diff --git a/docs/running-on-yarn.md b/docs/running-on-yarn.md
index 3bd62646bab060eba316406fa9a1c7a4983a31b1..fb8a043df33d0d0463bdea36caead97225ed43d6 100644
--- a/docs/running-on-yarn.md
+++ b/docs/running-on-yarn.md
@@ -133,7 +133,7 @@ See [Building Spark with Maven](building-with-maven.html) for instructions on ho
 
 # Important Notes
 
-- We do not requesting container resources based on the number of cores. Thus the numbers of cores given via command line arguments cannot be guaranteed.
+- Before Hadoop 2.2, YARN does not support cores in container resource requests. Thus, when running against an earlier version, the numbers of cores given via command line arguments cannot be guaranteed.
 - The local directories used for spark will be the local directories configured for YARN (Hadoop Yarn config yarn.nodemanager.local-dirs). If the user specifies spark.local.dir, it will be ignored.
 - The --files and --archives options support specifying file names with the # similar to Hadoop. For example you can specify: --files localtest.txt#appSees.txt and this will upload the file you have locally named localtest.txt into HDFS but this will be linked to by the name appSees.txt and your application should use the name as appSees.txt to reference it when running on YARN.
 - The --addJars option allows the SparkContext.addJar function to work if you are using it with local files. It does not need to be used if you are using it with HDFS, HTTP, HTTPS, or FTP files.
diff --git a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
index 738ff986d85a58152e4b874a698f380b2b645977..f53c13013f9cbfe255d69df9123ec9f44945b33b 100644
--- a/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
+++ b/yarn/stable/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocationHandler.scala
@@ -102,7 +102,8 @@ private[yarn] class YarnAllocationHandler(
   def getNumWorkersFailed: Int = numWorkersFailed.intValue
 
   def isResourceConstraintSatisfied(container: Container): Boolean = {
-    container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+    (container.getResource.getMemory >= (workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+      && container.getResource.getVirtualCores >= workerCores)
   }
 
   def releaseContainer(container: Container) {
@@ -532,15 +533,15 @@ private[yarn] class YarnAllocationHandler(
       priority: Int
     ): ArrayBuffer[ContainerRequest] = {
 
-    val memoryResource = Records.newRecord(classOf[Resource])
-    memoryResource.setMemory(workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD)
+    val memoryRequest = workerMemory + YarnAllocationHandler.MEMORY_OVERHEAD
+    val resource = Resource.newInstance(memoryRequest, workerCores)
 
     val prioritySetting = Records.newRecord(classOf[Priority])
     prioritySetting.setPriority(priority)
 
     val requests = new ArrayBuffer[ContainerRequest]()
     for (i <- 0 until numWorkers) {
-      requests += new ContainerRequest(memoryResource, hosts, racks, prioritySetting)
+      requests += new ContainerRequest(resource, hosts, racks, prioritySetting)
     }
     requests
   }