Data Mining and Warehouse

Data Mining and Warehouse

Abstract

Most enterprises using Data Warehouse do not suffer from a lack of data but from an overabundance of data. The problem is difficulty in accessing the data for decision support applications. Such applications involve complex queries. Query performance in such an environment is critical because decision support applications often require interactive query response time. Data Warehouses are updated infrequently, so it becomes possible to improve query performance by caching sets retrieved by queries in addition to query execution plans. In this paper we describe an algorithm for finding frequent item sets and the problem associated with it. We suggest two algorithms that are well suited for sets retrieved by queries as compared to traditional LRU in Data Warehousing environment. The two algorithms are Cache Replacement algorithm (LNC-R) and Cache Admission algorithm (LNC-A). These algorithms achieve a substantial performance improvement in a decision support environment when compared to a traditional LRU replacement algorithm.