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feat: Add CometBroadcastExchangeExec to support broadcasting the resu…
…lt of Comet native operator (#80)
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spark/src/main/scala/org/apache/spark/sql/comet/CometBroadcastExchangeExec.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.comet | ||
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| import java.util.UUID | ||
| import java.util.concurrent.{Future, TimeoutException, TimeUnit} | ||
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| import scala.concurrent.{ExecutionContext, Promise} | ||
| import scala.concurrent.duration.NANOSECONDS | ||
| import scala.util.control.NonFatal | ||
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| import org.apache.spark.{broadcast, Partition, SparkContext, TaskContext} | ||
| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.plans.logical.Statistics | ||
| import org.apache.spark.sql.errors.QueryExecutionErrors | ||
| import org.apache.spark.sql.execution.{ColumnarToRowExec, FileSourceScanExec, SparkPlan, SQLExecution} | ||
| import org.apache.spark.sql.execution.exchange.BroadcastExchangeLike | ||
| import org.apache.spark.sql.execution.metric.{SQLMetric, SQLMetrics} | ||
| import org.apache.spark.sql.internal.{SQLConf, StaticSQLConf} | ||
| import org.apache.spark.sql.vectorized.ColumnarBatch | ||
| import org.apache.spark.util.{SparkFatalException, ThreadUtils} | ||
| import org.apache.spark.util.io.ChunkedByteBuffer | ||
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| import com.google.common.base.Objects | ||
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| /** | ||
| * A [[CometBroadcastExchangeExec]] collects, transforms and finally broadcasts the result of a | ||
| * transformed SparkPlan. This is a copy of the [[BroadcastExchangeExec]] class with the necessary | ||
| * changes to support the Comet operator. | ||
| * | ||
| * [[CometBroadcastExchangeExec]] will be used in broadcast join operator. | ||
| * | ||
| * Note that this class cannot extend `CometExec` as usual similar to other Comet operators. As | ||
| * the trait `BroadcastExchangeLike` in Spark extends abstract class `Exchange`, it limits the | ||
| * flexibility to extend `CometExec` and `Exchange` at the same time. | ||
| */ | ||
| case class CometBroadcastExchangeExec(originalPlan: SparkPlan, child: SparkPlan) | ||
| extends BroadcastExchangeLike { | ||
| import CometBroadcastExchangeExec._ | ||
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| override val runId: UUID = UUID.randomUUID | ||
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| override lazy val metrics: Map[String, SQLMetric] = Map( | ||
| "dataSize" -> SQLMetrics.createSizeMetric(sparkContext, "data size"), | ||
| "numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows"), | ||
| "collectTime" -> SQLMetrics.createTimingMetric(sparkContext, "time to collect"), | ||
| "buildTime" -> SQLMetrics.createTimingMetric(sparkContext, "time to build"), | ||
| "broadcastTime" -> SQLMetrics.createTimingMetric(sparkContext, "time to broadcast")) | ||
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| override def doCanonicalize(): SparkPlan = { | ||
| CometBroadcastExchangeExec(originalPlan.canonicalized, child.canonicalized) | ||
| } | ||
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| override def runtimeStatistics: Statistics = { | ||
| val dataSize = metrics("dataSize").value | ||
| val rowCount = metrics("numOutputRows").value | ||
| Statistics(dataSize, Some(rowCount)) | ||
| } | ||
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| @transient | ||
| private lazy val promise = Promise[broadcast.Broadcast[Any]]() | ||
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| @transient | ||
| override lazy val completionFuture: scala.concurrent.Future[broadcast.Broadcast[Any]] = | ||
| promise.future | ||
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| @transient | ||
