Review feedback

Author: sryza

yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala

@@ -17,15 +17,15 @@
 
 package org.apache.spark.deploy.yarn
 
-import com.google.common.util.concurrent.ThreadFactoryBuilder
-
 import java.util.concurrent._
 import java.util.concurrent.atomic.AtomicInteger
 import java.util.regex.Pattern
 
 import scala.collection.JavaConversions._
 import scala.collection.mutable.{ArrayBuffer, HashMap, HashSet}
 
+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.api.protocolrecords.AllocateResponse
@@ -53,7 +53,6 @@ object AllocationType extends Enumeration {
 // Refer to http://developer.yahoo.com/blogs/hadoop/posts/2011/03/mapreduce-nextgen-scheduler/ for
 // more info on how we are requesting for containers.
 
-
 /**
  * Acquires resources for executors from a ResourceManager and launches executors in new containers.
  */
@@ -505,8 +504,7 @@ private[yarn] class YarnAllocator(
     amClient.allocate(progressIndicator)
   }
 
-  private def createRackResourceRequests(
-      hostContainers: ArrayBuffer[ContainerRequest])
+  private def createRackResourceRequests(hostContainers: ArrayBuffer[ContainerRequest])
     : ArrayBuffer[ContainerRequest] = {
     // Generate modified racks and new set of hosts under it before issuing requests.
     val rackToCounts = new HashMap[String, Int]()
@@ -602,8 +600,7 @@ private[yarn] class YarnAllocator(
       requestType: AllocationType.AllocationType,
       resource: String,
       numExecutors: Int,
-      priority: Int)
-    : ArrayBuffer[ContainerRequest] = {
+      priority: Int): ArrayBuffer[ContainerRequest] = {
     // If hostname is specified, then we need at least two requests - node local and rack local.
     // There must be a third request, which is ANY. That will be specially handled.
     requestType match {

yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnRMClient.scala

@@ -19,6 +19,10 @@ package org.apache.spark.deploy.yarn
 
 import java.util.{List => JList}
 
+import scala.collection.JavaConversions._
+import scala.collection.{Map, Set}
+import scala.util.Try
+
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.yarn.api.ApplicationConstants
 import org.apache.hadoop.yarn.api.records._
@@ -32,10 +36,6 @@ import org.apache.spark.{Logging, SecurityManager, SparkConf}
 import org.apache.spark.scheduler.SplitInfo
 import org.apache.spark.util.Utils
 
-import scala.collection.JavaConversions._
-import scala.collection.{Map, Set}
-import scala.util.Try
-
 /**
  * Handles registering and unregistering the application with the YARN ResourceManager.
  */
@@ -120,7 +120,7 @@ private[spark] class YarnRMClient(args: ApplicationMasterArguments) extends Logg
   }
 
   /** Returns the maximum number of attempts to register the AM. */
-  def getMaxRegAttempts(conf: YarnConfiguration) =
+  def getMaxRegAttempts(conf: YarnConfiguration): Int =
     conf.getInt(YarnConfiguration.RM_AM_MAX_ATTEMPTS, YarnConfiguration.DEFAULT_RM_AM_MAX_ATTEMPTS)
 
 }