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A Time-Based Dynamic Synchronization Policy for Consolidated Database Systems1

机译:整合数据库系统的基于时间的动态同步策略1

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Data is becoming an increasingly important asset in today's organizations. Various challenges in the age of big data, such as high volume and high velocity, call for efficient database maintenance policies. This study focuses on deriving an optimal synchronization policy for consolidated database systems. By trading off synchronization cost with data staleness cost, we propose a time-based dynamic synchronization (TDS) policy, which evaluates the system state at predetermined checkpoints and synchronizes a consolidated database system only if given staleness thresholds are crossed. Although several database synchronization and knowledge refreshment policies have been proposed in the prior literature, the TDS policy retains their advantages and overcomes their inflexibility in that, under the TDS policy, system check and synchronization are easy to schedule, disruptions to business operations can be avoided, and synchronization is run only if necessary. Experimental results show that the TDS policy consistently outperforms benchmark policies, leading to substantial cost savings. In particular, the performance gap between the TDS policy and a static periodic policy is greater when data changes arrive less frequently but carry higher unit staleness costs, or when queries arrive more frequently and suffer higher unit staleness costs.
机译:在当今的组织中,数据正变得越来越重要。大数据时代的各种挑战,例如高容量和高速度,要求有效的数据库维护策略。这项研究着重于为统一数据库系统推导最佳同步策略。通过权衡同步成本和数据过时成本,我们提出了一种基于时间的动态同步(TDS)策略,该策略在预定的检查点评估系统状态并仅在超过给定的过时阈值时才同步统一数据库系统。尽管在先前的文献中已经提出了几种数据库同步和知识更新策略,但是TDS策略保留了它们的优点并克服了它们的灵活性,因为在TDS策略下,系统检查和同步易于安排,可以避免对业务运营的破坏,并且仅在必要时运行同步。实验结果表明,TDS策略始终优于基准策略,从而节省了大量成本。尤其是,当数据更改的到达频率较低但携带较高的单位过时成本时,或者当查询到达的频率较高且遭受较高的单位过时成本时,TDS策略和静态定期策略之间的性能差距会更大。

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