Title :
Ω-storage: a self organizing multi-attribute storage technique for very large main memories
Author :
Karlsson, Jonas S. ; Kersten, Martin L.
Author_Institution :
Centre for Math. & Comput. Sci., Amsterdam, Netherlands
Abstract :
Main memory storage is continuously improving, both in its price and its capacity. With this comes new storage problems and new directions of possible usage. Several main-memory database systems are now becoming commercially available. The hot areas for their deployment include boosting the performance of Web-enabled systems, such as search engines, and electronic auctioning systems. We present a novel data storage structure - the Ω-storage structure, a high-performance data structure, to index very large amounts of multi-attribute data. The experiments show excellent performance for point retrieval and highly efficient pruning for pattern searches. It provides the balanced storage previously achieved by random kd-trees, but avoids their increased pattern-match search times by an effective assignment of attribute bits to the index. Moreover, it avoids the sensitivity of the kd-tree to the insertion order
Keywords :
data structures; database indexing; pattern matching; search engines; self-organising storage; software performance evaluation; very large databases; Ω-storage structure; World Wide Web-enabled systems; attribute bit assignment; electronic auctioning systems; high-performance data structure; insertion order; main-memory database systems; multi-attribute data indexing; pattern search pruning; pattern-match search time; performance; point retrieval; random kd-trees; search engines; self-organizing multi-attribute storage technique; very large main memories; Boosting; Computer science; Data mining; Data structures; Indexing; Mathematics; Memory; Ores; Organizing; Pattern matching;
Conference_Titel :
Database Conference, 2000. ADC 2000. Proceedings. 11th Australasian
Conference_Location :
Canberra, ACT
Print_ISBN :
0-7695-0528-7
DOI :
10.1109/ADC.2000.819814