LuciferYang commented on code in PR #46726:
URL: https://github.com/apache/spark/pull/46726#discussion_r1612670412
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connector/connect/client/jvm/src/main/scala/org/apache/spark/sql/internal/SessionCleaner.scala:
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@@ -17,130 +17,33 @@
package org.apache.spark.sql.internal
-import java.lang.ref.{ReferenceQueue, WeakReference}
-import java.util.Collections
-import java.util.concurrent.ConcurrentHashMap
+import java.lang.ref.Cleaner
import org.apache.spark.connect.proto
import org.apache.spark.internal.Logging
import org.apache.spark.sql.SparkSession
-/**
- * Classes that represent cleaning tasks.
- */
-private sealed trait CleanupTask
-private case class CleanupCachedRemoteRelation(dfID: String) extends
CleanupTask
-
-/**
- * A WeakReference associated with a CleanupTask.
- *
- * When the referent object becomes only weakly reachable, the corresponding
- * CleanupTaskWeakReference is automatically added to the given reference
queue.
- */
-private class CleanupTaskWeakReference(
- val task: CleanupTask,
- referent: AnyRef,
- referenceQueue: ReferenceQueue[AnyRef])
- extends WeakReference(referent, referenceQueue)
-
-/**
- * An asynchronous cleaner for objects.
- *
- * This maintains a weak reference for each CashRemoteRelation, etc. of
interest, to be processed
- * when the associated object goes out of scope of the application. Actual
cleanup is performed in
- * a separate daemon thread.
- */
private[sql] class SessionCleaner(session: SparkSession) extends Logging {
-
- /**
- * How often (seconds) to trigger a garbage collection in this JVM. This
context cleaner
- * triggers cleanups only when weak references are garbage collected. In
long-running
- * applications with large driver JVMs, where there is little memory
pressure on the driver,
- * this may happen very occasionally or not at all. Not cleaning at all may
lead to executors
- * running out of disk space after a while.
- */
- private val refQueuePollTimeout: Long = 100
-
- /**
- * A buffer to ensure that `CleanupTaskWeakReference`s are not garbage
collected as long as they
- * have not been handled by the reference queue.
- */
- private val referenceBuffer =
- Collections.newSetFromMap[CleanupTaskWeakReference](new ConcurrentHashMap)
-
- private val referenceQueue = new ReferenceQueue[AnyRef]
-
- private val cleaningThread = new Thread() { override def run(): Unit =
keepCleaning() }
-
- @volatile private var started = false
- @volatile private var stopped = false
-
- /** Start the cleaner. */
- def start(): Unit = {
- cleaningThread.setDaemon(true)
- cleaningThread.setName("Spark Connect Context Cleaner")
- cleaningThread.start()
- }
-
- /**
- * Stop the cleaning thread and wait until the thread has finished running
its current task.
- */
- def stop(): Unit = {
- stopped = true
- // Interrupt the cleaning thread, but wait until the current task has
finished before
- // doing so. This guards against the race condition where a cleaning
thread may
- // potentially clean similarly named variables created by a different
SparkSession.
- synchronized {
- cleaningThread.interrupt()
- }
- cleaningThread.join()
- }
+ private val cleaner = Cleaner.create()
Review Comment:
It seems that the lifecycle of `SessionCleaner` is the same as
`SparkSession`, so when the client holds multiple `SparkSession`s, multiple
instances of `java.lang.ref.Cleaner` will be created. If `cleaner` is defined
in the companion object of `SessionCleaner`, it can allow multiple
`SessionCleaner` to share one `java.lang.ref.Cleaner` instance . Can this meet
the requirements?
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