-
Notifications
You must be signed in to change notification settings - Fork 28.5k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
[SPARK-24386][SS] coalesce(1) aggregates in continuous processing
## What changes were proposed in this pull request? Provide a continuous processing implementation of coalesce(1), as well as allowing aggregates on top of it. The changes in ContinuousQueuedDataReader and such are to use split.index (the ID of the partition within the RDD currently being compute()d) rather than context.partitionId() (the partition ID of the scheduled task within the Spark job - that is, the post coalesce writer). In the absence of a narrow dependency, these values were previously always the same, so there was no need to distinguish. ## How was this patch tested? new unit test Author: Jose Torres <[email protected]> Closes #21560 from jose-torres/coalesce.
- Loading branch information
1 parent
2224861
commit f6e6899
Showing
13 changed files
with
310 additions
and
18 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
51 changes: 51 additions & 0 deletions
51
...in/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceExec.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,51 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
||
| package org.apache.spark.sql.execution.streaming.continuous | ||
|
|
||
| import java.util.UUID | ||
|
|
||
| import org.apache.spark.{HashPartitioner, SparkEnv} | ||
| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.expressions.{Attribute, UnsafeRow} | ||
| import org.apache.spark.sql.catalyst.plans.physical.{Partitioning, SinglePartition} | ||
| import org.apache.spark.sql.execution.SparkPlan | ||
| import org.apache.spark.sql.execution.streaming.continuous.shuffle.{ContinuousShuffleReadPartition, ContinuousShuffleReadRDD} | ||
|
|
||
| /** | ||
| * Physical plan for coalescing a continuous processing plan. | ||
| * | ||
| * Currently, only coalesces to a single partition are supported. `numPartitions` must be 1. | ||
| */ | ||
| case class ContinuousCoalesceExec(numPartitions: Int, child: SparkPlan) extends SparkPlan { | ||
| override def output: Seq[Attribute] = child.output | ||
|
|
||
| override def children: Seq[SparkPlan] = child :: Nil | ||
|
|
||
| override def outputPartitioning: Partitioning = SinglePartition | ||
|
|
||
| override def doExecute(): RDD[InternalRow] = { | ||
| assert(numPartitions == 1) | ||
| new ContinuousCoalesceRDD( | ||
| sparkContext, | ||
| numPartitions, | ||
| conf.continuousStreamingExecutorQueueSize, | ||
| sparkContext.getLocalProperty(ContinuousExecution.EPOCH_INTERVAL_KEY).toLong, | ||
| child.execute()) | ||
| } | ||
| } |
136 changes: 136 additions & 0 deletions
136
...ain/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceRDD.scala
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,136 @@ | ||
| /* | ||
| * 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. | ||
| */ | ||
|
|
||
| package org.apache.spark.sql.execution.streaming.continuous | ||
|
|
||
| import java.util.UUID | ||
|
|
||
| import org.apache.spark._ | ||
| import org.apache.spark.rdd.RDD | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.expressions.UnsafeRow | ||
| import org.apache.spark.sql.execution.streaming.continuous.shuffle._ | ||
| import org.apache.spark.util.ThreadUtils | ||
|
|
||
| case class ContinuousCoalesceRDDPartition( | ||
| index: Int, | ||
| endpointName: String, | ||
| queueSize: Int, | ||
| numShuffleWriters: Int, | ||
| epochIntervalMs: Long) | ||
| extends Partition { | ||
| // Initialized only on the executor, and only once even as we call compute() multiple times. | ||
| lazy val (reader: ContinuousShuffleReader, endpoint) = { | ||
