Efficient processing of queries using filtered bitmap index with multi-join multiple set predicates

Abstract

Efficient query process is an essential task in numerous environments that relate large sum of information. The performance degradation occurs when the sum of information is increased. It will further degrade when the amount of joins in the queries is increased. These problems emphasize a need for good query processing approach. Thus, in this report, we take a various method to optimize the multi-join query with multiple set predicates in Data warehousing environment. So we have proposed an effective algorithm as Filtered Bitmap Index with multi-join multiple set predicates processing approach and examine the time complexity on huge data set with multiple tables. In this approach, the multi-join query is processed by selecting the tabular array based on their level number from lower to higher. A simple rewritten query was created from the given complex query exploitation uses the lowest level table and executed. If the result exists then only continue the join processing in the rewritten query, by taking the next lower level table from the complex query and do the execution. The ratio of our technique is to demonstrated with moving experiment using WorldCup98 and TPC-H benchmark datasets.