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Multi-objective scheduling for real-time data warehouses

机译:实时数据仓库的多目标调度

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The issue of write-read contention is one of the most prevalent problems when deploying real-time data warehouses. With increasing load, updates are increasingly delayed and previously fast queries tend to be slowed down considerably. However, depending on the user requirements, we can improve the response time or the data quality by scheduling the queries and updates appropriately. If both criteria are to be considered simultaneously, we are faced with a so-called multi-objective optimization problem. We transformed this problem into a knapsack problem with additional inequalities and solved it efficiently. Based on our solution, we developed a scheduling approach that provides the optimal schedule with regard to the user requirements at any given point in time. We evaluated our scheduling in an extensive experimental study, where we compared our approach with the respective optimal schedule policies of each single optimization objective.
机译:在部署实时数据仓库时,读写冲突问题是最普遍的问题之一。随着负载的增加,更新越来越延迟,并且以前快速的查询往往会大大减慢速度。但是,根据用户要求,我们可以通过适当安排查询和更新来改善响应时间或数据质量。如果两个标准要同时考虑,我们将面临一个所谓的多目标优化问题。我们将此问题转化为具有其他不等式的背包问题,并有效地解决了该问题。基于我们的解决方案,我们开发了一种调度方法,该方法可以在任何给定的时间点针对用户需求提供最佳的调度。我们在一项广泛的实验研究中评估了我们的调度,在此我们将我们的方法与每个单个优化目标的各自最佳调度策略进行了比较。

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