| val env = SparkEnv.get.rpcEnv | ||
| val receiver = new RPCContinuousShuffleReader( | ||
| queueSize, numShuffleWriters, epochIntervalMs, env) | ||
| val endpoint = env.setupEndpoint(endpointName, receiver) | ||
|
|
||
| TaskContext.get().addTaskCompletionListener { ctx => | ||
| env.stop(endpoint) | ||
| } | ||
| (receiver, endpoint) | ||
| } | ||
| // This flag will be flipped on the executors to indicate that the threads processing | ||
| // partitions of the write-side RDD have been started. These will run indefinitely | ||
| // asynchronously as epochs of the coalesce RDD complete on the read side. | ||
| private[continuous] var writersInitialized: Boolean = false | ||
| } | ||
|
|
||
| /** | ||
| * RDD for continuous coalescing. Asynchronously writes all partitions of `prev` into a local | ||
| * continuous shuffle, and then reads them in the task thread using `reader`. | ||
| */ | ||
| class ContinuousCoalesceRDD( | ||
| context: SparkContext, | ||
| numPartitions: Int, | ||
| readerQueueSize: Int, | ||
| epochIntervalMs: Long, | ||
| prev: RDD[InternalRow]) | ||
| extends RDD[InternalRow](context, Nil) { | ||
|
|
||
| // When we support more than 1 target partition, we'll need to figure out how to pass in the | ||
| // required partitioner. | ||
| private val outputPartitioner = new HashPartitioner(1) | ||
|
|
||
| private val readerEndpointNames = (0 until numPartitions).map { i => | ||
| s"ContinuousCoalesceRDD-part$i-${UUID.randomUUID()}" | ||
| } | ||
|
|
||
| override def getPartitions: Array[Partition] = { | ||
| (0 until numPartitions).map { partIndex => | ||
| ContinuousCoalesceRDDPartition( | ||
| partIndex, | ||
| readerEndpointNames(partIndex), | ||
| readerQueueSize, | ||
| prev.getNumPartitions, | ||
| epochIntervalMs) | ||
| }.toArray | ||
| } | ||
|
|
||
| private lazy val threadPool = ThreadUtils.newDaemonFixedThreadPool( | ||
| prev.getNumPartitions, | ||
| this.name) | ||
|
|
||
| override def compute(split: Partition, context: TaskContext): Iterator[InternalRow] = { | ||
| val part = split.asInstanceOf[ContinuousCoalesceRDDPartition] | ||
|
|
||
| if (!part.writersInitialized) { | ||
| val rpcEnv = SparkEnv.get.rpcEnv | ||
|
|
||
| // trigger lazy initialization | ||
| part.endpoint | ||
| val endpointRefs = readerEndpointNames.map { endpointName => | ||
| rpcEnv.setupEndpointRef(rpcEnv.address, endpointName) | ||
| } | ||
|
|
||
| val runnables = prev.partitions.map { prevSplit => | ||
| new Runnable() { | ||
| override def run(): Unit = { | ||
| TaskContext.setTaskContext(context) | ||
|
|
||
| val writer: ContinuousShuffleWriter = new RPCContinuousShuffleWriter( | ||
| prevSplit.index, outputPartitioner, endpointRefs.toArray) | ||
|
|
||
| EpochTracker.initializeCurrentEpoch( | ||
| context.getLocalProperty(ContinuousExecution.START_EPOCH_KEY).toLong) | ||
| while (!context.isInterrupted() && !context.isCompleted()) { | ||
| writer.write(prev.compute(prevSplit, context).asInstanceOf[Iterator[UnsafeRow]]) | ||
| // Note that current epoch is a non-inheritable thread local, so each writer thread | ||
| // can properly increment its own epoch without affecting the main task thread. | ||
| EpochTracker.incrementCurrentEpoch() | ||
| } | ||
| } | ||
| } | ||
| } | ||
|
|
||
| context.addTaskCompletionListener { ctx => | ||
| threadPool.shutdownNow() | ||
| } | ||
|
|
||
| part.writersInitialized = true | ||
|
|
||
| runnables.foreach(threadPool.execute) | ||
| } | ||
|
|
||
| part.reader.read() | ||
| } | ||
|
|
||
| override def clearDependencies(): Unit = { | ||
| throw new IllegalStateException("Continuous RDDs cannot be checkpointed") | ||
| } | ||
| } |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Oops, something went wrong.