIDX_FRAGMENT_CLASS_NAME,
        ANDROIDX_FRAGMENT_DESTROY_WATCHER_CLASS_NAME,
        objectWatcher,
        configProvider
    )?.let {
      fragmentDestroyWatchers.add(it)
    }

    //Support 
    getWatcherIfAvailable(
        ANDROID_SUPPORT_FRAGMENT_CLASS_NAME,
        ANDROID_SUPPORT_FRAGMENT_DESTROY_WATCHER_CLASS_NAME,
        objectWatcher,
        configProvider
    )?.let {
      fragmentDestroyWatchers.add(it)
    }

    if (fragmentDestroyWatchers.size == 0) {
      return
    }

    application.registerActivityLifecycleCallbacks(object : Application.ActivityLifecycleCallbacks by noOpDelegate() {
      override fun onActivityCreated(
        activity: Activity,
        savedInstanceState: Bundle?
      ) {
        for (watcher in fragmentDestroyWatchers) {
          watcher(activity)
        }
      }
    })
  }

  ···
}

由于 AndroidXFragmentDestroyWatcherAndroidSupportFragmentDestroyWatcherAndroidOFragmentDestroyWatcher 在逻辑上很类似,且就 AndroidXFragmentDestroyWatcher 同时提供了 ViewModel 内存泄露的检测功能,所以这里只看 AndroidXFragmentDestroyWatcher 就行

AndroidXFragmentDestroyWatcher 的主要逻辑是:

  • 在 invoke 方法里向 Activity 的 FragmentManager 以及 childFragmentManager 注册一个 FragmentLifecycleCallback,通过该回调拿到 onFragmentViewDestroyed 和 onFragmentDestroyed 的事件通知,收到通知时就通过 ObjectWatcher 启动检测
  • 在 onFragmentCreated 回调里通过 ViewModelClearedWatcher 来启动和 Fragment 关联的 ViewModel 的内存泄露检测逻辑
  • 在 invoke 方法里通过 ViewModelClearedWatcher 来启动和 Activity 关联的 ViewModel 的内存泄露检测
internal class AndroidXFragmentDestroyWatcher(
  private val objectWatcher: ObjectWatcher,
  private val configProvider: () -> Config
) : (Activity) -> Unit {

  private val fragmentLifecycleCallbacks = object : FragmentManager.FragmentLifecycleCallbacks() {

    override fun onFragmentCreated(
      fm: FragmentManager,
      fragment: Fragment,
      savedInstanceState: Bundle?
    ) {
      ViewModelClearedWatcher.install(fragment, objectWatcher, configProvider)
    }

    override fun onFragmentViewDestroyed(
      fm: FragmentManager,
      fragment: Fragment
    ) {
      val view = fragment.view
      if (view != null && configProvider().watchFragmentViews) {
        objectWatcher.watch(
            view, "${fragment::class.java.name} received Fragment#onDestroyView() callback " +
            "(references to its views should be cleared to prevent leaks)"
        )
      }
    }

    override fun onFragmentDestroyed(
      fm: FragmentManager,
      fragment: Fragment
    ) {
      if (configProvider().watchFragments) {
        objectWatcher.watch(
            fragment, "${fragment::class.java.name} received Fragment#onDestroy() callback"
        )
      }
    }
  }

  override fun invoke(activity: Activity) {
    if (activity is FragmentActivity) {
      val supportFragmentManager = activity.supportFragmentManager
      supportFragmentManager.registerFragmentLifecycleCallbacks(fragmentLifecycleCallbacks, true)
      ViewModelClearedWatcher.install(activity, objectWatcher, configProvider)
    }
  }
}

Fragment 和 FragmentView 走向 Destroyed 时,正常情况下它们都是不会被复用的,应该会很快就被 GC 回收,且它们本质上都只是一种对象,所以直接使用 ObjectWatcher 进行检测即可

