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Design and comparative analysis of DSS queries in distributed environment

机译:分布式环境中DSS查询的设计与比较分析

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Query processing and its optimization is one of the major aspects of distributed database system. The research has exposed that the design of a query and its execution technique plays an important role in the optimization of a query. There are two major categories of distributed queries in distributed database system known as Decision Support system (DSS) queries and Online Transaction Processing (OLTP) queries. In this paper the prime focus is on design and analysis of DSS queries. The selected set of DSS queries are simulated by using exhaustive enumerative technique and genetic approach under serial and parallel processing environment. The simulation results show that an exhaustive enumeration approach provides optimized solution but takes huge time for complex DSS queries (Hours, Days, Month or even Years), hence it is infeasible to implement this approach for optimizing a set of DSS queries. On the other hand genetic algorithms optimize DSS Queries very quickly but show loss in accuracy and quality of solution as compare to exhaustive enumerative approach. Further the parallel execution of the different sub operations of a DSS query significantly reduces the total cost of system resources.
机译:查询处理及其优化是分布式数据库系统的主要方面之一。该研究暴露了查询的设计和其执行技术在查询的优化中起着重要作用。分布式数据库系统中有两种主要类别的分布式查询,称为决策支持系统(DSS)查询和在线事务处理(OLTP)查询。本文本文主要重点是对DSS查询的设计和分析。通过使用串行和并行处理环境下的穷举枚举技术和遗传方法模拟所选的DSS查询。仿真结果表明,详尽的枚举方法提供了优化的解决方案,但对于复杂的DSS查询(小时,天,月甚至年)需要大量时间,因此实现这种方法是为了优化一组DSS查询而无法使用。另一方面,遗传算法非常快速地优化DSS查询,但在解决方案的准确性和质量损失,与详尽的枚举方法相比。此外,DSS查询的不同子操作的并行执行显着降低了系统资源的总成本。

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