diff --git a/core/src/main/scala/org/apache/spark/SparkContext.scala b/core/src/main/scala/org/apache/spark/SparkContext.scala
index a47136ea36..f377f13d30 100644
--- a/core/src/main/scala/org/apache/spark/SparkContext.scala
+++ b/core/src/main/scala/org/apache/spark/SparkContext.scala
@@ -2798,7 +2798,7 @@ object SparkContext extends Logging {
         defaultProf.maxTasksPerExecutor(sc.conf) < cpuSlots) {
         throw new IllegalArgumentException("The number of slots on an executor has to be " +
           "limited by the number of cores, otherwise you waste resources and " +
-          "dynamic allocation doesn't work properly. Your configuration has " +
+          "some scheduling doesn't work properly. Your configuration has " +
           s"core/task cpu slots = ${cpuSlots} and " +
           s"${limitingResource} = " +
           s"${defaultProf.maxTasksPerExecutor(sc.conf)}. Please adjust your configuration " +
diff --git a/core/src/main/scala/org/apache/spark/resource/ResourceProfile.scala b/core/src/main/scala/org/apache/spark/resource/ResourceProfile.scala
index 2608ab9fc0..5b2476c18c 100644
--- a/core/src/main/scala/org/apache/spark/resource/ResourceProfile.scala
+++ b/core/src/main/scala/org/apache/spark/resource/ResourceProfile.scala
@@ -168,7 +168,7 @@ class ResourceProfile(
             // limiting resource because the scheduler code uses that for slots
             throw new IllegalArgumentException("The number of slots on an executor has to be " +
               "limited by the number of cores, otherwise you waste resources and " +
-              "dynamic allocation doesn't work properly. Your configuration has " +
+              "some scheduling doesn't work properly. Your configuration has " +
               s"core/task cpu slots = ${taskLimit} and " +
               s"${execReq.resourceName} = ${numTasks}. " +
               "Please adjust your configuration so that all resources require same number " +
@@ -183,12 +183,11 @@ class ResourceProfile(
           "no corresponding task resource request was specified.")
       }
     }
-    if(!shouldCheckExecCores && Utils.isDynamicAllocationEnabled(sparkConf)) {
+    if(!shouldCheckExecCores && execResourceToCheck.nonEmpty) {
       // if we can't rely on the executor cores config throw a warning for user
       logWarning("Please ensure that the number of slots available on your " +
         "executors is limited by the number of cores to task cpus and not another " +
-        "custom resource. If cores is not the limiting resource then dynamic " +
-        "allocation will not work properly!")
+        "custom resource.")
     }
     if (taskResourcesToCheck.nonEmpty) {
       throw new SparkException("No executor resource configs were not specified for the " +