六、ViewModelClearedWatcher:检测ViewModel

和 Fragment、FragmentView 相比,ViewModel 就比较特殊了,由于可能存在一个 Activity 和多个 Fragment 同时持有一个 ViewModel 实例的情况,而 leakcanary 无法知道 ViewModel 到底是同时被几个持有者所持有,所以无法通过单独一个 Activity 和 Fragment 的 Destroyed 回调来启动对 ViewModel 的检测。幸好 ViewMode 也提供了 onCleared() 的回调事件,leakcanary 就通过该回调来知道 ViewModel 是什么时候需要被回收。对 ViewModel 的实现原理不清楚的同学可以看我的这篇文章:从源码看 Jetpack(6)-ViewModel源码详解

ViewModelClearedWatcher 的主要逻辑是:

  • ViewModelClearedWatcher 继承于 ViewModel,当拿到 ViewModelStoreOwner 实例(Activity 或者 Fragment)后,就创建一个和该实例绑定的 ViewModelClearedWatcher 对象
  • ViewModelClearedWatcher 通过反射获取到 ViewModelStore 中的 mMap 变量,该变量就存储了所有的 Viewmodel 实例
  • 当 ViewModelClearedWatcher 的 onCleared() 方法被回调了,就说明了所有和 Activity 或者 Fragment 绑定的 ViewModel 实例都不再被需要了,此时就可以开始监测所有的 ViewModel 实例了
internal class ViewModelClearedWatcher(
        storeOwner: ViewModelStoreOwner,
        private val objectWatcher: ObjectWatcher,
        private val configProvider: () -> Config
) : ViewModel() {

    private val viewModelMap: Map?

    init {
        // We could call ViewModelStore#keys with a package spy in androidx.lifecycle instead,
        // however that was added in 2.1.0 and we support AndroidX first stable release. viewmodel-2.0.0
        // does not have ViewModelStore#keys. All versions currently have the mMap field.
        viewModelMap = try {
            val mMapField = ViewModelStore::class.java.getDeclaredField("mMap")
            mMapField.isAccessible = true
            @Suppress("UNCHECKED_CAST")
            mMapField[storeOwner.viewModelStore] as Map
        } catch (ignored: Exception) {
            null
        }
    }

    override fun onCleared() {
        if (viewModelMap != null && configProvider().watchViewModels) {
            viewModelMap.values.forEach { viewModel ->
                objectWatcher.watch(
                        viewModel, "${viewModel::class.java.name} received ViewModel#onCleared() callback"
                )
            }
        }
    }

    companion object {
        fun install(storeOwner: ViewModelStoreOwner, objectWatcher: ObjectWatcher, configProvider: () -> Config) {
            val provider = ViewModelProvider(storeOwner, object : Factory {
              @Suppress("UNCHECKED_CAST")
              override fun  create(modelClass: Class): T =
                      ViewModelClearedWatcher(storeOwner, objectWatcher, configProvider) as T
            })
            provider.get(ViewModelClearedWatcher::class.java)
        }
    }
}

七、检测到内存泄露后的流程

我们不可能在 Activity 刚被回调了 onDestroy 方法就马上来判断 ReferenceQueue 中是否有值,因为 JVM 的 GC 时机是不确定的,Activity 对象可能不会那么快就被回收,所以需要延迟一段时间后再来检测。而即使延迟检测了,也可能会存在应用没有发生内存泄露只是系统还未执行 GC 的情况,所以就需要去主动触发 GC,经过几轮检测后才可以确定当前应用是否的确发生了内存泄露

这里就来看下具体的检测流程

ObjectWatcher 对象包含了一个 Executor 参数:checkRetainedExecutor。检测操作的触发时机就取决于向 checkRetainedExecutor 提交的任务在什么时候会被执行

class ObjectWatcher constructor(private val clock: Clock, private val checkRetainedExecutor: Executor,
        /**
         * Calls to [watch] will be ignored when [isEnabled] returns false
         */
        private val isEnabled: () -> Boolean = { true }
) {

