DWMiner: A Tool for Mining Frequent Itemsets Efficiently in Data Warehouses
Bruno Almentero (Federal University of Rio de Janeiro, Computer Science Department, COPPE, Brazil)Alexandre Evsukoff (Federal University of Rio de Janeiro, Civil Engineering Departament, COPPE, Brazil)
Marta Mattoso (Federal University of Rio de Janeiro, Computer Science Department, COPPE, Brazil)
Abstract:
This work presents DWMiner, an association rules efficient mining tool to process data directly over a relational DBMS data warehouse. DWMiner executes the Apriori algorithm as SQL queries in parallel, using a database PC Cluster middleware developed for SQL query optimization in OLAP applications. DWMiner combines intra- and inter-query parallelism in order to reduce the total time needed to find frequent item sets directly from a data warehouse. DWMiner was tested using the BMS-Web-View1 database from KDD-Cup 2000 and obtained linear and super-linear speedups.
Keywords:
Cluster and Grid Computing, Parallel and Distributed Computing,
