Multi-wavelength astronomical studies require cross-identification of detections of the same celestial objects in multiple catalogs based on spherical coordinates and other properties. Because of the large data volumes and spherical geometry, the symmetric N-way association of astronomical detections is a computationally intensive problem, even when sophisticated indexing schemes are used to exclude obviously false candidates. Legacy astronomical catalogs already contain detections of more than a hundred million objects while ongoing and future surveys will produce catalogs of billions of objects with multiple detections of each at different times. One time, pair-wise cross-identification of these large catalogs is not sufficient for many astronomical scenarios. Consequently, a novel system is necessary that can cross-identify multiple catalogs on-demand, efficiently and reliably. In this paper, we present our solution based on a cluster of commodity servers and ordinary relational databases. The cross-identification problems are formulated in a language based on SQL, but extended with special clauses. These special queries are partitioned spatially by coordinate ranges and compiled into a complex workflow of ordinary SQL queries. Workflows are then executed in a parallel framework using a cluster of servers hosting identical mirrors of the same data sets. © 2012 Springer-Verlag.
CITATION STYLE
Dobos, L., Budavári, T., Li, N., Szalay, A. S., & Csabai, I. (2012). SkyQuery: An implementation of a parallel probabilistic join engine for cross-identification of multiple astronomical databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7338 LNCS, pp. 159–167). https://doi.org/10.1007/978-3-642-31235-9_10
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