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[SPARK-12101][CORE] Fix thread pools that cannot cache tasks in Worker and AppClient

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`SynchronousQueue` cannot cache any task. This issue is similar to #9978. It's an easy fix. Just use the fixed `ThreadUtils.newDaemonCachedThreadPool`.

Author: Shixiong Zhu <shixiong@databricks.com>

Closes #10108 from zsxwing/fix-threadpool.
This commit is contained in:
Shixiong Zhu 2015-12-03 11:06:25 -08:00
parent 7bc9e1db2c
commit 649be4fa45
3 changed files with 12 additions and 22 deletions
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10
core/src/main/scala/org/apache/spark/deploy/client/AppClient.scala
View file

@ -68,12 +68,10 @@ private[spark] class AppClient(
// A thread pool for registering with masters. Because registering with a master is a blocking
// action, this thread pool must be able to create "masterRpcAddresses.size" threads at the same
// time so that we can register with all masters.
private val registerMasterThreadPool = new ThreadPoolExecutor(
0,
masterRpcAddresses.length, // Make sure we can register with all masters at the same time
60L, TimeUnit.SECONDS,
new SynchronousQueue[Runnable](),
ThreadUtils.namedThreadFactory("appclient-register-master-threadpool"))
private val registerMasterThreadPool = ThreadUtils.newDaemonCachedThreadPool(
"appclient-register-master-threadpool",
masterRpcAddresses.length // Make sure we can register with all masters at the same time
)
// A scheduled executor for scheduling the registration actions
private val registrationRetryThread =

10
core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
View file

@ -146,12 +146,10 @@ private[deploy] class Worker(
// A thread pool for registering with masters. Because registering with a master is a blocking
// action, this thread pool must be able to create "masterRpcAddresses.size" threads at the same
// time so that we can register with all masters.
private val registerMasterThreadPool = new ThreadPoolExecutor(
0,
masterRpcAddresses.size, // Make sure we can register with all masters at the same time
60L, TimeUnit.SECONDS,
new SynchronousQueue[Runnable](),
ThreadUtils.namedThreadFactory("worker-register-master-threadpool"))
private val registerMasterThreadPool = ThreadUtils.newDaemonCachedThreadPool(
"worker-register-master-threadpool",
masterRpcAddresses.size // Make sure we can register with all masters at the same time
)
var coresUsed = 0
var memoryUsed = 0

14
yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
View file

@ -25,8 +25,6 @@ import scala.collection.mutable
import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet}
import scala.collection.JavaConverters._
import com.google.common.util.concurrent.ThreadFactoryBuilder
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.yarn.api.records._
import org.apache.hadoop.yarn.client.api.AMRMClient
@ -40,7 +38,7 @@ import org.apache.spark.deploy.yarn.YarnSparkHadoopUtil._
import org.apache.spark.rpc.{RpcCallContext, RpcEndpointRef}
import org.apache.spark.scheduler.{ExecutorExited, ExecutorLossReason}
import org.apache.spark.scheduler.cluster.CoarseGrainedClusterMessages.RemoveExecutor
import org.apache.spark.util.Utils
import org.apache.spark.util.ThreadUtils
/**
* YarnAllocator is charged with requesting containers from the YARN ResourceManager and deciding
@ -117,13 +115,9 @@ private[yarn] class YarnAllocator(
// Resource capability requested for each executors
private[yarn] val resource = Resource.newInstance(executorMemory + memoryOverhead, executorCores)
private val launcherPool = new ThreadPoolExecutor(
// max pool size of Integer.MAX_VALUE is ignored because we use an unbounded queue
sparkConf.getInt("spark.yarn.containerLauncherMaxThreads", 25), Integer.MAX_VALUE,
1, TimeUnit.MINUTES,
new LinkedBlockingQueue[Runnable](),
new ThreadFactoryBuilder().setNameFormat("ContainerLauncher #%d").setDaemon(true).build())
launcherPool.allowCoreThreadTimeOut(true)
private val launcherPool = ThreadUtils.newDaemonCachedThreadPool(
"ContainerLauncher",
sparkConf.getInt("spark.yarn.containerLauncherMaxThreads", 25))
// For testing
private val launchContainers = sparkConf.getBoolean("spark.yarn.launchContainers", true)