-
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-2711. Create a ShuffleMemoryManager to track memory for all spi…
…lling collections This tracks memory properly if there are multiple spilling collections in the same task (which was a problem before), and also implements an algorithm that lets each thread grow up to 1 / 2N of the memory pool (where N is the number of threads) before spilling, which avoids an inefficiency with small spills we had before (some threads would spill many times at 0-1 MB because the pool was allocated elsewhere). Author: Matei Zaharia <matei@databricks.com> Closes #1707 from mateiz/spark-2711 and squashes the following commits: debf75b [Matei Zaharia] Review comments 24f28f3 [Matei Zaharia] Small rename c8f3a8b [Matei Zaharia] Update ShuffleMemoryManager to be able to partially grant requests 315e3a5 [Matei Zaharia] Some review comments b810120 [Matei Zaharia] Create central manager to track memory for all spilling collections (cherry picked from commit 4fde28c) Signed-off-by: Matei Zaharia <matei@databricks.com>
- Loading branch information
Showing
6 changed files
with
450 additions
and
81 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
125 changes: 125 additions & 0 deletions
125
core/src/main/scala/org/apache/spark/shuffle/ShuffleMemoryManager.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 +1,125 @@ | ||
| /* | ||
| * 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.shuffle | ||
|
|
||
| import scala.collection.mutable | ||
|
|
||
| import org.apache.spark.{Logging, SparkException, SparkConf} | ||
|
|
||
| /** | ||
| * Allocates a pool of memory to task threads for use in shuffle operations. Each disk-spilling | ||
| * collection (ExternalAppendOnlyMap or ExternalSorter) used by these tasks can acquire memory | ||
| * from this pool and release it as it spills data out. When a task ends, all its memory will be | ||
| * released by the Executor. | ||
| * | ||
| * This class tries to ensure that each thread gets a reasonable share of memory, instead of some | ||
| * thread ramping up to a large amount first and then causing others to spill to disk repeatedly. | ||
| * If there are N threads, it ensures that each thread can acquire at least 1 / 2N of the memory | ||
| * before it has to spill, and at most 1 / N. Because N varies dynamically, we keep track of the | ||
| * set of active threads and redo the calculations of 1 / 2N and 1 / N in waiting threads whenever | ||
| * this set changes. This is all done by synchronizing access on "this" to mutate state and using | ||
| * wait() and notifyAll() to signal changes. | ||
| */ | ||
| private[spark] class ShuffleMemoryManager(maxMemory: Long) extends Logging { | ||
| private val threadMemory = new mutable.HashMap[Long, Long]() // threadId -> memory bytes | ||
|
|
||
| def this(conf: SparkConf) = this(ShuffleMemoryManager.getMaxMemory(conf)) | ||
|
|
||
| /** | ||
| * Try to acquire up to numBytes memory for the current thread, and return the number of bytes | ||
| * obtained, or 0 if none can be allocated. This call may block until there is enough free memory | ||
| * in some situations, to make sure each thread has a chance to ramp up to at least 1 / 2N of the | ||
| * total memory pool (where N is the # of active threads) before it is forced to spill. This can | ||
| * happen if the number of threads increases but an older thread had a lot of memory already. | ||
| */ | ||
| def tryToAcquire(numBytes: Long): Long = synchronized { | ||
| val threadId = Thread.currentThread().getId | ||
| assert(numBytes > 0, "invalid number of bytes requested: " + numBytes) | ||
|
|
||
| // Add this thread to the threadMemory map just so we can keep an accurate count of the number | ||
| // of active threads, to let other threads ramp down their memory in calls to tryToAcquire | ||
| if (!threadMemory.contains(threadId)) { | ||
| threadMemory(threadId) = 0L | ||
| notifyAll() // Will later cause waiting threads to wake up and check numThreads again | ||
| } | ||
|
|
||
| // Keep looping until we're either sure that we don't want to grant this request (because this | ||
| // thread would have more than 1 / numActiveThreads of the memory) or we have enough free | ||
| // memory to give it (we always let each thread get at least 1 / (2 * numActiveThreads)). | ||
| while (true) { | ||
| val numActiveThreads = threadMemory.keys.size | ||
| val curMem = threadMemory(threadId) | ||
| val freeMemory = maxMemory - threadMemory.values.sum | ||
|
|
||
| // How much we can grant this thread; don't let it grow to more than 1 / numActiveThreads | ||
| val maxToGrant = math.min(numBytes, (maxMemory / numActiveThreads) - curMem) | ||
|
|
||
| if (curMem < maxMemory / (2 * numActiveThreads)) { | ||
| // We want to let each thread get at least 1 / (2 * numActiveThreads) before blocking; | ||
| // if we can't give it this much now, wait for other threads to free up memory | ||
| // (this happens if older threads allocated lots of memory before N grew) | ||
| if (freeMemory >= math.min(maxToGrant, maxMemory / (2 * numActiveThreads) - curMem)) { | ||
| val toGrant = math.min(maxToGrant, freeMemory) | ||
| threadMemory(threadId) += toGrant | ||
| return toGrant | ||
| } else { | ||
| logInfo(s"Thread $threadId waiting for at least 1/2N of shuffle memory pool to be free") | ||
| wait() | ||
| } | ||
| } else { | ||
| // Only give it as much memory as is free, which might be none if it reached 1 / numThreads | ||
| val toGrant = math.min(maxToGrant, freeMemory) | ||
| threadMemory(threadId) += toGrant | ||
| return toGrant | ||
| } | ||
| } | ||
| 0L // Never reached | ||
| } | ||
|
|
||
| /** Release numBytes bytes for the current thread. */ | ||
| def release(numBytes: Long): Unit = synchronized { | ||
| val threadId = Thread.currentThread().getId | ||
| val curMem = threadMemory.getOrElse(threadId, 0L) | ||
| if (curMem < numBytes) { | ||
| throw new SparkException( | ||
| s"Internal error: release called on ${numBytes} bytes but thread only has ${curMem}") | ||
| } | ||
| threadMemory(threadId) -= numBytes | ||
| notifyAll() // Notify waiters who locked "this" in tryToAcquire that memory has been freed | ||
| } | ||
|
|
||
| /** Release all memory for the current thread and mark it as inactive (e.g. when a task ends). */ | ||
| def releaseMemoryForThisThread(): Unit = synchronized { | ||
| val threadId = Thread.currentThread().getId | ||
| threadMemory.remove(threadId) | ||
| notifyAll() // Notify waiters who locked "this" in tryToAcquire that memory has been freed | ||
| } | ||
| } | ||
|
|
||
| private object ShuffleMemoryManager { | ||
| /** | ||
| * Figure out the shuffle memory limit from a SparkConf. We currently have both a fraction | ||
| * of the memory pool and a safety factor since collections can sometimes grow bigger than | ||
| * the size we target before we estimate their sizes again. | ||
| */ | ||
| def getMaxMemory(conf: SparkConf): Long = { | ||
| val memoryFraction = conf.getDouble("spark.shuffle.memoryFraction", 0.2) | ||
| val safetyFraction = conf.getDouble("spark.shuffle.safetyFraction", 0.8) | ||
| (Runtime.getRuntime.maxMemory * memoryFraction * safetyFraction).toLong | ||
| } | ||
| } |
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.