diff --git a/jvm-packages/pom.xml b/jvm-packages/pom.xml
index 5899a6f76a47..5e47ae5c5d1a 100644
--- a/jvm-packages/pom.xml
+++ b/jvm-packages/pom.xml
@@ -34,7 +34,7 @@
         <maven.compiler.source>1.8</maven.compiler.source>
         <maven.compiler.target>1.8</maven.compiler.target>
         <flink.version>1.7.2</flink.version>
-        <spark.version>2.4.3</spark.version>
+        <spark.version>3.0.0</spark.version>
         <scala.version>2.12.8</scala.version>
         <scala.binary.version>2.12</scala.binary.version>
         <hadoop.version>2.7.3</hadoop.version>
diff --git a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
index 4ae41e8fa1f8..e62c66a5ec61 100644
--- a/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
+++ b/jvm-packages/xgboost4j-spark/src/main/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostClassifier.scala
@@ -272,7 +272,7 @@ class XGBoostClassificationModel private[ml](
   }
 
   // Actually we don't use this function at all, to make it pass compiler check.
-  override protected def predictRaw(features: Vector): Vector = {
+  override def predictRaw(features: Vector): Vector = {
     throw new Exception("XGBoost-Spark does not support \'predictRaw\'")
   }
 
diff --git a/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/MissingValueHandlingSuite.scala b/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/MissingValueHandlingSuite.scala
index 22e35e847a0f..bb23ba50a781 100644
--- a/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/MissingValueHandlingSuite.scala
+++ b/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/MissingValueHandlingSuite.scala
@@ -60,13 +60,8 @@ class MissingValueHandlingSuite extends FunSuite with PerTest {
     val vectorAssembler = new VectorAssembler()
       .setInputCols(Array("col1", "col2", "col3"))
       .setOutputCol("features")
-    org.apache.spark.SPARK_VERSION match {
-      case version if version.startsWith("2.4") =>
-        val m = vectorAssembler.getClass.getDeclaredMethods
-          .filter(_.getName.contains("setHandleInvalid")).head
-        m.invoke(vectorAssembler, "keep")
-      case _ =>
-    }
+      .setHandleInvalid("keep")
+
     val inputDF = vectorAssembler.transform(testDF).select("features", "label")
     val paramMap = List("eta" -> "1", "max_depth" -> "2",
       "objective" -> "binary:logistic", "missing" -> Float.NaN, "num_workers" -> 1).toMap
diff --git a/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressorSuite.scala b/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressorSuite.scala
index ff88ff328659..fc1f8d9063ed 100644
--- a/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressorSuite.scala
+++ b/jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostRegressorSuite.scala
@@ -127,7 +127,7 @@ class XGBoostRegressorSuite extends FunSuite with PerTest {
     val paramMap = Map("eta" -> "1", "max_depth" -> "6", "silent" -> "1",
       "objective" -> "reg:squarederror", "num_round" -> 5, "num_workers" -> numWorkers)
 
-    val getWeightFromId = udf({id: Int => if (id == 0) 1.0f else 0.001f}, DataTypes.FloatType)
+    val getWeightFromId = udf({id: Int => if (id == 0) 1.0f else 0.001f})
     val trainingDF = buildDataFrame(Regression.train)
       .withColumn("weight", getWeightFromId(col("id")))
     val testDF = buildDataFrame(Regression.test)