SciQL, Bridging the Gap between Science and Relational DBMS
Scientific discoveries increasingly rely on the ability to efficiently grind massive amounts of experimental data using database technologies. To bridge the gap between the needs of the Data-Intensive Research fields and the current DBMS technologies, we propose SciQL (pronounced as ‘cycle’), the first SQL-based query language for scientific applications with both tables and arrays as first class citizens. It provides a seamless symbiosis of array-, set- and sequence- interpretations. A key innovation is the extension of value-based grouping of SQL:2003 with structural grouping, i.e., fixed-sized and unbounded groups based on explicit relationships between elements positions. This leads to a generalisation of window-based query processing with wide applicability in science domains. This paper describes the main language features of SciQL and illustrates it using time-series concepts.
|Keywords||sciql, array query language, scientific data, time series data processing|
|THEME||Information (theme 2)|
|Publisher||ACM New York, NY, USA|
|Conference||International Database Engineering and Applications Symposium|
Zhang, Y, Kersten, M.L, Ivanova, M.G, & Nes, N.J. (2011). SciQL, Bridging the Gap between Science and Relational DBMS. ACM New York, NY, USA.