    ···

    /**
     * Watches the provided [watchedObject].
     *
     * @param description Describes why the object is watched.
     */
    @Synchronized
    fun watch(
            watchedObject: Any,
            description: String
    ) {
        if (!isEnabled()) {
            return
        }
        removeWeaklyReachableObjects()
        val key = UUID.randomUUID()
                .toString()
        val watchUptimeMillis = clock.uptimeMillis()
        val reference =
                KeyedWeakReference(watchedObject, key, description, watchUptimeMillis, queue)
        SharkLog.d {
            "Watching " +
                    (if (watchedObject is Class<*>) watchedObject.toString() else "instance of ${watchedObject.javaClass.name}") +
                    (if (description.isNotEmpty()) " ($description)" else "") +
                    " with key $key"
        }
        watchedObjects[key] = reference
        //重点
        checkRetainedExecutor.execute {
            moveToRetained(key)
        }
    }
    
    //判断 key 关联的对象是否已经泄露
    //是的话则将更新其 retainedUptimeMillis 值,以此来标记其发生了泄露
    @Synchronized
    private fun moveToRetained(key: String) {
        removeWeaklyReachableObjects()
        val retainedRef = watchedObjects[key]
        if (retainedRef != null) {
            retainedRef.retainedUptimeMillis = clock.uptimeMillis()
            //重点,向外发出可能有内存泄露的通知
            onObjectRetainedListeners.forEach { it.onObjectRetained() }
        }
    }

    ···
    
}

ObjectWatcher 对象又是在 InternalAppWatcher 里初始化的,checkRetainedExecutor 在收到任务后会通过 Handler 来延时五秒执行

internal object InternalAppWatcher {

  ···   
    
  private val mainHandler by lazy {
    Handler(Looper.getMainLooper())
  }

  private val checkRetainedExecutor = Executor {
    mainHandler.postDelayed(it, AppWatcher.config.watchDurationMillis)
  }
  
  val objectWatcher = ObjectWatcher(
      clock = clock,
      checkRetainedExecutor = checkRetainedExecutor,
      isEnabled = { true }
  )

  ···

}

ObjectWatchermoveToRetained 方法又会通过 onObjectRetained 向外发出通知:当前可能发生了内存泄露InternalLeakCanary 会收到这个通知,然后交由 HeapDumpTrigger 来进行检测

internal object InternalLeakCanary : (Application) -> Unit, OnObjectRetainedListener {
   
    private lateinit var heapDumpTrigger: HeapDumpTrigger
    
    override fun onObjectRetained() = scheduleRetainedObjectCheck()

    fun scheduleRetainedObjectCheck() {
        if (this::heapDumpTrigger.isInitialized) {
            heapDumpTrigger.scheduleRetainedObjectCheck()
        }
    }
    
    ···
    
}

当 LeakCanary 判定当前真的存在内存泄露时,就会进行 DumpHeap,找到泄露对象的引用链,而这个操作是比较费时费内存的,可能会直接导致应用页面无响应,所以 LeakCanary 进行 DumpHeap 前会有许多前置检查操作和前置条件,就是为了尽量减少 DumpHeap 次数以及在 DumpHeap 时尽量减少对开发人员的干扰

heapDumpTriggerscheduleRetainedObjectCheck() 方法的主要逻辑是:

  1. 获取当前还未回收的对象个数 retainedKeysCount。如果个数大于 0,则先主动触发 GC,尽量尝试回收对象,避免误判,然后执行第二步;如果个数为 0,那么流程就结束了
  2. GC 过后再次更新 retainedKeysCount 值,如果对象都被回收了(即 retainedKeysCount 值为 0),那么流程就结束了,否则就执行第三步
  3. 如果 retainedKeysCount 小于阈值 5,且当前“应用处于前台”或者是“应用处于后台但退到后台的时间还未超出五秒”,那么就启动一个定时任务,在二十秒后重新执行第一步,否则执行第四步
  4. 如果上一次 DumpHeap 离现在不足一分钟,那么就启动一个定时任务,满一分钟后重新执行第一步,否则执行第五步
  5. 此时各个条件都满足了,已经可以确定发生了内存泄漏,去执行 DumpHeap
internal class HeapDumpTrigger(
        private val application: Application,
        private val backgroundHandler: Handler,
        private val objectWatcher: ObjectWatcher,
        private val gcTrigger: GcTrigger,
        private val heapDumper: HeapDumper,
        private val configProvider: () -> Config
) {