| private val timeout: Long = conf.broadcastTimeout | ||
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| @transient | ||
| private lazy val maxBroadcastRows = 512000000 | ||
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| @transient | ||
| override lazy val relationFuture: Future[broadcast.Broadcast[Any]] = { | ||
| SQLExecution.withThreadLocalCaptured[broadcast.Broadcast[Any]]( | ||
| session, | ||
| CometBroadcastExchangeExec.executionContext) { | ||
| try { | ||
| // Setup a job group here so later it may get cancelled by groupId if necessary. | ||
| sparkContext.setJobGroup( | ||
| runId.toString, | ||
| s"broadcast exchange (runId $runId)", | ||
| interruptOnCancel = true) | ||
| val beforeCollect = System.nanoTime() | ||
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| val countsAndBytes = child.asInstanceOf[CometExec].getByteArrayRdd().collect() | ||
| val numRows = countsAndBytes.map(_._1).sum | ||
| val input = countsAndBytes.iterator.map(countAndBytes => countAndBytes._2) | ||
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| longMetric("numOutputRows") += numRows | ||
| if (numRows >= maxBroadcastRows) { | ||
| throw QueryExecutionErrors.cannotBroadcastTableOverMaxTableRowsError( | ||
| maxBroadcastRows, | ||
| numRows) | ||
| } | ||
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| val beforeBuild = System.nanoTime() | ||
| longMetric("collectTime") += NANOSECONDS.toMillis(beforeBuild - beforeCollect) | ||
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| val batches = input.toArray | ||
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| val dataSize = batches.map(_.size).sum | ||
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| longMetric("dataSize") += dataSize | ||
| if (dataSize >= MAX_BROADCAST_TABLE_BYTES) { | ||
| throw QueryExecutionErrors.cannotBroadcastTableOverMaxTableBytesError( | ||
| MAX_BROADCAST_TABLE_BYTES, | ||
| dataSize) | ||
| } | ||
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| val beforeBroadcast = System.nanoTime() | ||
| longMetric("buildTime") += NANOSECONDS.toMillis(beforeBroadcast - beforeBuild) | ||
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| // SPARK-39983 - Broadcast the relation without caching the unserialized object. | ||
| val broadcasted = sparkContext | ||
| .broadcastInternal(batches, serializedOnly = true) | ||
| .asInstanceOf[broadcast.Broadcast[Any]] | ||
| longMetric("broadcastTime") += NANOSECONDS.toMillis(System.nanoTime() - beforeBroadcast) | ||
| val executionId = sparkContext.getLocalProperty(SQLExecution.EXECUTION_ID_KEY) | ||
| SQLMetrics.postDriverMetricUpdates(sparkContext, executionId, metrics.values.toSeq) | ||
| promise.trySuccess(broadcasted) | ||
| broadcasted | ||
| } catch { | ||
| // SPARK-24294: To bypass scala bug: https://github.com/scala/bug/issues/9554, we throw | ||
| // SparkFatalException, which is a subclass of Exception. ThreadUtils.awaitResult | ||
| // will catch this exception and re-throw the wrapped fatal throwable. | ||
| case oe: OutOfMemoryError => | ||
| val tables = child.collect { case f: FileSourceScanExec => f.tableIdentifier }.flatten | ||
| val ex = new SparkFatalException( | ||
| QueryExecutionErrors.notEnoughMemoryToBuildAndBroadcastTableError(oe, tables)) | ||
| promise.tryFailure(ex) | ||
| throw ex | ||
| case e if !NonFatal(e) => | ||
| val ex = new SparkFatalException(e) | ||
| promise.tryFailure(ex) | ||
| throw ex | ||
| case e: Throwable => | ||
| promise.tryFailure(e) | ||
| throw e | ||
| } | ||
| } | ||
| } | ||
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| override protected def doPrepare(): Unit = { | ||
| // Materialize the future. | ||
| relationFuture | ||
| } | ||
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| override protected def doExecute(): RDD[InternalRow] = { | ||
| throw QueryExecutionErrors.executeCodePathUnsupportedError("CometBroadcastExchangeExec") | ||
| } | ||
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| override def supportsColumnar: Boolean = true | ||
