Abstract: The growth of World Wide Web requires large database the organizations are using large volume of data. A number of commercial and research systems application required power and scalability of parallel query processing. Web-based applications, such as e-commerce sites, are faced with highly changeable workloads. The number of customers browsing and purchasing items varies through-out the day and business managers can further complicate the workload by requesting complex reports on sales data. This means the load on a database system can vary considerably with a sudden arrival of requests or a request involving a complex query. If there are too many requests operating in the DBMS concurrently, then resources are stressed and performance drops. To keep the DBMS's performance consistent across varying loads, a load control system can be used. We focus on scheduling of queries for parallel database systems by dividing the workload into batches. We propose scheduling algorithms which exploit the common operations within the queries in a batch. One scheduling algorithm cannot optimally meet an arbitrary set of Quality of Service (QoS) requirements. Therefore, to meet unique features of specific monitoring applications, an adaptive strategy selector guidable by QoS requirements was developed. The adaptive algorithm is general, being able to use any scheduling algorithm and to react to any combination of quality of service preferences.
Title: Customized Stream Query Scheduling In Parallel Database System
Author: Mr. Niraj Kumar, Mr. Mahadeo Prasad, Mr. Rajesh Singh
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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