Abstract
In order to perform an effective cross-matching computation on an enormous amount of text-file-based astronomical observation data, this study proposes an algorithm based on the MapReduce distributed architecture. Such an approach not only greatly enhances the computation speed, but also provides a data structure for storing the computation results. It provides a satisfactory solution not only for cross-matching the entirety of the data, but also for simply updating the changes.
Author
Kuei-sheng Lee, Meng-feng Tsai, Yuji Urata, Kui-yun Huang, Chi-sheng Huang
Journal
Proceedings of the ASE BigData & SocialInformatics 2015
Paper Publication Date
October 2015
Paper Type
Astroinformatics