    ···
    
    fun scheduleRetainedObjectCheck(
            delayMillis: Long = 0L
    ) {
        val checkCurrentlyScheduledAt = checkScheduledAt
        if (checkCurrentlyScheduledAt > 0) {
            //如果当前已经在进行检测了,则直接返回
            return
        }
        checkScheduledAt = SystemClock.uptimeMillis() + delayMillis
        backgroundHandler.postDelayed({
          checkScheduledAt = 0
          checkRetainedObjects()
        }, delayMillis)
    }

    private fun checkRetainedObjects() {
        val iCanHasHeap = HeapDumpControl.iCanHasHeap()

        val config = configProvider()

        if (iCanHasHeap is Nope) {
            if (iCanHasHeap is NotifyingNope) {
                // Before notifying that we can't dump heap, let's check if we still have retained object.
                var retainedReferenceCount = objectWatcher.retainedObjectCount

                if (retainedReferenceCount > 0) {
                    gcTrigger.runGc()
                    retainedReferenceCount = objectWatcher.retainedObjectCount
                }

                val nopeReason = iCanHasHeap.reason()
                val wouldDump = !checkRetainedCount(
                        retainedReferenceCount, config.retainedVisibleThreshold, nopeReason
                )

                if (wouldDump) {
                    val uppercaseReason = nopeReason[0].toUpperCase() + nopeReason.substring(1)
                    onRetainInstanceListener.onEvent(DumpingDisabled(uppercaseReason))
                    showRetainedCountNotification(
                            objectCount = retainedReferenceCount,
                            contentText = uppercaseReason
                    )
                }
            } else {
                SharkLog.d {
                    application.getString(
                            R.string.leak_canary_heap_dump_disabled_text, iCanHasHeap.reason()
                    )
                }
            }
            return
        }

        //获取当前还未回收的对象个数
        var retainedReferenceCount = objectWatcher.retainedObjectCount

        if (retainedReferenceCount > 0) {
            //主动触发 GC,尽量尝试回收对象,避免误判
            gcTrigger.runGc()
            retainedReferenceCount = objectWatcher.retainedObjectCount
        }

        if (checkRetainedCount(retainedReferenceCount, config.retainedVisibleThreshold))
            return

        val now = SystemClock.uptimeMillis()
        val elapsedSinceLastDumpMillis = now - lastHeapDumpUptimeMillis

        //如果上一次 DumpHeap 离现在不足一分钟,那么就启动一个定时任务,满一分钟后再次检查
        if (elapsedSinceLastDumpMillis < WAIT_BETWEEN_HEAP_DUMPS_MILLIS) {
            onRetainInstanceListener.onEvent(DumpHappenedRecently)
            showRetainedCountNotification(
                    objectCount = retainedReferenceCount,
                    contentText = application.getString(R.string.leak_canary_notification_retained_dump_wait)
            )
            scheduleRetainedObjectCheck(
                    delayMillis = WAIT_BETWEEN_HEAP_DUMPS_MILLIS - elapsedSinceLastDumpMillis
            )
            return
        }

        dismissRetainedCountNotification()
        //各个条件都满足了,已经可以确定发生了内存泄漏,去执行 DumpiHeap
        dumpHeap(retainedReferenceCount, retry = true)
    }

