Spark-Based Large-Scale Matrix Inversion for Big Data Processing

Towards Large Scale Environmental Data Processing with Apache Spark

Currently available environmental datasets are either manually constructed by professionals or automatically generated from the observations provided by sensing devices. Usually, the former are modelled and recorded with traditional general-purpose relational technologies, whereas the latter require more specific scientific array formats and tools. Declarative data processing technologies are a...

A Big Data Platform for Large Scale Event Processing

a reducer function that processes intermediate values associated with the same intermediate key. For the example of simply counting the number of terms occurring across the entire collection of documents, the mapper takes as input a document URL (key) and the document content (value) and outputs pairs of term and term count in the document. The reducer then aggregates all term counts of a term ...

A Big Data Platform for Large Scale Event Processing

a reducer function that processes intermediate values associated with the same intermediate key. For the example of simply counting the number of terms occurring across the entire collection of documents, the mapper takes as input a document URL (key) and the document content (value) and outputs pairs of term and term count in the document. The reducer then aggregates all term counts of a term ...

CONSTRAINED BIG BANG-BIG CRUNCH ALGORITHM FOR OPTIMAL SOLUTION OF LARGE SCALE RESERVOIR OPERATION PROBLEM

A constrained version of the Big Bang-Big Crunch algorithm for the efficient solution of the optimal reservoir operation problems is proposed in this paper. Big Bang-Big Crunch (BB-BC) algorithm is a new meta-heuristic population-based algorithm that relies on one of the theories of the evolution of universe namely, the Big Bang and Big Crunch theory. An improved formulation of the algorithm na...

Large Scale and Big Data - Processing and Management