1 files changed, 5 insertions, 5 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
index 4a3ad662a0..36dce01590 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/recommendation/ALS.scala
@@ -40,7 +40,7 @@ import org.apache.spark.ml.util._
 import org.apache.spark.mllib.linalg.CholeskyDecomposition
 import org.apache.spark.mllib.optimization.NNLS
 import org.apache.spark.rdd.RDD
-import org.apache.spark.sql.DataFrame
+import org.apache.spark.sql.{DataFrame, Dataset}
 import org.apache.spark.sql.functions._
 import org.apache.spark.sql.types.{DoubleType, FloatType, IntegerType, StructType}
 import org.apache.spark.storage.StorageLevel
@@ -200,8 +200,8 @@ class ALSModel private[ml] (
   @Since("1.3.0")
   def setPredictionCol(value: String): this.type = set(predictionCol, value)
 
-  @Since("1.3.0")
-  override def transform(dataset: DataFrame): DataFrame = {
+  @Since("2.0.0")
+  override def transform(dataset: Dataset[_]): DataFrame = {
     // Register a UDF for DataFrame, and then
     // create a new column named map(predictionCol) by running the predict UDF.
     val predict = udf { (userFeatures: Seq[Float], itemFeatures: Seq[Float]) =>
@@ -385,8 +385,8 @@ class ALS(@Since("1.4.0") override val uid: String) extends Estimator[ALSModel]
     this
   }
 
-  @Since("1.3.0")
-  override def fit(dataset: DataFrame): ALSModel = {
+  @Since("2.0.0")
+  override def fit(dataset: Dataset[_]): ALSModel = {
     import dataset.sqlContext.implicits._
     val r = if ($(ratingCol) != "") col($(ratingCol)).cast(FloatType) else lit(1.0f)
     val ratings = dataset