Github user yinxusen commented on a diff in the pull request:
https://github.com/apache/spark/pull/268#discussion_r11161910
--- Diff:
mllib/src/test/scala/org/apache/spark/mllib/rdd/VectorRDDFunctionsSuite.scala
---
@@ -0,0 +1,84 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.mllib.rdd
+
+import scala.collection.mutable.ArrayBuffer
+
+import org.scalatest.FunSuite
+
+import org.apache.spark.mllib.linalg.{Vector, Vectors}
+import org.apache.spark.mllib.util.LocalSparkContext
+import org.apache.spark.mllib.util.MLUtils._
+
+/**
+ * Test suite for the summary statistics of RDD[Vector]. Both the accuracy
and the time consuming
+ * between dense and sparse vector are tested.
+ */
+class VectorRDDFunctionsSuite extends FunSuite with LocalSparkContext {
+ import VectorRDDFunctionsSuite._
+
+ val localData = Array(
+ Vectors.dense(1.0, 2.0, 3.0),
+ Vectors.dense(4.0, 5.0, 6.0),
+ Vectors.dense(7.0, 8.0, 9.0)
+ )
+
+ val sparseData = ArrayBuffer(Vectors.sparse(20, Seq((0, 1.0), (9, 2.0),
(10, 7.0))))
+ for (i <- 0 until 10000) sparseData += Vectors.sparse(20, Seq((9, 0.0)))
+ sparseData += Vectors.sparse(20, Seq((0, 5.0), (9, 13.0), (16, 2.0)))
+ sparseData += Vectors.sparse(20, Seq((3, 5.0), (9, 13.0), (18, 2.0)))
+
+ test("full-statistics") {
+ val data = sc.parallelize(localData, 2)
+ val (VectorRDDStatisticalSummary(mean, variance, cnt, nnz, max, min),
denseTime) =
+ time(data.summarizeStatistics(3))
+
+ assert(equivVector(mean, Vectors.dense(4.0, 5.0, 6.0)), "Column mean
do not match.")
+ assert(equivVector(variance, Vectors.dense(6.0, 6.0, 6.0)), "Column
variance do not match.")
+ assert(cnt === 3, "Column cnt do not match.")
+ assert(equivVector(nnz, Vectors.dense(3.0, 3.0, 3.0)), "Column nnz do
not match.")
+ assert(equivVector(max, Vectors.dense(7.0, 8.0, 9.0)), "Column max do
not match.")
+ assert(equivVector(min, Vectors.dense(1.0, 2.0, 3.0)), "Column min do
not match.")
+
+ val dataForSparse = sc.parallelize(sparseData.toSeq, 2)
+ val (_, sparseTime) = time(dataForSparse.summarizeStatistics(20))
+
+ println(s"dense time is $denseTime, sparse time is $sparseTime.")
+ assert(relativeTime(denseTime, sparseTime),
+ "Relative time between dense and sparse vector doesn't match.")
+ }
+}
+
+object VectorRDDFunctionsSuite {
+ def time[R](block: => R): (R, Double) = {
+ val t0 = System.nanoTime()
+ val result = block
+ val t1 = System.nanoTime()
+ (result, (t1 - t0).toDouble / 1.0e9)
+ }
+
+ def equivVector(lhs: Vector, rhs: Vector): Boolean = {
+ (lhs.toBreeze - rhs.toBreeze).norm(2) < 1e-9
+ }
+
+ def relativeTime(lhs: Double, rhs: Double): Boolean = {
+ val denominator = math.max(lhs, rhs)
+ math.abs(lhs - rhs) / denominator < 0.3
+ }
+}
+
--- End diff --
Build failed might be caught by this empty line in the end. I'll fix it in
next commit with other problems.
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