I have a system of linear equations in the form of Ax = b to solve in Spark.
A is n by n b is n by 1 I represent 'A' in the form of IndexedRowMatrix or RowMatrix and 'b' in the form of DenseMatrix or DenseVector. How can I solve this system to calculate the 'x' vector? If the suggested solution is Cholesky Decomposition <https://github.com/apache/spark/blob/master/mllib/src/main/scala/org/apache/spark/mllib/linalg/CholeskyDecomposition.scala> , would you please guide me through doing it as it is not part of the public API ? For example if the original matrix A is: 1,2,3,4 2,1,5,6 3,5,1,7 4,6,7,1 and b is: 5,6,7,8 What is passed as argument to the "solve" method ? Any other solution other than inversing 'A' would be very helpful. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Solve-system-of-linear-equations-in-Spark-tp27847.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe e-mail: user-unsubscr...@spark.apache.org
