diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala index 09183fe65b72202c6af2837b5ed749dd10da42e6..035bfc07b684dbdd8ec32bf4c3549b6b5fd191a0 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/MinMaxScalerSuite.scala @@ -21,13 +21,11 @@ import org.apache.spark.SparkFunSuite import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils} import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext -import org.apache.spark.sql.{Row, SQLContext} +import org.apache.spark.sql.Row class MinMaxScalerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { test("MinMaxScaler fit basic case") { - val sqlContext = new SQLContext(sc) - val data = Array( Vectors.dense(1, 0, Long.MinValue), Vectors.dense(2, 0, 0), diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala index de3d438ce83be8be70ffbdbc660afc95508177ee..468833901995a36ffc92325065fb515eace253db 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/NormalizerSuite.scala @@ -22,7 +22,7 @@ import org.apache.spark.ml.util.DefaultReadWriteTest import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ -import org.apache.spark.sql.{DataFrame, Row, SQLContext} +import org.apache.spark.sql.{DataFrame, Row} class NormalizerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { @@ -61,7 +61,6 @@ class NormalizerSuite extends SparkFunSuite with MLlibTestSparkContext with Defa Vectors.sparse(3, Seq()) ) - val sqlContext = new SQLContext(sc) dataFrame = sqlContext.createDataFrame(sc.parallelize(data, 2).map(NormalizerSuite.FeatureData)) normalizer = new Normalizer() .setInputCol("features") diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala index 74706a23e0936660a7363150a642f8a956cced47..8acc3369c489c53aa5682539486b6a94b6d4b651 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorSlicerSuite.scala @@ -24,7 +24,7 @@ import org.apache.spark.ml.util.DefaultReadWriteTest import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.types.StructType -import org.apache.spark.sql.{DataFrame, Row, SQLContext} +import org.apache.spark.sql.{DataFrame, Row} class VectorSlicerSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest { @@ -54,8 +54,6 @@ class VectorSlicerSuite extends SparkFunSuite with MLlibTestSparkContext with De } test("Test vector slicer") { - val sqlContext = new SQLContext(sc) - val data = Array( Vectors.sparse(5, Seq((0, -2.0), (1, 2.3))), Vectors.dense(-2.0, 2.3, 0.0, 0.0, 1.0), diff --git a/mllib/src/test/scala/org/apache/spark/ml/impl/TreeTests.scala b/mllib/src/test/scala/org/apache/spark/ml/impl/TreeTests.scala index 460849c79f04fe89b9465baf695b3eb03e3b966f..4e2d0e93bd4122af59d8a554daa5eece229ef63c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/impl/TreeTests.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/impl/TreeTests.scala @@ -42,7 +42,7 @@ private[ml] object TreeTests extends SparkFunSuite { data: RDD[LabeledPoint], categoricalFeatures: Map[Int, Int], numClasses: Int): DataFrame = { - val sqlContext = new SQLContext(data.sparkContext) + val sqlContext = SQLContext.getOrCreate(data.sparkContext) import sqlContext.implicits._ val df = data.toDF() val numFeatures = data.first().features.size diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala index dd6366050c02071eb6d751766665148cbda7d2d3..d281084f913c0689a8bfb84c82291d4ad53a4cc7 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala @@ -29,7 +29,7 @@ import org.apache.spark.ml.regression.LinearRegression import org.apache.spark.mllib.classification.LogisticRegressionSuite.generateLogisticInput import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} -import org.apache.spark.sql.{DataFrame, SQLContext} +import org.apache.spark.sql.DataFrame import org.apache.spark.sql.types.StructType class CrossValidatorSuite @@ -39,7 +39,6 @@ class CrossValidatorSuite override def beforeAll(): Unit = { super.beforeAll() - val sqlContext = new SQLContext(sc) dataset = sqlContext.createDataFrame( sc.parallelize(generateLogisticInput(1.0, 1.0, 100, 42), 2)) }