AEfficient Processing of Queries using Filtered Bitmap Index with Multi-Join Multiple Set Predicates
A. Regita Thangam1, S.John Peter2
1A. Regita Thangam, Research Scholar, Department of Computer Science, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, India.
2S. John Peter, Associate Professor & Head, Department of Computer Science, St.Xavier’s College, Palayamkottai, Tamil Nadu, India.
Manuscript received on 05 September 2019 | Revised Manuscript received on 29 September 2019 | Manuscript Published on 29 June 2020 | PP: 363-370 | Volume-8 Issue-10S2 August 2019 | Retrieval Number: J106508810S19/2019©BEIESP | DOI: 10.35940/ijitee.J1065.08810S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Data Warehousing, Time Complexity, Multiple set Predicates, Multi-join Query, Query Processing, Optimizing, Level Number.
Scope of the Article: Computer Science and Its Applications