add dimension parameters to example
Project: http://git-wip-us.apache.org/repos/asf/incubator-spark/repo Commit: http://git-wip-us.apache.org/repos/asf/incubator-spark/commit/1afdeaeb Tree: http://git-wip-us.apache.org/repos/asf/incubator-spark/tree/1afdeaeb Diff: http://git-wip-us.apache.org/repos/asf/incubator-spark/diff/1afdeaeb Branch: refs/heads/master Commit: 1afdeaeb2f436084a6fbe8d73690f148f7b462c4 Parents: 21c8a54 Author: Reza Zadeh <riz...@gmail.com> Authored: Fri Jan 10 21:30:54 2014 -0800 Committer: Reza Zadeh <riz...@gmail.com> Committed: Fri Jan 10 21:30:54 2014 -0800 ---------------------------------------------------------------------- .../main/scala/org/apache/spark/examples/SparkSVD.scala | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/incubator-spark/blob/1afdeaeb/examples/src/main/scala/org/apache/spark/examples/SparkSVD.scala ---------------------------------------------------------------------- diff --git a/examples/src/main/scala/org/apache/spark/examples/SparkSVD.scala b/examples/src/main/scala/org/apache/spark/examples/SparkSVD.scala index d9c672f..ce7c1c4 100644 --- a/examples/src/main/scala/org/apache/spark/examples/SparkSVD.scala +++ b/examples/src/main/scala/org/apache/spark/examples/SparkSVD.scala @@ -29,12 +29,12 @@ import org.apache.spark.mllib.linalg.SparseMatrix * Where i is the column, j the row, and value is the matrix entry * * For example input file, see: - * mllib/data/als/test.data + * mllib/data/als/test.data (example is 4 x 4) */ object SparkSVD { def main(args: Array[String]) { - if (args.length != 2) { - System.err.println("Usage: SparkSVD <master> <file>") + if (args.length != 4) { + System.err.println("Usage: SparkSVD <master> <file> m n") System.exit(1) } val sc = new SparkContext(args(0), "SVD", @@ -45,8 +45,8 @@ object SparkSVD { val parts = line.split(',') MatrixEntry(parts(0).toInt, parts(1).toInt, parts(2).toDouble) } - val m = 4 - val n = 4 + val m = args(2).toInt + val n = args(3).toInt // recover largest singular vector val decomposed = SVD.sparseSVD(SparseMatrix(data, m, n), 1)
