Providing A Compiler Technology-Based Alternative For Big Data Application Infrastructures

arXiv (Cornell University)

Abstract

The unprecedented growth of data volumes has caused traditional approaches to computing to be re-evaluated. This has started a transition towards the use of very large-scale clusters of commodity hardware and has given rise to the development of many new languages and paradigms for data processing and analysis. In this paper, we propose a compiler technology-based alternative to the development of many different Big Data application infrastructures. Key to this approach is the development of a single intermediate representation that enables the integration of compiler optimization and query optimization, and the re-use of many traditional compiler techniques for parallelization such as data distribution and loop scheduling. We show how the single intermediate can act as a generic intermediate for Big Data languages by mapping SQL and MapReduce onto this intermediate.

Authors 2

1. Kristian F. D. Rietveld Aachen

   Leiden University · University of Applied Sciences Leiden

   Affiliation as printed

   Leiden University Niels Bohrweg Leiden , The Netherlands

2. Harry A. G. Wijshoff Aachen

   Leiden University · University of Applied Sciences Leiden

   Affiliation as printed

   Leiden University Niels Bohrweg Leiden , The Netherlands