spark-service-contextcleaner.adoc

ContextCleaner — Spark Application Garbage Collector

ContextCleaner is a Spark service that is responsible for application-wide cleanup of shuffles, RDDs, broadcasts, accumulators and checkpointed RDDs that is aimed at reducing the memory requirements of long-running data-heavy Spark applications.

ContextCleaner runs on the driver. It is created and immediately started when SparkContext starts (and spark.cleaner.referenceTracking Spark property is enabled, which it is by default). It is stopped when SparkContext is stopped.

Table 1. ContextCleaner’s Internal Registries and Counters

Name	Description
referenceBuffer	Used when ???
referenceQueue	Used when ???
listeners	Used when ???

It uses a daemon Spark Context Cleaner thread that cleans RDD, shuffle, and broadcast states (using keepCleaning method).

ShuffleDependencies register themselves for cleanup.

Tip	Enable INFO or DEBUG logging level for org.apache.spark.ContextCleaner logger to see what happens in ContextCleaner. Add the following line to conf/log4j.properties: log4j.logger.org.apache.spark.ContextCleaner=DEBUG Refer to Logging.

doCleanupRDD Method

Caution

FIXME

keepCleaning Internal Method

keepCleaning(): Unit

keepCleaning runs indefinitely until ContextCleaner is stopped. It…​FIXME

You should see the following DEBUG message in the logs:

DEBUG Got cleaning task [task]

Note	keepCleaning is exclusively used in Spark Context Cleaner Cleaning Thread that is started once when ContextCleaner is started.

Spark Context Cleaner Cleaning Thread — cleaningThread Attribute

Caution

FIXME

The name of the daemon thread is Spark Context Cleaner.

$ jstack -l [sparkPID] | grep "Spark Context Cleaner"
"Spark Context Cleaner" #80 daemon prio=5 os_prio=31 tid=0x00007fc304677800 nid=0xa103 in Object.wait() [0x0000000120371000]

Note	cleaningThread is started as a daemon thread when ContextCleaner starts.

registerRDDCheckpointDataForCleanup Method

Caution

FIXME

registerBroadcastForCleanup Method

Caution

FIXME

registerRDDForCleanup Method

Caution

FIXME

registerAccumulatorForCleanup Method

Caution

FIXME

stop Method

Caution

FIXME

Creating ContextCleaner Instance

ContextCleaner takes a SparkContext.

ContextCleaner initializes the internal registries and counters.

Starting ContextCleaner — start Method

start(): Unit

start starts cleaning thread and an action to request the JVM garbage collector (using System.gc()) every spark.cleaner.periodicGC.interval interval.

Note	The action to request the JVM GC is scheduled on periodicGCService executor service.

periodicGCService Single-Thread Executor Service

periodicGCService is an internal single-thread executor service with the name context-cleaner-periodic-gc to request the JVM garbage collector.

Note	Requests for JVM GC are scheduled every spark.cleaner.periodicGC.interval interval. The periodic runs are started when ContextCleaner starts and stopped when ContextCleaner stops.

Registering ShuffleDependency for Cleanup — registerShuffleForCleanup Method

registerShuffleForCleanup(shuffleDependency: ShuffleDependency[_, _, _]): Unit

registerShuffleForCleanup registers a ShuffleDependency for cleanup.

Internally, registerShuffleForCleanup simply executes registerForCleanup for the input ShuffleDependency.

Note	registerShuffleForCleanup is exclusively used when ShuffleDependency is created.

Registering Object Reference For Cleanup — registerForCleanup Internal Method

registerForCleanup(objectForCleanup: AnyRef, task: CleanupTask): Unit

Internally, registerForCleanup adds the input objectForCleanup to referenceBuffer internal queue.

Note	Despite the widest-possible AnyRef type of the input objectForCleanup, the type is really CleanupTaskWeakReference which is a custom Java’s java.lang.ref.WeakReference.

Removing Shuffle Blocks From MapOutputTrackerMaster and BlockManagerMaster — doCleanupShuffle Method

doCleanupShuffle(shuffleId: Int, blocking: Boolean): Unit

doCleanupShuffle performs a shuffle cleanup which is to remove the shuffle from the current MapOutputTrackerMaster and BlockManagerMaster. doCleanupShuffle also notifies CleanerListeners.

Internally, when executed, you should see the following DEBUG message in the logs:

DEBUG Cleaning shuffle [id]

doCleanupShuffle unregisters the input shuffleId from MapOutputTrackerMaster.

Note	doCleanupShuffle uses SparkEnv to access the current MapOutputTracker.

doCleanupShuffle removes the shuffle blocks of the input shuffleId from BlockManagerMaster.

Note	doCleanupShuffle uses SparkEnv to access the current BlockManagerMaster.

doCleanupShuffle informs all registered CleanerListener listeners (from listeners internal queue) that the input shuffleId was cleaned.

In the end, you should see the following DEBUG message in the logs:

DEBUG Cleaned shuffle [id]

In case of any exception, you should see the following ERROR message in the logs and the exception itself.

ERROR Error cleaning shuffle [id]

Note	doCleanupShuffle is executed when ContextCleaner cleans a shuffle reference and (interestingly) while fitting a ALSModel (in Spark MLlib).

Settings

Table 2. Spark Properties

Spark Property	Default Value	Description
spark.cleaner.periodicGC.interval	30min	Controls how often to trigger a garbage collection.
spark.cleaner.referenceTracking	true	Controls whether a ContextCleaner should be created when a SparkContext initializes.
spark.cleaner.referenceTracking.blocking	true	Controls whether the cleaning thread should block on cleanup tasks (other than shuffle, which is controlled by spark.cleaner.referenceTracking.blocking.shuffle Spark property). It is true as a workaround to SPARK-3015 Removing broadcast in quick successions causes Akka timeout.
spark.cleaner.referenceTracking.blocking.shuffle	false	Controls whether the cleaning thread should block on shuffle cleanup tasks. It is false as a workaround to SPARK-3139 Akka timeouts from ContextCleaner when cleaning shuffles.
spark.cleaner.referenceTracking.cleanCheckpoints	false	Controls whether to clean checkpoint files if the reference is out of scope.