You should supply more information about your input data.
For example ,I generate a IndexRowMatrix from ALS algorithm input data
format,my code like this:
val inputData = sc.textFile(fname).map{
line=>
val parts = line.trim.split(' ')
(parts(0).toLong,parts(1).toInt,parts(2).toDouble)
}
val ncol = inputData.map(_._2).max()+1
val nrows = inputData.map(_._1).max()+1
logInfo(s"rows:$nrows,columns:$ncol")
val dataRows = inputData.groupBy(_._1).map[IndexedRow]{ row =>
val (indices, values) = row._2.map(e => (e._2, e._3)).unzip
new IndexedRow(row._1, new SparseVector(ncol, indices.toArray,
values.toArray))
}
val svd = new
IndexedRowMatrix(dataRows.persist(),nrows,ncol).computeSVD(rank,computeU =
true)
If your input data has no index information,I think you should care
about the sort of rows in your RowMatrix, your matrix multiply should not
rely on assumption rowmatrix ordered.
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