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[Spark] Propagate thread locals to Delta thread pools
* The default thread pool executor in Apache Spark does not forward thread locals to threads spawned in a thread pool. * This can cause issues if the threads depend on the thread locals. * To fix this, we introduce a wrapper class around the thread pool executor that forwards thread locals. Closes delta-io#2154 GitOrigin-RevId: 9e9423e4b041232457ffaab18f5f96490bb45b88
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118 changes: 118 additions & 0 deletions
118
...rg/apache/spark/sql/delta/util/threads/SparkThreadLocalForwardingThreadPoolExecutor.scala
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * Copyright (2021) The Delta Lake Project Authors. | ||
| * | ||
| * Licensed 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.delta.util.threads | ||
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| import java.util.Properties | ||
| import java.util.concurrent._ | ||
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| import scala.collection.JavaConverters._ | ||
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| import org.apache.spark.{SparkContext, TaskContext} | ||
| import org.apache.spark.internal.Logging | ||
| import org.apache.spark.util.{Utils => SparkUtils} | ||
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| /** | ||
| * Implementation of ThreadPoolExecutor that captures the Spark ThreadLocals present at submit time | ||
| * and inserts them into the thread before executing the provided runnable. | ||
| */ | ||
| class SparkThreadLocalForwardingThreadPoolExecutor( | ||
| corePoolSize: Int, | ||
| maximumPoolSize: Int, | ||
| keepAliveTime: Long, | ||
| unit: TimeUnit, | ||
| workQueue: BlockingQueue[Runnable], | ||
| threadFactory: ThreadFactory, | ||
| rejectedExecutionHandler: RejectedExecutionHandler = new ThreadPoolExecutor.AbortPolicy) | ||
| extends ThreadPoolExecutor( | ||
| corePoolSize, maximumPoolSize, keepAliveTime, | ||
| unit, workQueue, threadFactory, rejectedExecutionHandler) { | ||
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| override def execute(command: Runnable): Unit = | ||
| super.execute(new SparkThreadLocalCapturingRunnable(command)) | ||
| } | ||
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| trait SparkThreadLocalCapturingHelper extends Logging { | ||
| // At the time of creating this instance we capture the task context and command context. | ||
| val capturedTaskContext = TaskContext.get() | ||
| val sparkContext = SparkContext.getActive | ||
| // Capture an immutable threadsafe snapshot of the current local properties | ||
| val capturedProperties = sparkContext | ||
| .map(sc => CapturedSparkThreadLocals.toValuesArray( | ||
| SparkUtils.cloneProperties(sc.getLocalProperties))) | ||
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| def runWithCaptured[T](body: => T): T = { | ||
| // Save the previous contexts, overwrite them with the captured contexts, and then restore the | ||
| // previous when execution completes. | ||
| // This has the unfortunate side effect of writing nulls to these thread locals if they were | ||
| // empty beforehand. | ||
| val previousTaskContext = TaskContext.get() | ||
| val previousProperties = sparkContext.map(_.getLocalProperties) | ||
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| TaskContext.setTaskContext(capturedTaskContext) | ||
| for { | ||
| p <- capturedProperties | ||
| sc <- sparkContext | ||
| } { | ||
| sc.setLocalProperties(CapturedSparkThreadLocals.toProperties(p)) | ||
| } | ||
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| try { | ||
| body | ||
| } catch { | ||
| case t: Throwable => | ||
| logError(s"Exception in thread ${Thread.currentThread().getName}", t) | ||
| throw t | ||
| } finally { | ||
| TaskContext.setTaskContext(previousTaskContext) | ||
| for { | ||
| p <- previousProperties | ||
| sc <- sparkContext | ||
| } { | ||
| sc.setLocalProperties(p) | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| class CapturedSparkThreadLocals extends SparkThreadLocalCapturingHelper | ||
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| object CapturedSparkThreadLocals { | ||
| def apply(): CapturedSparkThreadLocals = { | ||
| new CapturedSparkThreadLocals() | ||
| } | ||
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| def toProperties(props: Array[(String, String)]): Properties = { | ||
| val resultProps = new Properties() | ||
| for ((key, value) <- props) { | ||
| resultProps.put(key, value) | ||
| } | ||
| resultProps | ||
| } | ||
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| def toValuesArray(props: Properties): Array[(String, String)] = { | ||
| props.asScala.toArray | ||
| } | ||
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| } | ||
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| class SparkThreadLocalCapturingRunnable(runnable: Runnable) | ||
| extends Runnable with SparkThreadLocalCapturingHelper { | ||
| override def run(): Unit = { | ||
| runWithCaptured(runnable.run()) | ||
| } | ||
| } |
69 changes: 69 additions & 0 deletions
69
spark/src/test/scala/org/apache/spark/sql/delta/util/threads/DeltaThreadPoolSuite.scala
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,69 @@ | ||
| /* | ||
| * Copyright (2021) The Delta Lake Project Authors. | ||
| * | ||
| * Licensed 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.delta.util.threads | ||
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| import java.util.Properties | ||
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| import org.apache.spark.{SparkFunSuite, TaskContext, TaskContextImpl} | ||
| import org.apache.spark.sql.test.SharedSparkSession | ||
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| class DeltaThreadPoolSuite extends SparkFunSuite with SharedSparkSession { | ||
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| val threadPool: DeltaThreadPool = DeltaThreadPool("test", 1) | ||
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| def makeTaskContext(id: Int): TaskContext = { | ||
| new TaskContextImpl(id, 0, 0, 0, attemptNumber = 45613, 0, null, new Properties(), null) | ||
| } | ||
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| def testForwarding(testName: String, id: Int)(f: => Unit): Unit = { | ||
| test(testName) { | ||
| val prevTaskContext = TaskContext.get() | ||
| TaskContext.setTaskContext(makeTaskContext(id)) | ||
| sparkContext.setLocalProperty("test", id.toString) | ||
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| try { | ||
| f | ||
| } finally { | ||
| TaskContext.setTaskContext(prevTaskContext) | ||
| } | ||
| } | ||
| } | ||
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| def assertTaskAndProperties(id: Int): Unit = { | ||
| assert(TaskContext.get() !== null) | ||
| assert(TaskContext.get().stageId() === id) | ||
| assert(sparkContext.getLocalProperty("test") === id.toString) | ||
| } | ||
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| testForwarding("parallelMap captures TaskContext", id = 0) { | ||
| threadPool.parallelMap(spark, 0 until 1) { _ => | ||
| assertTaskAndProperties(id = 0) | ||
| } | ||
| } | ||
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| testForwarding("submit captures TaskContext and local properties", id = 1) { | ||
| threadPool.submit(spark) { | ||
| assertTaskAndProperties(id = 1) | ||
| } | ||
| } | ||
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| testForwarding("submitNonFateSharing captures TaskContext and local properties", id = 2) { | ||
| threadPool.submitNonFateSharing { _ => | ||
| assertTaskAndProperties(id = 2) | ||
| } | ||
| } | ||
| } |
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