Large-Scale Query and XMatch, Entering the Parallel Zone
Databases
2007-05-23 v1 Computational Engineering, Finance, and Science
Abstract
Current and future astronomical surveys are producing catalogs with millions and billions of objects. On-line access to such big datasets for data mining and cross-correlation is usually as highly desired as unfeasible. Providing these capabilities is becoming critical for the Virtual Observatory framework. In this paper we present various performance tests that show how using Relational Database Management Systems (RDBMS) and a Zoning algorithm to partition and parallelize the computation, we can facilitate large-scale query and cross-match.
Keywords
Cite
@article{arxiv.cs/0701167,
title = {Large-Scale Query and XMatch, Entering the Parallel Zone},
author = {Maria A. Nieto-Santisteban and Aniruddha R. Thakar and Alexander S. Szalay and Jim Gray},
journal= {arXiv preprint arXiv:cs/0701167},
year = {2007}
}
Comments
Astronomical Data Analysis Software and Systems XV in San Lorenzo de El Escorial, Madrid, Spain, October 2005, to appear in the ASP Conference Series