Dr. Junko Furusawa Profile

Dr. Junko Furusawa

at National Astronomical Observatory of Japan

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Proceedings Article | 13 December 2020 Poster + Presentation + Paper

Innovative astronomical applications with a new-generation relational database

Junko Furusawa, Tadafumi Takata, Hisanori Furusawa, Takafumi Ootsubo, Shohei Aoyama, Yoshihiko Yamada, Yuki Okura, Makoto Onizuka

Proceedings Volume 11452, 1145226 (2020) https://doi.org/10.1117/12.2561201

KEYWORDS: Databases, Astronomy, Data processing, Data archive systems, Telescopes, Computer programming, Calibration

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Database technology has been developing to exploit the next-generation hardware in the era of big data processing. At the same time, astronomical data size has been steadily increasing, and astronomical source catalogs obtained from largescale surveys with a wide-field camera, such as Subaru/Hyper Suprime-Cam (HSC), are a good test bench for evaluating the new database technology with a large data set. Such archive systems often employ a highly versatile relational database management system (RDBMS), but reducing the time required for data transaction and complex analysis has come to an important challenge. To tackle this difficulty, we aim to develop astronomical applications with a new catalog database using a next-generation RDBMS technology, where the query engine is designed to efficiently use computing infrastructures for processing big data. Demonstrations with science applications are essential to evaluate the new database. We verify query performance with the current HSC source catalog. For application to huge astronomical catalog databases, we are pursuing and verifying the capabilities of new database technologies. It will, in turn, enable fast ad hoc search and efficient detection of a wide range of variable events with the technology. Our pilot tests using typical astronomical queries on a cluster system shows significant improvements in response times with the aid of distributed query engines. We report performance of the test database for typical astronomical queries, and discuss optimizing the schema based on query workloads.

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