Title :
The ATLaS system and its powerful database language based on simple extensions of SQL
Author :
Wang, Haixun ; Zaniolo, Carlo
Author_Institution :
IBM Thomas J. Watson Res. Center, Hawthorne, NY, USA
Abstract :
A lack of power and extensibility in their query languages has seriously limited the generality of DBMSs and hampered their ability to support new applications domains, such as data mining. In this paper, we solve this problem by stream-oriented aggregate functions and generalized table functions which are definable by users in the SQL language itself, rather than in an external programming language. These simple extensions turn SQL into a powerful database language, which can express a wide range of applications, including recursive queries, ROLAP (relational online analytical processing) aggregates, time-series queries, stream-oriented processing and data-mining functions. The SQL extensions are implemented in ATLaS (Aggregate and Table Language and System)
Keywords :
SQL; data mining; database languages; relational databases; time series; ATLaS; DBMS generality; ROLAP aggregates; SQL; aggregate language; aggregate system; applications domains; data mining; database language; generalized table functions; query language extensions; recursive queries; relational online analytical processing; stream-oriented aggregate functions; stream-oriented processing; table language; table system; time-series queries; Aggregates; Computational modeling; Computer languages; Data engineering; Data mining; Database languages; Humidity; Power system modeling; Proposals;
Conference_Titel :
Data Engineering, 2002. Proceedings. 18th International Conference on
Conference_Location :
San Jose, CA
Print_ISBN :
0-7695-1531-2
DOI :
10.1109/ICDE.2002.994734
