3.11 ContextCleaner的创建与启动
ContextCleaner用于清理那些超出应用范围的RDD、ShuffleDependency和Broadcast对象。由于配置属性spark.cleaner.referenceTracking默认是true，所以会构造并启动ContextCleaner，代码如下。
private[spark] val cleaner: Option[ContextCleaner] = {
if (conf.getBoolean("spark.cleaner.referenceTracking", true)) {
Some(new ContextCleaner(this))
} else {
None
}
}
cleaner.foreach(_.start())
ContextCleaner的组成如下：
referenceQueue：缓存顶级的AnyRef引用；
referenceBuffer：缓存AnyRef的虚引用；
listeners：缓存清理工作的监听器数组；
cleaningThread：用于具体清理工作的线程。
ContextCleaner的工作原理和listenerBus一样，也采用监听器模式，由线程来处理，此线程实际只是调用keepCleaning方法。keepCleaning的实现见代码清单3-48。
代码清单3-48 keep Cleaning的实现
private def keepCleaning(): Unit = Utils.logUncaughtExceptions {
while (!stopped) {
try {
val reference = Option(referenceQueue.remove(ContextCleaner.REF_QUEUE_POLL_TIMEOUT))
.map(_.asInstanceOf[CleanupTaskWeakReference])
// Synchronize here to avoid being interrupted on stop()
synchronized {
reference.map(_.task).foreach { task =>
logDebug("Got cleaning task " + task)
referenceBuffer -= reference.get
task match {
case CleanRDD(rddId) =>
doCleanupRDD(rddId, blocking = blockOnCleanupTasks)
case CleanShuffle(shuffleId) =>
doCleanupShuffle(shuffleId, blocking = blockOnShuffleCleanupTasks)
case CleanBroadcast(broadcastId) =>
doCleanupBroadcast(broadcastId, blocking = blockOnCleanupTasks)
}
}
}
} catch {
case ie: InterruptedException if stopped => // ignore
case e: Exception => logError("Error in cleaning thread", e)
}
}
}
