diff options
Diffstat (limited to 'mllib/src/test')
3 files changed, 3 insertions, 3 deletions
diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala index 1912afce93..33e40dc741 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala @@ -31,7 +31,7 @@ class LogisticRegressionSuite extends FunSuite with MLlibTestSparkContext { override def beforeAll(): Unit = { super.beforeAll() sqlContext = new SQLContext(sc) - dataset = sqlContext.createSchemaRDD( + dataset = sqlContext.createDataFrame( sc.parallelize(generateLogisticInput(1.0, 1.0, 100, 42), 2)) } diff --git a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala index 58289acdbc..9da253c61d 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/recommendation/ALSSuite.scala @@ -350,7 +350,7 @@ class ALSSuite extends FunSuite with MLlibTestSparkContext with Logging { numItemBlocks: Int = 3, targetRMSE: Double = 0.05): Unit = { val sqlContext = this.sqlContext - import sqlContext.createSchemaRDD + import sqlContext.createDataFrame val als = new ALS() .setRank(rank) .setRegParam(regParam) 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 74104fa7a6..761ea821ef 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 @@ -32,7 +32,7 @@ class CrossValidatorSuite extends FunSuite with MLlibTestSparkContext { override def beforeAll(): Unit = { super.beforeAll() val sqlContext = new SQLContext(sc) - dataset = sqlContext.createSchemaRDD( + dataset = sqlContext.createDataFrame( sc.parallelize(generateLogisticInput(1.0, 1.0, 100, 42), 2)) } |