[SPARK-3081][MLLIB] rename RandomRDDGenerators to RandomRDDs

`RandomRDDGenerators` means factory for `RandomRDDGenerator`. However, its methods return RDDs but not RDDGenerators. So a more proper (and shorter) name would be `RandomRDDs`.

dorx brkyvz

Author: Xiangrui Meng <meng@databricks.com>

Closes #1979 from mengxr/randomrdds and squashes the following commits:

b161a2d [Xiangrui Meng] rename RandomRDDGenerators to RandomRDDs

3 files changed, 12 insertions, 12 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
index 18dc087856..4343124f10 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/api/python/PythonMLLibAPI.scala
@@ -27,7 +27,7 @@ import org.apache.spark.mllib.classification._
 import org.apache.spark.mllib.clustering._
 import org.apache.spark.mllib.optimization._
 import org.apache.spark.mllib.linalg.{Matrix, SparseVector, Vector, Vectors}
-import org.apache.spark.mllib.random.{RandomRDDGenerators => RG}
+import org.apache.spark.mllib.random.{RandomRDDs => RG}
 import org.apache.spark.mllib.recommendation._
 import org.apache.spark.mllib.regression._
 import org.apache.spark.mllib.tree.configuration.{Algo, Strategy}
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDGenerators.scala b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala
index b0a0593223..3627036952 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDGenerators.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/random/RandomRDDs.scala
@@ -17,6 +17,8 @@
 
 package org.apache.spark.mllib.random
 
+import scala.reflect.ClassTag
+
 import org.apache.spark.SparkContext
 import org.apache.spark.annotation.Experimental
 import org.apache.spark.mllib.linalg.Vector
@@ -24,14 +26,12 @@ import org.apache.spark.mllib.rdd.{RandomVectorRDD, RandomRDD}
 import org.apache.spark.rdd.RDD
 import org.apache.spark.util.Utils
 
-import scala.reflect.ClassTag
-
 /**
  * :: Experimental ::
  * Generator methods for creating RDDs comprised of i.i.d. samples from some distribution.
  */
 @Experimental
-object RandomRDDGenerators {
+object RandomRDDs {
 
   /**
    * :: Experimental ::
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDGeneratorsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
index 96e0bc63b0..c50b78bcbc 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDGeneratorsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/random/RandomRDDsSuite.scala
@@ -34,7 +34,7 @@ import org.apache.spark.util.StatCounter
  *
  * TODO update tests to use TestingUtils for floating point comparison after PR 1367 is merged
  */
-class RandomRDDGeneratorsSuite extends FunSuite with LocalSparkContext with Serializable {
+class RandomRDDsSuite extends FunSuite with LocalSparkContext with Serializable {
 
   def testGeneratedRDD(rdd: RDD[Double],
       expectedSize: Long,
@@ -113,18 +113,18 @@ class RandomRDDGeneratorsSuite extends FunSuite with LocalSparkContext with Seri
     val poissonMean = 100.0
 
     for (seed <- 0 until 5) {
-      val uniform = RandomRDDGenerators.uniformRDD(sc, size, numPartitions, seed)
+      val uniform = RandomRDDs.uniformRDD(sc, size, numPartitions, seed)
       testGeneratedRDD(uniform, size, numPartitions, 0.5, 1 / math.sqrt(12))
 
-      val normal = RandomRDDGenerators.normalRDD(sc, size, numPartitions, seed)
+      val normal = RandomRDDs.normalRDD(sc, size, numPartitions, seed)
       testGeneratedRDD(normal, size, numPartitions, 0.0, 1.0)
 
-      val poisson = RandomRDDGenerators.poissonRDD(sc, poissonMean, size, numPartitions, seed)
+      val poisson = RandomRDDs.poissonRDD(sc, poissonMean, size, numPartitions, seed)
       testGeneratedRDD(poisson, size, numPartitions, poissonMean, math.sqrt(poissonMean), 0.1)
     }
 
     // mock distribution to check that partitions have unique seeds
-    val random = RandomRDDGenerators.randomRDD(sc, new MockDistro(), 1000L, 1000, 0L)
+    val random = RandomRDDs.randomRDD(sc, new MockDistro(), 1000L, 1000, 0L)
     assert(random.collect.size === random.collect.distinct.size)
   }
 
@@ -135,13 +135,13 @@ class RandomRDDGeneratorsSuite extends FunSuite with LocalSparkContext with Seri
     val poissonMean = 100.0
 
     for (seed <- 0 until 5) {
-      val uniform = RandomRDDGenerators.uniformVectorRDD(sc, rows, cols, parts, seed)
+      val uniform = RandomRDDs.uniformVectorRDD(sc, rows, cols, parts, seed)
       testGeneratedVectorRDD(uniform, rows, cols, parts, 0.5, 1 / math.sqrt(12))
 
-      val normal = RandomRDDGenerators.normalVectorRDD(sc, rows, cols, parts, seed)
+      val normal = RandomRDDs.normalVectorRDD(sc, rows, cols, parts, seed)
       testGeneratedVectorRDD(normal, rows, cols, parts, 0.0, 1.0)
 
-      val poisson = RandomRDDGenerators.poissonVectorRDD(sc, poissonMean, rows, cols, parts, seed)
+      val poisson = RandomRDDs.poissonVectorRDD(sc, poissonMean, rows, cols, parts, seed)
       testGeneratedVectorRDD(poisson, rows, cols, parts, poissonMean, math.sqrt(poissonMean), 0.1)
     }
   }