Query Optimization on Distributed Database Dengue Fever by Minimizing Attribute Involvement
- 1 Dian Nuswantoro University, Indonesia
Abstract
Query optimization is an important task in a client/server environment of a distributed database, whereas a health epidemiologist data distribution based on DBD data on Geographic Information Systems (GIS). A proper method for a particular query process function is needed to generate query optimization on a distributed database. The query process requires important attention especially in distributed databases because the result of a cost-based query process is accessed by involving a number of attributes and visited sites. A query operation typically will search for data from various attributes in a scattered database table, although the processes do not require all table attributes. Query optimization requires minimum query operating costs (communication costs and access fees). The query cost can be optimized by separating attributes that are not required by the query. This can reduce the amount of communication and access time. The attributes should not be divided indiscriminately to obtain the best result of the query process and a vertical fragmentation method can be used to perform such attribute separation. In this research, attributes separation using vertical fragmentation method for a database health table is studied by comparing Bond Energy Algorithm (BEA) and Graphic Based Vertical Partitioning (GBVP) algorithm. The initial result of vertical fragmentation in both algorithms is the determination of types of attributes separated from a number of specific query process. The result of the separation of attributes from each algorithm is compared and evaluated using Partitioned Evaluator (PE) in order to achieve the access cost of several attributes. The results show that GBVP algorithm is more optimal for use in vertical table fragmentation process applied as query operation on distributed DBD database in a health field. The GBVP algorithm has less computational complexity, results a higher partition evaluator value and has lower query execution time than BEA.
DOI: https://doi.org/10.3844/jcssp.2018.466.476
Copyright: © 2018 Slamet Sudaryanto Nurhendratno, Sudaryanto, Fikri Budiman and Maryani Setyowati. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Query Distribution Process
- Vertical Fragmentation
- Optimization
- BEA
- GBVP
- PE