diff --git a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
index 8b117650ab5b9..25db71ca49132 100644
--- a/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
+++ b/resource-managers/yarn/src/main/scala/org/apache/spark/deploy/yarn/YarnAllocator.scala
@@ -329,21 +329,21 @@ private[yarn] class YarnAllocator(
       // to request YARN containers with extra resources without Spark scheduling on
       // them, the user can specify resources via the <code>spark.yarn.executor.resource.</code>
       // config. Those configs are only used in the base default profile though and do
-      // not get propogated into any other custom ResourceProfiles. This is because
+      // not get propagated into any other custom ResourceProfiles. This is because
       // there would be no way to remove them if you wanted a stage to not have them.
       // This results in your default profile getting custom resources defined in
       // <code>spark.yarn.executor.resource.</code> plus spark defined resources of
       // GPU or FPGA. Spark converts GPU and FPGA resources into the YARN built in
       // types <code>yarn.io/gpu</code>) and <code>yarn.io/fpga</code>, but does not
       // know the mapping of any other resources. Any other Spark custom resources
-      // are not propogated to YARN for the default profile. So if you want Spark
+      // are not propagated to YARN for the default profile. So if you want Spark
       // to schedule based off a custom resource and have it requested from YARN, you
       // must specify it in both YARN (<code>spark.yarn.{driver/executor}.resource.</code>)
       // and Spark (<code>spark.{driver/executor}.resource.</code>) configs. Leave the Spark
       // config off if you only want YARN containers with the extra resources but Spark not to
       // schedule using them. Now for custom ResourceProfiles, it doesn't currently have a way
       // to only specify YARN resources without Spark scheduling off of them. This means for
-      // custom ResourceProfiles we propogate all the resources defined in the ResourceProfile
+      // custom ResourceProfiles we propagate all the resources defined in the ResourceProfile
       // to YARN. We still convert GPU and FPGA to the YARN build in types as well. This requires
       // that the name of any custom resources you specify match what they are defined as in YARN.
       val customResources = if (rp.id == DEFAULT_RESOURCE_PROFILE_ID) {