April 2017
Intermediate to advanced
532 pages
12h 39m
English
book
Machine Learning with Spark - Second Edition
by Rajdeep Dua, Brian O'Neill, Stephen Boesch, Manpreet Singh Ghotra, Nick Pentreath
Content preview from Machine Learning with Spark - Second Edition
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Matrix in Spark
A local matrix in Spark has integer-typed row and column indices. Values are double-typed. All the values are stored on a single machine. MLlib supports the following matrix types:
- Dense matrices: Matrices where entry values stored are in a single, double array in a column-major order.
- Sparse matrices: Matrices where non-zero entry values are stored in the CSC format in a column-major order. For example, the following dense matrix is stored in a one-dimensional array [2.0, 3.0, 4.0, 1.0, 4.0, 5.0] for the matrix size (3, 2):
2.0 3.0
4.0 1.0
4.0 5.0
This is an example of a dense and sparse matrix:
val dMatrix: Matrix = Matrices.dense(2, 2, Array(1.0, 2.0, 3.0, 4.0)) println("dMatrix: n" + dMatrix) val sMatrixOne: Matrix ...Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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