[SPARK-5430] move treeReduce and treeAggregate from mllib to core

We have seen many use cases of `treeAggregate`/`treeReduce` outside the ML domain. Maybe it is time to move them to Core. pwendell

Author: Xiangrui Meng <meng@databricks.com>

Closes #4228 from mengxr/SPARK-5430 and squashes the following commits:

20ad40d [Xiangrui Meng] exclude tree* from mima
e89a43e [Xiangrui Meng] fix compile and update java doc
3ae1a4b [Xiangrui Meng] add treeReduce/treeAggregate to Python
6f948c5 [Xiangrui Meng] add treeReduce/treeAggregate to JavaRDDLike
d600b6c [Xiangrui Meng] move treeReduce and treeAggregate to core

2 files changed, 0 insertions, 19 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/mllib/feature/StandardScalerSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/feature/StandardScalerSuite.scala
index 4c93c0ca4f..e9e510b6f5 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/feature/StandardScalerSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/feature/StandardScalerSuite.scala
@@ -22,7 +22,6 @@ import org.scalatest.FunSuite
 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.mllib.rdd.RDDFunctions._
 import org.apache.spark.mllib.stat.{MultivariateStatisticalSummary, MultivariateOnlineSummarizer}
 import org.apache.spark.rdd.RDD
 
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/rdd/RDDFunctionsSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/rdd/RDDFunctionsSuite.scala
index 681ce92639..6d6c0aa5be 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/rdd/RDDFunctionsSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/rdd/RDDFunctionsSuite.scala
@@ -46,22 +46,4 @@ class RDDFunctionsSuite extends FunSuite with MLlibTestSparkContext {
     val expected = data.flatMap(x => x).sliding(3).toSeq.map(_.toSeq)
     assert(sliding === expected)
   }
-
-  test("treeAggregate") {
-    val rdd = sc.makeRDD(-1000 until 1000, 10)
-    def seqOp = (c: Long, x: Int) => c + x
-    def combOp = (c1: Long, c2: Long) => c1 + c2
-    for (depth <- 1 until 10) {
-      val sum = rdd.treeAggregate(0L)(seqOp, combOp, depth)
-      assert(sum === -1000L)
-    }
-  }
-
-  test("treeReduce") {
-    val rdd = sc.makeRDD(-1000 until 1000, 10)
-    for (depth <- 1 until 10) {
-      val sum = rdd.treeReduce(_ + _, depth)
-      assert(sum === -1000)
-    }
-  }
 }