NDLI: Integrating Association Rule Mining with Relational Database Systems: Alternatives and Implications

Content Provider	Springer Nature Link
Author	Sarawagi, Sunita Thomas, Shiby Agrawal, Rakesh
Copyright Year	2000
Abstract	Data mining on large data warehouses is becoming increasingly important. In support of this trend, we consider a spectrum of architectural alternatives for coupling mining with database systems. These alternatives include: loose-coupling through a SQL cursor interface; encapsulation of a mining algorithm in a stored procedure; caching the data to a file system on-the-fly and mining; tight-coupling using primarily user-defined functions; and SQL implementations for processing in the DBMS. We comprehensively study the option of expressing the mining algorithm in the form of SQL queries using Association rule mining as a case in point. We consider four options in SQL-92 and six options in SQL enhanced with object-relational extensions (SQL-OR). Our evaluation of the different architectural alternatives shows that from a performance perspective, the Cache option is superior, although the performance of the SQL-OR option is within a factor of two. Both the Cache and the SQL-OR approaches incur a higher storage penalty than the loose-coupling approach which performance-wise is a factor of 3 to 4 worse than Cache. The SQL-92 implementations were too slow to qualify as a competitive option. We also compare these alternatives on the basis of qualitative factors like automatic parallelization, development ease, portability and inter-operability. As a byproduct of this study, we identify some primitives for native support in database systems for decision-support applications.
Starting Page	89
Ending Page	125
Page Count	37
File Format	PDF
ISSN	13845810
Journal	Data Mining and Knowledge Discovery
Volume Number	4
Issue Number	2-3
e-ISSN	1573756X
Language	English
Publisher	Kluwer Academic Publishers
Publisher Date	2000-01-01
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Data Structures, Cryptology and Information Theory Information Storage and Retrieval Computing Methodologies Artificial Intelligence (incl. Robotics) Statistics for Engineering, Physics, Computer Science, Chemistry & Geosciences Statistics
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Information Systems Computer Science Applications

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