public class IndexedRowMatrix extends Object implements DistributedMatrix
DistributedMatrix
with
indexed rows.
Constructor and Description |
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IndexedRowMatrix(RDD<IndexedRow> rows)
Alternative constructor leaving matrix dimensions to be determined automatically.
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IndexedRowMatrix(RDD<IndexedRow> rows,
long nRows,
int nCols) |
Modifier and Type | Method and Description |
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Matrix |
computeGramianMatrix()
Computes the Gramian matrix
A^T A . |
SingularValueDecomposition<IndexedRowMatrix,Matrix> |
computeSVD(int k,
boolean computeU,
double rCond)
Computes the singular value decomposition of this IndexedRowMatrix.
|
IndexedRowMatrix |
multiply(Matrix B)
Multiply this matrix by a local matrix on the right.
|
long |
numCols()
Gets or computes the number of columns.
|
long |
numRows()
Gets or computes the number of rows.
|
RDD<IndexedRow> |
rows() |
breeze.linalg.DenseMatrix<Object> |
toBreeze()
Collects data and assembles a local dense breeze matrix (for test only).
|
RowMatrix |
toRowMatrix()
Drops row indices and converts this matrix to a
RowMatrix . |
public IndexedRowMatrix(RDD<IndexedRow> rows, long nRows, int nCols)
public IndexedRowMatrix(RDD<IndexedRow> rows)
public RDD<IndexedRow> rows()
public long numCols()
DistributedMatrix
numCols
in interface DistributedMatrix
public long numRows()
DistributedMatrix
numRows
in interface DistributedMatrix
public RowMatrix toRowMatrix()
RowMatrix
.public SingularValueDecomposition<IndexedRowMatrix,Matrix> computeSVD(int k, boolean computeU, double rCond)
The cost and implementation of this method is identical to that in
RowMatrix
With the addition of indices.
At most k largest non-zero singular values and associated vectors are returned. If there are k such values, then the dimensions of the return will be:
U is an IndexedRowMatrix
of size m x k that
satisfies U'U = eye(k),
s is a Vector of size k, holding the singular values in descending order,
and V is a local Matrix of size n x k that satisfies V'V = eye(k).
k
- number of singular values to keep. We might return less than k if there are
numerically zero singular values. See rCond.computeU
- whether to compute UrCond
- the reciprocal condition number. All singular values smaller than rCond * sigma(0)
are treated as zero, where sigma(0) is the largest singular value.public IndexedRowMatrix multiply(Matrix B)
B
- a local matrix whose number of rows must match the number of columns of this matrixpublic Matrix computeGramianMatrix()
A^T A
.public breeze.linalg.DenseMatrix<Object> toBreeze()
DistributedMatrix
toBreeze
in interface DistributedMatrix