[SPARK-14516][ML][FOLLOW-UP] Move ClusteringEvaluatorSuite test data …

…to data/mllib.

## What changes were proposed in this pull request?
Move ```ClusteringEvaluatorSuite``` test data(iris) to data/mllib, to prevent from re-creating a new folder.

## How was this patch tested?
Existing tests.

Author: Yanbo Liang <ybliang8@gmail.com>

Closes apache#19648 from yanboliang/spark-14516.

mllib/src/test/scala/org/apache/spark/ml/evaluation/ClusteringEvaluatorSuite.scala

@@ -22,15 +22,21 @@ import org.apache.spark.ml.param.ParamsSuite
 import org.apache.spark.ml.util.DefaultReadWriteTest
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
-import org.apache.spark.sql.{DataFrame, SparkSession}
-import org.apache.spark.sql.types.IntegerType
+import org.apache.spark.sql.Dataset
 
 
 class ClusteringEvaluatorSuite
   extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
 
   import testImplicits._
 
+  @transient var irisDataset: Dataset[_] = _
+
+  override def beforeAll(): Unit = {
+    super.beforeAll()
+    irisDataset = spark.read.format("libsvm").load("../data/mllib/iris_libsvm.txt")
+  }
+
   test("params") {
     ParamsSuite.checkParams(new ClusteringEvaluator)
   }
@@ -53,37 +59,23 @@ class ClusteringEvaluatorSuite
     0.6564679231
   */
   test("squared euclidean Silhouette") {
-    val iris = ClusteringEvaluatorSuite.irisDataset(spark)
     val evaluator = new ClusteringEvaluator()
         .setFeaturesCol("features")
         .setPredictionCol("label")
 
-    assert(evaluator.evaluate(iris) ~== 0.6564679231 relTol 1e-5)
+    assert(evaluator.evaluate(irisDataset) ~== 0.6564679231 relTol 1e-5)
   }
 
   test("number of clusters must be greater than one") {
-    val iris = ClusteringEvaluatorSuite.irisDataset(spark)
-      .where($"label" === 0.0)
+    val singleClusterDataset = irisDataset.where($"label" === 0.0)
     val evaluator = new ClusteringEvaluator()
       .setFeaturesCol("features")
       .setPredictionCol("label")
 
     val e = intercept[AssertionError]{
-      evaluator.evaluate(iris)
+      evaluator.evaluate(singleClusterDataset)
     }
     assert(e.getMessage.contains("Number of clusters must be greater than one"))
   }
 
 }
-
-object ClusteringEvaluatorSuite {
-  def irisDataset(spark: SparkSession): DataFrame = {
-
-    val irisPath = Thread.currentThread()
-      .getContextClassLoader
-      .getResource("test-data/iris.libsvm")
-      .toString
-
-    spark.read.format("libsvm").load(irisPath)
-  }
-}