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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ivanova, Milena Nes, Niels Kersten, Martin Zhang, Ying |
| Abstract | 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. |
| Starting Page | 124 |
| Ending Page | 133 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450306270 |
| DOI | 10.1145/2076623.2076639 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2011-09-21 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Scientific databases Array query language Sciql Time series Array database |
| Content Type | Text |
| Resource Type | Article |
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