From dcc502ec91ce5301b983116250a1909b9621848b Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Fri, 8 Aug 2014 12:16:41 -0700
Subject: [PATCH 1/2] update breeze to 0.9

---
 mllib/pom.xml                                                 | 2 +-
 .../org/apache/spark/mllib/linalg/distributed/RowMatrix.scala | 4 ++--
 .../spark/mllib/linalg/distributed/RowMatrixSuite.scala       | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/mllib/pom.xml b/mllib/pom.xml
index 9a33bd1cf6ad1..fc1ecfbea708f 100644
--- a/mllib/pom.xml
+++ b/mllib/pom.xml
@@ -57,7 +57,7 @@
     <dependency>
       <groupId>org.scalanlp</groupId>
       <artifactId>breeze_${scala.binary.version}</artifactId>
-      <version>0.7</version>
+      <version>0.9</version>
       <exclusions>
         <!-- This is included as a compile-scoped dependency by jtransforms, which is
              a dependency of breeze. -->
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
index 45486b2c7d82d..e76bc9fefff01 100644
--- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
+++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/distributed/RowMatrix.scala
@@ -222,7 +222,7 @@ class RowMatrix(
         EigenValueDecomposition.symmetricEigs(v => G * v, n, k, tol, maxIter)
       case SVDMode.LocalLAPACK =>
         val G = computeGramianMatrix().toBreeze.asInstanceOf[BDM[Double]]
-        val (uFull: BDM[Double], sigmaSquaresFull: BDV[Double], _) = brzSvd(G)
+        val brzSvd.SVD(uFull: BDM[Double], sigmaSquaresFull: BDV[Double], _) = brzSvd(G)
         (sigmaSquaresFull, uFull)
       case SVDMode.DistARPACK =>
         require(k < n, s"k must be smaller than n in dist-eigs mode but got k=$k and n=$n.")
@@ -338,7 +338,7 @@ class RowMatrix(
 
     val Cov = computeCovariance().toBreeze.asInstanceOf[BDM[Double]]
 
-    val (u: BDM[Double], _, _) = brzSvd(Cov)
+    val brzSvd.SVD(u: BDM[Double], _, _) = brzSvd(Cov)
 
     if (k == n) {
       Matrices.dense(n, k, u.data)
diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
index 325b817980f68..1d3a3221365cc 100644
--- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/distributed/RowMatrixSuite.scala
@@ -99,7 +99,7 @@ class RowMatrixSuite extends FunSuite with LocalSparkContext {
     for (mat <- Seq(denseMat, sparseMat)) {
       for (mode <- Seq("auto", "local-svd", "local-eigs", "dist-eigs")) {
         val localMat = mat.toBreeze()
-        val (localU, localSigma, localVt) = brzSvd(localMat)
+        val brzSvd.SVD(localU, localSigma, localVt) = brzSvd(localMat)
         val localV: BDM[Double] = localVt.t.toDenseMatrix
         for (k <- 1 to n) {
           val skip = (mode == "local-eigs" || mode == "dist-eigs") && k == n

From 7fc16b64c4088a300b700eb0078ed59ddb8f8929 Mon Sep 17 00:00:00 2001
From: Xiangrui Meng <meng@databricks.com>
Date: Fri, 8 Aug 2014 13:32:58 -0700
Subject: [PATCH 2/2] don't know why but exclude a private method for mima

---
 project/MimaExcludes.scala | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala
index 537ca0dcf267d..b4653c72c10b5 100644
--- a/project/MimaExcludes.scala
+++ b/project/MimaExcludes.scala
@@ -110,6 +110,10 @@ object MimaExcludes {
             ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.LabelParser$"),
             ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.MulticlassLabelParser"),
             ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.mllib.util.MulticlassLabelParser$")
+          ) ++ 
+          Seq ( // package-private classes removed in MLlib
+            ProblemFilters.exclude[MissingMethodProblem](
+              "org.apache.spark.mllib.regression.GeneralizedLinearAlgorithm.org$apache$spark$mllib$regression$GeneralizedLinearAlgorithm$$prependOne")
           )
         case v if v.startsWith("1.0") =>
           Seq(