    /**
     * 判断当前是否符合 DumpHeap 的条件,符合的话返回 false
     * @param retainedKeysCount 当前还未回收的对象个数
     * @param retainedVisibleThreshold 触发 DumpHeap 的阈值
     * 只有当 retainedKeysCount 大于等于 retainedVisibleThreshold 时才会触发 DumpHeap,默认值是 5
     * @param nopeReason
     */
    private fun checkRetainedCount(
            retainedKeysCount: Int,
            retainedVisibleThreshold: Int,
            nopeReason: String? = null
    ): Boolean {
        //用于标记本次检测相对上次,未回收的对象个数是否发生了变化
        val countChanged = lastDisplayedRetainedObjectCount != retainedKeysCount
        lastDisplayedRetainedObjectCount = retainedKeysCount
        if (retainedKeysCount == 0) {
            if (countChanged) {
                //如果 retainedKeysCount 为 0,且值相对上次检测减少了,则说明有对象被回收了
                SharkLog.d { "All retained objects have been garbage collected" }
                onRetainInstanceListener.onEvent(NoMoreObjects)
                showNoMoreRetainedObjectNotification()
            }
            return true
        }

        //应用是否还在前台
        val applicationVisible = applicationVisible
        val applicationInvisibleLessThanWatchPeriod = applicationInvisibleLessThanWatchPeriod

        ···

        if (retainedKeysCount < retainedVisibleThreshold) { //还未达到阈值
            if (applicationVisible || applicationInvisibleLessThanWatchPeriod) {
                if (countChanged) {
                    onRetainInstanceListener.onEvent(BelowThreshold(retainedKeysCount))
                }
                //在通知栏显示当前未回收的对象个数
                showRetainedCountNotification(
                        objectCount = retainedKeysCount,
                        contentText = application.getString(
                                R.string.leak_canary_notification_retained_visible, retainedVisibleThreshold
                        )
                )
                //retainedKeysCount 还未达到阈值,且当前“应用处于前台”或者是“应用处于后台但退到后台的时间还未超出五秒”
                //此时就启动一个定时任务,在二十秒后重新再检测一遍
                scheduleRetainedObjectCheck(
                        delayMillis = WAIT_FOR_OBJECT_THRESHOLD_MILLIS
                )
                return true
            }
        }
        return false
    }

   ···

}

更后面的流程就涉及具体的 DumpHeap 操作了,这里就不再展开了,因为我也不太懂,后续有机会再单独写一篇文章来介绍了~~

八、小提示

1、检测任意对象

除了 LeakCanary 默认支持的四种类型外,我们还可以主动检测任意对象。例如,可以检测 Service:

class MyService : Service {

  // ...

  override fun onDestroy() {
    super.onDestroy()
    AppWatcher.objectWatcher.watch(
      watchedObject = this,
      description = "MyService received Service#onDestroy() callback"
    )
  }
}

2、更改配置项

LeakCanary 提供的默认配置项大多数情况已经很适合我们在项目中直接使用了,而如果我们想要更改 LeakCanary 的默认配置项(例如不希望检测 FragmentView),可以在 Application 中进行更改:

class DebugExampleApplication : Application() {

  override fun onCreate() {
    super.onCreate()
    AppWatcher.config = AppWatcher.config.copy(watchFragmentViews = false)
  }
}

由于 LeakCanary 的引用方式是 debugImplementation,在 releas 环境下是引用不到 LeakCanary 的,所以为了避免在生成 release 包时需要主动来删除这行配置项,需要将 DebugExampleApplication 放到 src/debug/java 文件夹中

九、结尾

可以看出 Activity、Fragment、FragmentView、ViewModel 等四种类型的内存检测都是需要依靠 ObjectWatcher 来完成的,因为这四种类型本质上都是属于不同的对象。而 ObjectWatcher 需要依靠引用队列 ReferenceQueue 来实现,因此 LeakCanary 的基本实现基础就是来源于 Java 的原生特性

LeakCanary 的整体源码讲得也差不多了,后边就再来写一篇关于内存泄露的扩展阅读

你可能感兴趣的:(三方库源码笔记(5)- LeakCanary 源码详解)