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[SPARK-48370][CONNECT] Checkpoint and localCheckpoint in Scala Spark …
…Connect client ### What changes were proposed in this pull request? This PR adds `Dataset.checkpoint` and `Dataset.localCheckpoint` into Scala Spark Connect client. Python API was implemented at #46570 ### Why are the changes needed? For API parity. ### Does this PR introduce _any_ user-facing change? Yes, it adds `Dataset.checkpoint` and `Dataset.localCheckpoint` into Scala Spark Connect client. ### How was this patch tested? Unittests added. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #46683 from HyukjinKwon/SPARK-48370. Authored-by: Hyukjin Kwon <gurwls223@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
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...ctor/connect/client/jvm/src/main/scala/org/apache/spark/sql/internal/SessionCleaner.scala
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one or more | ||
| * contributor license agreements. See the NOTICE file distributed with | ||
| * this work for additional information regarding copyright ownership. | ||
| * The ASF licenses this file to You under the Apache License, Version 2.0 | ||
| * (the "License"); you may not use this file except in compliance with | ||
| * the License. You may obtain a copy of the License at | ||
| * | ||
| * http://www.apache.org/licenses/LICENSE-2.0 | ||
| * | ||
| * Unless required by applicable law or agreed to in writing, software | ||
| * distributed under the License is distributed on an "AS IS" BASIS, | ||
| * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | ||
| * See the License for the specific language governing permissions and | ||
| * limitations under the License. | ||
| */ | ||
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| package org.apache.spark.sql.internal | ||
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| import java.lang.ref.{ReferenceQueue, WeakReference} | ||
| import java.util.Collections | ||
| import java.util.concurrent.ConcurrentHashMap | ||
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| import org.apache.spark.connect.proto | ||
| import org.apache.spark.internal.Logging | ||
| import org.apache.spark.sql.SparkSession | ||
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| /** | ||
| * Classes that represent cleaning tasks. | ||
| */ | ||
| private sealed trait CleanupTask | ||
| private case class CleanupCachedRemoteRelation(dfID: String) extends CleanupTask | ||
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| /** | ||
| * 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) | ||
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| /** | ||
| * 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 { | ||
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| /** | ||
| * 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 | ||
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| /** | ||
| * 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) | ||
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| private val referenceQueue = new ReferenceQueue[AnyRef] | ||
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| private val cleaningThread = new Thread() { override def run(): Unit = keepCleaning() } | ||
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| @volatile private var started = false | ||
| @volatile private var stopped = false | ||
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| /** Start the cleaner. */ | ||
| def start(): Unit = { | ||
| cleaningThread.setDaemon(true) | ||
| cleaningThread.setName("Spark Connect Context Cleaner") | ||
| cleaningThread.start() | ||
| } | ||
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| /** | ||
| * 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() | ||
| } | ||
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| /** Register a CachedRemoteRelation for cleanup when it is garbage collected. */ | ||
| def registerCachedRemoteRelationForCleanup(relation: proto.CachedRemoteRelation): Unit = { | ||
| registerForCleanup(relation, CleanupCachedRemoteRelation(relation.getRelationId)) | ||
| } | ||
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| /** Register an object for cleanup. */ | ||
| private def registerForCleanup(objectForCleanup: AnyRef, task: CleanupTask): Unit = { | ||
| if (!started) { | ||
| // Lazily starts when the first cleanup is registered. | ||
| start() | ||
| started = true | ||
| } | ||
| referenceBuffer.add(new CleanupTaskWeakReference(task, objectForCleanup, referenceQueue)) | ||
| } | ||
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| /** Keep cleaning objects. */ | ||
| private def keepCleaning(): Unit = { | ||
| while (!stopped && !session.client.channel.isShutdown) { | ||
| try { | ||
| val reference = Option(referenceQueue.remove(refQueuePollTimeout)) | ||
| .map(_.asInstanceOf[CleanupTaskWeakReference]) | ||
| // Synchronize here to avoid being interrupted on stop() | ||
| synchronized { | ||
| reference.foreach { ref => | ||
| logDebug("Got cleaning task " + ref.task) | ||
| referenceBuffer.remove(ref) | ||
| ref.task match { | ||
| case CleanupCachedRemoteRelation(dfID) => | ||
| doCleanupCachedRemoteRelation(dfID) | ||
| } | ||
| } | ||
| } | ||
| } catch { | ||
| case e: Throwable => logError("Error in cleaning thread", e) | ||
| } | ||
| } | ||
| } | ||
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| /** Perform CleanupCachedRemoteRelation cleanup. */ | ||
| private[spark] def doCleanupCachedRemoteRelation(dfID: String): Unit = { | ||
| session.execute { | ||
| session.newCommand { builder => | ||
| builder.getRemoveCachedRemoteRelationCommandBuilder | ||
| .setRelation(proto.CachedRemoteRelation.newBuilder().setRelationId(dfID).build()) | ||
| } | ||
| } | ||
| } | ||
| } |
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