How to parse CSV file values into MatrixEntry in Java/Scala -

i've got code in scala , have change java:

import au.com.bytecode.opencsv.csvparser import org.apache.spark.rdd.rdd import org.apache.spark.mllib.linalg.distributed.matrixentry import org.apache.spark.mllib.linalg.distributed.coordinatematrix import org.apache.spark.mllib.linalg.distributed.rowmatrix import org.apache.spark.mllib.linalg.matrix import org.apache.spark.mllib.linalg.singularvaluedecomposition import org.apache.spark.mllib.linalg.vector import scala.collection.immutable.list import java.io._ import java.nio.file.{paths, files} import java.nio.charset.standardcharsets import org.apache.spark.mllib.linalg.matrix import org.apache.spark.mllib.linalg.matrices import org.apache.spark.mllib.linalg.densematrix import org.apache.spark.mllib.linalg.distributed.indexedrowmatrix  def exportmatrix(matrix:array[double], filename: string, numcols:int, numrows:int) = {   val pw = new printwriter(filename)    for(columnindex <- 0 until numcols) {     pw.print("word"+columnindex)     if(columnindex == numcols - 1)         pw.println       else         pw.print(",")   }    for( rowindex <- 0 until numrows){     for(columnindex <- 0 until numcols) {       pw.print(matrix(numrows * columnindex + rowindex))       if(columnindex == numcols - 1)         pw.println       else         pw.print(",")     }    }   pw.flush   pw.close }  def exportrowmatrix(matrix:rdd[string], filename: string) = {   val pw = new printwriter(filename)   matrix.collect().foreach(line => pw.println(line))    pw.flush   pw.close }  val csv = sc.textfile("hdfs://myhost/sparse.csv").cache()  // original file  val data = csv.mappartitions(lines => {     val parser = new csvparser(' ')     lines.map(line => {       parser.parseline(line)     })   }).map(line => {     matrixentry(line(0).tolong - 1, line(1).tolong - 1 , line(2).toint)    } )  val indexedrowmatrix: indexedrowmatrix = new coordinatematrix(data).toindexedrowmatrix()   /*val mat: coordinatematrix =  val rowmatrix: rowmatrix = mat.torowmatrix()*/   val svd: singularvaluedecomposition[indexedrowmatrix, matrix] = indexedrowmatrix.computesvd(100, computeu = true)  val u: indexedrowmatrix = svd.u // u factor rowmatrix. val s: vector = svd.s // singular values stored in local dense vector. val v: matrix = svd.v // v factor local dense matrix.  val sarray: array[double] = s.toarray // done val varray: array[double] = v.toarray // done  val rdd = u.rows.map( x => x.vector.toarray.mkstring(","))  exportmatrix(sarray, "../s.csv", s.size, 1) exportmatrix(varray, "../v.csv", v.numcols.toint, v.numrows.toint) exportrowmatrix(rdd, "../u.csv")  val diag = matrices.diag(s)  val d = new densematrix(diag.numrows, diag.numcols, diag.toarray)  val multiplyresult = v.multiply(d)  val darray = multiplyresult.toarray exportmatrix(darray, "../d.csv", multiplyresult.numcols, multiplyresult.numrows) 

i've made this:

javasparkcontext sc = new javasparkcontext(sparkconfiguration.getsparkconfiguration()); javardd<string> csv = sc.textfile("hdfs://yoda/nlp/sparse.csv").cache();  system.out.println(csv.first()); //todo function parsing textfile rdd matrixentry rdd<matrixentry> data = null;  csv.mappartitions(new flatmapfunction<iterator<string>, string>() {      @override     public iterable<string> call(iterator<string> t)             throws exception {         // todo auto-generated method stub         return null;     }   });   indexedrowmatrix indexedrowmatrix = (new coordinatematrix(data)).toindexedrowmatrix(); singularvaluedecomposition<indexedrowmatrix, matrix> svd = indexedrowmatrix.computesvd(100, true, 0); indexedrowmatrix u = svd.u(); vector s = svd.s(); matrix v = svd.v();  double[] sarray = s.toarray(); double[] varray = v.toarray();  //todo function maping each row string value rdd<string> rdd = u.rows().map(null, null);  matrix diag = matrices.diag(s); densematrix d = new densematrix(diag.numrows(), diag.numcols(), diag.toarray()); densematrix multiplyresult = v.multiply(d); double[] darray = multiplyresult.toarray(); 

my questions are:

• how parse each line in matrix market format matrixentry? should done csv.mappartitions()
• how define function exportmatrix in java? identical normal java function?