Scala 2.13 support. (#9099)

1. Updated the test logic
2. Added smoke tests for Spark examples.
3. Added integration tests for Spark with Scala 2.13

jvm-packages/xgboost4j/pom.xml

@@ -5,10 +5,11 @@
     <modelVersion>4.0.0</modelVersion>
     <parent>
         <groupId>ml.dmlc</groupId>
-        <artifactId>xgboost-jvm_2.12</artifactId>
+        <artifactId>xgboost-jvm</artifactId>
         <version>2.0.0-SNAPSHOT</version>
     </parent>
-    <artifactId>xgboost4j_2.12</artifactId>
+    <name>xgboost4j</name>
+    <artifactId>xgboost4j_${scala.binary.version}</artifactId>
     <version>2.0.0-SNAPSHOT</version>
     <packaging>jar</packaging>
 
@@ -28,13 +29,13 @@
         <dependency>
             <groupId>junit</groupId>
             <artifactId>junit</artifactId>
-            <version>4.13.2</version>
+            <version>${junit.version}</version>
             <scope>test</scope>
         </dependency>
         <dependency>
           <groupId>org.scalatest</groupId>
           <artifactId>scalatest_${scala.binary.version}</artifactId>
-          <version>3.2.16</version>
+          <version>${scalatest.version}</version>
           <scope>provided</scope>
         </dependency>
     </dependencies>

jvm-packages/xgboost4j/src/main/scala/ml/dmlc/xgboost4j/scala/EvalTrait.scala

@@ -37,7 +37,7 @@ trait EvalTrait extends IEvaluation {
    */
   def eval(predicts: Array[Array[Float]], dmat: DMatrix): Float
 
-  private[scala] def eval(predicts: Array[Array[Float]], jdmat: java.DMatrix): Float = {
+  def eval(predicts: Array[Array[Float]], jdmat: java.DMatrix): Float = {
     require(predicts.length == jdmat.getLabel.length, "predicts size and label size must match " +
       s" predicts size: ${predicts.length}, label size: ${jdmat.getLabel.length}")
     eval(predicts, new DMatrix(jdmat))

jvm-packages/xgboost4j/src/main/scala/ml/dmlc/xgboost4j/scala/ObjectiveTrait.scala

@@ -31,7 +31,7 @@ trait ObjectiveTrait extends IObjective {
    */
   def getGradient(predicts: Array[Array[Float]], dtrain: DMatrix): List[Array[Float]]
 
-  private[scala] def getGradient(predicts: Array[Array[Float]], dtrain: JDMatrix):
+  def getGradient(predicts: Array[Array[Float]], dtrain: JDMatrix):
     java.util.List[Array[Float]] = {
     getGradient(predicts, new DMatrix(dtrain)).asJava
   }

jvm-packages/xgboost4j/src/main/scala/ml/dmlc/xgboost4j/scala/XGBoost.scala

@@ -17,12 +17,11 @@
 package ml.dmlc.xgboost4j.scala
 
 import java.io.InputStream
+import ml.dmlc.xgboost4j.java.{XGBoostError, XGBoost => JXGBoost}
 
-import ml.dmlc.xgboost4j.java.{XGBoostError, Booster => JBooster, XGBoost => JXGBoost}
-import scala.collection.JavaConverters._
-
+import scala.jdk.CollectionConverters._
 import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.fs.{FileSystem, Path}
+import org.apache.hadoop.fs.Path
 
 /**
   * XGBoost Scala Training function.
@@ -40,7 +39,12 @@ object XGBoost {
       earlyStoppingRound: Int = 0,
       prevBooster: Booster,
       checkpointParams: Option[ExternalCheckpointParams]): Booster = {
-    val jWatches = watches.mapValues(_.jDMatrix).asJava
+
+    // we have to filter null value for customized obj and eval
+    val jParams: java.util.Map[String, AnyRef] =
+      params.filter(_._2 != null).mapValues(_.toString.asInstanceOf[AnyRef]).toMap.asJava
+
+    val jWatches = watches.mapValues(_.jDMatrix).toMap.asJava
     val jBooster = if (prevBooster == null) {
       null
     } else {
@@ -51,8 +55,7 @@ object XGBoost {
       map(cp => {
           JXGBoost.trainAndSaveCheckpoint(
             dtrain.jDMatrix,
-            // we have to filter null value for customized obj and eval
-            params.filter(_._2 != null).mapValues(_.toString.asInstanceOf[AnyRef]).asJava,
+            jParams,
             numRounds, jWatches, metrics, obj, eval, earlyStoppingRound, jBooster,
             cp.checkpointInterval,
             cp.checkpointPath,
@@ -61,8 +64,7 @@ object XGBoost {
       getOrElse(
         JXGBoost.train(
           dtrain.jDMatrix,
-          // we have to filter null value for customized obj and eval
-          params.filter(_._2 != null).mapValues(_.toString.asInstanceOf[AnyRef]).asJava,
+          jParams,
           numRounds, jWatches, metrics, obj, eval, earlyStoppingRound, jBooster)
       )
     if (prevBooster == null) {