[jvm-packages] fixed several issues in unit tests (#2173)

* add back train method but mark as deprecated

* fix scalastyle error

* change class to object in examples

* fix compilation error

* fix several issues in tests

jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostDFSuite.scala

@@ -222,22 +222,22 @@ class XGBoostDFSuite extends SharedSparkContext with Utils {
     LabeledPoint(intValueArray.last, new DenseVector(intValueArray.take(intValueArray.length - 1)))
   }
 
-  private def loadCSVPoints(filePath: String, zeroBased: Boolean = false): List[LabeledPoint] = {
+  private def loadCSVPoints(filePath: String, zeroBased: Boolean = false): Seq[LabeledPoint] = {
     val file = Source.fromFile(new File(filePath))
     val sampleList = new ListBuffer[LabeledPoint]
     for (sample <- file.getLines()) {
       sampleList += convertCSVPointToLabelPoint(sample.split(","))
     }
-    sampleList.toList
+    sampleList
   }
 
   test("multi_class classification test") {
     val paramMap = Map("eta" -> "0.1", "max_depth" -> "6", "silent" -> "1",
       "objective" -> "multi:softmax", "num_class" -> "6")
-    val testItr = loadCSVPoints(getClass.getResource("/dermatology.data").getFile).iterator
+    val trainingSet = loadCSVPoints(getClass.getResource("/dermatology.data").getFile)
-    val trainingDF = buildTrainingDataframe()
+    val spark = SparkSession.builder().getOrCreate()
-    XGBoost.trainWithDataFrame(trainingDF, paramMap,
+    import spark.implicits._
-      round = 5, nWorkers = numWorkers)
+    XGBoost.trainWithDataFrame(trainingSet.toDF(), paramMap, round = 5, nWorkers = numWorkers)
   }
 
   test("test DF use nested groupData") {

jvm-packages/xgboost4j-spark/src/test/scala/ml/dmlc/xgboost4j/scala/spark/XGBoostSparkPipelinePersistence.scala

@@ -16,16 +16,35 @@
 
 package ml.dmlc.xgboost4j.scala.spark
 
+import java.io.{File, FileNotFoundException}
+
 import org.apache.spark.SparkConf
 import org.apache.spark.ml.feature._
 import org.apache.spark.ml.{Pipeline, PipelineModel}
 import org.apache.spark.sql.SparkSession
-
 import scala.concurrent.duration._
 
 case class Foobar(TARGET: Int, bar: Double, baz: Double)
 
 class XGBoostSparkPipelinePersistence extends SharedSparkContext with Utils {
+
+  override def afterAll(): Unit = {
+    super.afterAll()
+    delete(new File("./testxgbPipe"))
+    delete(new File("./test2xgbPipe"))
+  }
+
+  private def delete(f: File) {
+    if (f.isDirectory()) {
+      for (c <- f.listFiles()) {
+        delete(c)
+      }
+    }
+    if (!f.delete()) {
+      throw new FileNotFoundException("Failed to delete file: " + f)
+    }
+  }
+
   test("test sparks pipeline persistence of dataframe-based model") {
     //  maybe move to shared context, but requires session to import implicits.
     // what about introducing https://github.com/holdenk/spark-testing-base ?