2007/01/26 by Maria A. Nieto-Santisteban, M. A. Nieto‐Santisteban, Nieto-Santisteban, Maria A. +6
Computer Science · #Advanced Database Systems and Queries #Computational Engineering #Data Mining Algorithms and Applications #Databases (cs.DB) #FOS: Computer and information sciences #Finance #Mobile Agent-Based Network Management #and Science (cs.CE) #cs.CE #cs.DB
paper · pdf · doi:10.48550/arxiv.cs/0701167
Astronomical Data Analysis Software and Systems XV in San Lorenzo de El Escorial, Madrid, Spain, October 2005, to appear in the ASP Conference Series
arxiv created 2007/01/26 · openalex publication_date 2007/01/26 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.