diff --git a/mllib-dal/src/main/scala/com/intel/oap/mllib/Utils.scala b/mllib-dal/src/main/scala/com/intel/oap/mllib/Utils.scala
index d3e3308e3..de1beaea8 100644
--- a/mllib-dal/src/main/scala/com/intel/oap/mllib/Utils.scala
+++ b/mllib-dal/src/main/scala/com/intel/oap/mllib/Utils.scala
@@ -28,18 +28,24 @@ object Utils {
 
   def isOAPEnabled(): Boolean = {
     val sc = SparkSession.active.sparkContext
-    return sc.getConf.getBoolean("spark.oap.mllib.enabled", true)
+    val dynamic = sc.getConf.getBoolean("spark.dynamicAllocation.enabled", false)
+    val isoap = sc.getConf.getBoolean("spark.oap.mllib.enabled", true)
+    if (isoap && dynamic) {
+      throw new Exception(
+        s"OAP MLlib does not support dynamic allocation, " +
+          s"spark.dynamicAllocation.enabled should be set to false")
+    }
+    isoap
   }
 
   def getOneCCLIPPort(data: RDD[_]): String = {
     val executorIPAddress = Utils.sparkFirstExecutorIP(data.sparkContext)
-    val kvsIP = data.sparkContext.getConf.get("spark.oap.mllib.oneccl.kvs.ip",
-      executorIPAddress)
+    val kvsIP = data.sparkContext.getConf.get("spark.oap.mllib.oneccl.kvs.ip", executorIPAddress)
     //  TODO: right now we use a configured port, will optimize auto port detection
     //  val kvsPortDetected = Utils.checkExecutorAvailPort(data, kvsIP)
     val kvsPortDetected = 3000
-    val kvsPort = data.sparkContext.getConf.getInt("spark.oap.mllib.oneccl.kvs.port",
-      kvsPortDetected)
+    val kvsPort =
+      data.sparkContext.getConf.getInt("spark.oap.mllib.oneccl.kvs.port", kvsPortDetected)
 
     kvsIP + "_" + kvsPort
   }
@@ -96,20 +102,23 @@ object Utils {
   def checkExecutorAvailPort(data: RDD[_], localIP: String): Int = {
 
     if (localIP == "127.0.0.1" || localIP == "127.0.1.1") {
-      println(s"\nOneCCL: Error: doesn't support loopback IP ${localIP}, " +
-        s"please assign IP address to your host.\n")
+      println(
+        s"\nOneCCL: Error: doesn't support loopback IP ${localIP}, " +
+          s"please assign IP address to your host.\n")
       System.exit(-1)
     }
 
     val sc = data.sparkContext
-    val result = data.mapPartitions { p =>
-      val port = OneCCL.getAvailPort(localIP)
-      if (port != -1) {
-        Iterator(port)
-      } else {
-        Iterator()
+    val result = data
+      .mapPartitions { p =>
+        val port = OneCCL.getAvailPort(localIP)
+        if (port != -1) {
+          Iterator(port)
+        } else {
+          Iterator()
+        }
       }
-    }.collect()
+      .collect()
 
     result(0)
   }
@@ -127,9 +136,11 @@ object Utils {
     // check workers' platform compatibility
     val executor_num = Utils.sparkExecutorNum(sc)
     val data = sc.parallelize(1 to executor_num, executor_num)
-    val result = data.mapPartitions { p =>
-      Iterator(OneDAL.cCheckPlatformCompatibility())
-    }.collect()
+    val result = data
+      .mapPartitions { p =>
+        Iterator(OneDAL.cCheckPlatformCompatibility())
+      }
+      .collect()
 
     result.forall(_ == true)
   }
diff --git a/mllib-dal/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala b/mllib-dal/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
index 74de47a85..e2c61ef35 100644
--- a/mllib-dal/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
+++ b/mllib-dal/src/main/scala/org/apache/spark/ml/classification/NaiveBayes.scala
@@ -1,3 +1,4 @@
+// scalastyle:off
 /*
  * Licensed to the Apache Software Foundation (ASF) under one or more
  * contributor license agreements.  See the NOTICE file distributed with
@@ -14,10 +15,12 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+// scalastyle:on
 
 package org.apache.spark.ml.classification
 
 import com.intel.oap.mllib.classification.NaiveBayesShim
+
 import org.apache.spark.annotation.Since
 import org.apache.spark.ml.linalg._
 import org.apache.spark.ml.param.ParamMap