org.apache.sysds.hops.estim

Class EstimatorSample

java.lang.Object

org.apache.sysds.hops.estim.SparsityEstimator

org.apache.sysds.hops.estim.EstimatorSample

public class EstimatorSample
extends SparsityEstimator

This estimator implements an approach based on row/column sampling Yongyang Yu, MingJie Tang, Walid G. Aref, Qutaibah M. Malluhi, Mostafa M. Abbas, Mourad Ouzzani: In-Memory Distributed Matrix Computation Processing and Optimization. ICDE 2017: 1047-1058 The basic idea is to draw random samples of aligned columns SA and rows SB, and compute the output nnz as max(nnz(SA_i)*nnz(SB_i)). However, this estimator is biased toward underestimation as the maximum is unlikely sampled and collisions are not accounted for. Accordingly, we also support an extended estimator that relies on similar ideas for element-wise addition as the other estimators.

Nested Class Summary

Nested classes/interfaces inherited from class org.apache.sysds.hops.estim.SparsityEstimator

SparsityEstimator.OpCode

Field Summary

Fields inherited from class org.apache.sysds.hops.estim.SparsityEstimator

MIN_PAR_THRESHOLD, MULTI_THREADED_BUILD, MULTI_THREADED_ESTIM

Constructor Summary

Constructors

Constructor and Description
EstimatorSample()
EstimatorSample(double sampleFrac)
EstimatorSample(double sampleFrac, boolean extended)

Method Summary

Modifier and Type	Method and Description
double	estim(MatrixBlock m1, MatrixBlock m2) Estimates the output sparsity for a single matrix multiplication.
double	estim(MatrixBlock m1, MatrixBlock m2, SparsityEstimator.OpCode op) Estimates the output sparsity for a given binary operation.
double	estim(MatrixBlock m, SparsityEstimator.OpCode op) Estimates the output sparsity for a given unary operation.
DataCharacteristics	estim(MMNode root) Estimates the output sparsity of a DAG of matrix multiplications for the given operator graph of a single root node.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

EstimatorSample

public EstimatorSample()

EstimatorSample

public EstimatorSample(double sampleFrac)

EstimatorSample

public EstimatorSample(double sampleFrac,
                       boolean extended)

Method Detail

estim

public DataCharacteristics estim(MMNode root)

Description copied from class: SparsityEstimator

Estimates the output sparsity of a DAG of matrix multiplications for the given operator graph of a single root node.

Specified by:

estim in class SparsityEstimator

Parameters:

root - DAG root node

Returns:

output data characteristics

estim

public double estim(MatrixBlock m1,
                    MatrixBlock m2)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a single matrix multiplication.

Specified by:

estim in class SparsityEstimator

Parameters:

m1 - left-hand-side operand

m2 - right-hand-side operand

Returns:

sparsity

estim

public double estim(MatrixBlock m1,
                    MatrixBlock m2,
                    SparsityEstimator.OpCode op)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a given binary operation.

Specified by:

estim in class SparsityEstimator

Parameters:

m1 - left-hand-side operand

m2 - right-hand-side operand

op - operator code

Returns:

sparsity

estim

public double estim(MatrixBlock m,
                    SparsityEstimator.OpCode op)

Description copied from class: SparsityEstimator

Estimates the output sparsity for a given unary operation.

Specified by:

estim in class SparsityEstimator

Parameters:

m - left-hand-side operand

op - operator code

Returns:

sparsity