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| // This is basically for unit test only. | ||
| override def executeCollect(): Array[InternalRow] = | ||
| ColumnarToRowExec(this).executeCollect() | ||
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| // This is basically for unit test only, called by `executeCollect` indirectly. | ||
| override protected def doExecuteColumnar(): RDD[ColumnarBatch] = { | ||
| val broadcasted = executeBroadcast[Array[ChunkedByteBuffer]]() | ||
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| new CometBatchRDD(sparkContext, broadcasted.value.length, broadcasted) | ||
| } | ||
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| override protected[sql] def doExecuteBroadcast[T](): broadcast.Broadcast[T] = { | ||
| try { | ||
| relationFuture.get(timeout, TimeUnit.SECONDS).asInstanceOf[broadcast.Broadcast[T]] | ||
| } catch { | ||
| case ex: TimeoutException => | ||
| logError(s"Could not execute broadcast in $timeout secs.", ex) | ||
| if (!relationFuture.isDone) { | ||
| sparkContext.cancelJobGroup(runId.toString) | ||
| relationFuture.cancel(true) | ||
| } | ||
| throw QueryExecutionErrors.executeBroadcastTimeoutError(timeout, Some(ex)) | ||
| } | ||
| } | ||
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| override def equals(obj: Any): Boolean = { | ||
| obj match { | ||
| case other: CometBroadcastExchangeExec => | ||
| this.originalPlan == other.originalPlan && | ||
| this.output == other.output && this.child == other.child | ||
| case _ => | ||
| false | ||
| } | ||
| } | ||
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| override def hashCode(): Int = Objects.hashCode(output, child) | ||
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| override def stringArgs: Iterator[Any] = Iterator(output, child) | ||
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| override protected def withNewChildInternal(newChild: SparkPlan): CometBroadcastExchangeExec = | ||
| copy(child = newChild) | ||
| } | ||
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| object CometBroadcastExchangeExec { | ||
| val MAX_BROADCAST_TABLE_BYTES: Long = 8L << 30 | ||
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| private[comet] val executionContext = ExecutionContext.fromExecutorService( | ||
| ThreadUtils.newDaemonCachedThreadPool( | ||
| "comet-broadcast-exchange", | ||
| SQLConf.get.getConf(StaticSQLConf.BROADCAST_EXCHANGE_MAX_THREAD_THRESHOLD))) | ||
| } | ||
|
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| /** | ||
| * [[CometBatchRDD]] is a [[RDD]] of [[ColumnarBatch]]s that are broadcasted to the executors. It | ||
| * is only used by [[CometBroadcastExchangeExec]] to broadcast the result of a Comet operator. | ||
| * | ||
| * @param sc | ||
| * SparkContext | ||
| * @param numPartitions | ||
| * number of partitions | ||
| * @param value | ||
| * the broadcasted batches which are serialized into an array of [[ChunkedByteBuffer]]s | ||
| */ | ||
| class CometBatchRDD( | ||
| sc: SparkContext, | ||
| numPartitions: Int, | ||
| value: broadcast.Broadcast[Array[ChunkedByteBuffer]]) | ||
| extends RDD[ColumnarBatch](sc, Nil) { | ||
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| override def getPartitions: Array[Partition] = (0 until numPartitions).toArray.map { i => | ||
| new CometBatchPartition(i, value) | ||
| } | ||
|
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| override def compute(split: Partition, context: TaskContext): Iterator[ColumnarBatch] = { | ||
| val partition = split.asInstanceOf[CometBatchPartition] | ||
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| partition.value.value.flatMap(CometExec.decodeBatches(_)).toIterator | ||
| } | ||
| } | ||
|
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| class CometBatchPartition( | ||
| override val index: Int, | ||
| val value: broadcast.Broadcast[Array[ChunkedByteBuffer]]) | ||
| extends Partition {} |
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