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author | CodingCat <zhunansjtu@gmail.com> | 2014-03-12 17:43:12 -0700 |
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committer | Aaron Davidson <aaron@databricks.com> | 2014-03-12 17:43:12 -0700 |
commit | 9032f7c0d5f1ae7985a20d54ca04c297201aae85 (patch) | |
tree | dff8324523fd8163ea369b524f73b1ef303605c0 /mllib/src | |
parent | b8afe3052086547879ebf28d6e36207e0d370710 (diff) | |
download | spark-9032f7c0d5f1ae7985a20d54ca04c297201aae85.tar.gz spark-9032f7c0d5f1ae7985a20d54ca04c297201aae85.tar.bz2 spark-9032f7c0d5f1ae7985a20d54ca04c297201aae85.zip |
SPARK-1160: Deprecate toArray in RDD
https://spark-project.atlassian.net/browse/SPARK-1160
reported by @mateiz: "It's redundant with collect() and the name doesn't make sense in Java, where we return a List (we can't return an array due to the way Java generics work). It's also missing in Python."
In this patch, I deprecated the method and changed the source files using it by replacing toArray with collect() directly
Author: CodingCat <zhunansjtu@gmail.com>
Closes #105 from CodingCat/SPARK-1060 and squashes the following commits:
286f163 [CodingCat] deprecate in JavaRDDLike
ee17b4e [CodingCat] add message and since
2ff7319 [CodingCat] deprecate toArray in RDD
Diffstat (limited to 'mllib/src')
-rw-r--r-- | mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala | 4 | ||||
-rw-r--r-- | mllib/src/test/scala/org/apache/spark/mllib/linalg/SVDSuite.scala | 6 |
2 files changed, 5 insertions, 5 deletions
diff --git a/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala b/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala index 8803c4c1a0..e4a26eeb07 100644 --- a/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala +++ b/mllib/src/main/scala/org/apache/spark/mllib/linalg/SVD.scala @@ -109,7 +109,7 @@ object SVD { // Construct jblas A^T A locally val ata = DoubleMatrix.zeros(n, n) - for (entry <- emits.toArray) { + for (entry <- emits.collect()) { ata.put(entry._1._1, entry._1._2, entry._2) } @@ -178,7 +178,7 @@ object SVD { val s = decomposed.S.data val v = decomposed.V.data - println("Computed " + s.toArray.length + " singular values and vectors") + println("Computed " + s.collect().length + " singular values and vectors") u.saveAsTextFile(output_u) s.saveAsTextFile(output_s) v.saveAsTextFile(output_v) diff --git a/mllib/src/test/scala/org/apache/spark/mllib/linalg/SVDSuite.scala b/mllib/src/test/scala/org/apache/spark/mllib/linalg/SVDSuite.scala index 32f3f141cd..a92386865a 100644 --- a/mllib/src/test/scala/org/apache/spark/mllib/linalg/SVDSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/mllib/linalg/SVDSuite.scala @@ -50,7 +50,7 @@ class SVDSuite extends FunSuite with BeforeAndAfterAll { val m = matrix.m val n = matrix.n val ret = DoubleMatrix.zeros(m, n) - matrix.data.toArray.map(x => ret.put(x.i, x.j, x.mval)) + matrix.data.collect().map(x => ret.put(x.i, x.j, x.mval)) ret } @@ -106,7 +106,7 @@ class SVDSuite extends FunSuite with BeforeAndAfterAll { val u = decomposed.U val s = decomposed.S val v = decomposed.V - val retrank = s.data.toArray.length + val retrank = s.data.collect().length assert(retrank == 1, "rank returned not one") @@ -139,7 +139,7 @@ class SVDSuite extends FunSuite with BeforeAndAfterAll { val u = decomposed.U val s = decomposed.S val v = decomposed.V - val retrank = s.data.toArray.length + val retrank = s.data.collect().length val densea = getDenseMatrix(a) val svd = Singular.sparseSVD(densea) |