Aggregate function plays very important role in analyzing data of data warehouse. Analysis of such a huge data requires execution of complex queries such as iceberg and OLAP queries which consist of aggregate function. Improving the performance of such a complex query is the challenge in front of the researchers .Presently available iceberg query processing techniques faces the problem of empty bitwise operations, futile queue pushing and require more table scans. The model proposed in this research applies concept of look ahead matching on bitmap index of query attributes. Based on the threshold value the analysis of logical operation is done in advance. If result satisfies threshold condition then only remaining part will be evaluated otherwise it will be prune and declare as fruitless operation. In this way look ahead matching strategy overcome the problem of previous research. This research proposes framework for SUM and COUNT aggregate function.

Aggregate functions(MIN, MAX, SUM, COUNT); Bitwise operations (AND,OR,XOR); Data warehouse(DW); Iceberg query (IBQ); Look Ahead Matching(LAM) strategy

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