[ https://issues.apache.org/jira/browse/SPARK-16566?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Joseph K. Bradley closed SPARK-16566. ------------------------------------- Resolution: Duplicate Linking existing JIRA which this one is duplicating. Could you please work under the other JIRA instead of this one? Thanks! > Bug in SparseMatrix multiplication with SparseVector > ---------------------------------------------------- > > Key: SPARK-16566 > URL: https://issues.apache.org/jira/browse/SPARK-16566 > Project: Spark > Issue Type: Bug > Components: MLlib > Affects Versions: 1.6.2 > Reporter: Wilson > > In the org.apache.spark.mllib.linalg.BLAS.scala, the multiplication between > SparseMatrix (sm) and SparseVector (sv) when sm is not transposed assume that > the indices is sorted, but there is no validation to make sure that is the > case, making the result returned wrongly. > This can be replicated simply by using spark-shell and entering these > commands: > import org.apache.spark.mllib.linalg.SparseMatrix > import org.apache.spark.mllib.linalg.SparseVector > import org.apache.spark.mllib.linalg.DenseVector > import scala.collection.mutable.ArrayBuffer > val vectorIndices = Array(3,2) > val vectorValues = Array(0.1,0.2) > val size = 4 > val sm = new SparseMatrix(size, size, Array(0, 0, 0, 1, 1), Array(0), > Array(1.0)) > val dm = sm.toDense > val sv = new SparseVector(size, vectorIndices, vectorValues) > val dv = new DenseVector(s.toArray) > sm.multiply(dv) == sm.multiply(sv) > sm.multiply(dv) > sm.multiply(sv) -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org