Warehouse views need to be updated when source data changes. Due to the constantly increasing size of warehouses and the rapid rates of change, there is increasing pressure to reduce the time taken for updating the warehouse views. In this paper we focus on reducing this "update window" by minimizing the work required to compute and install a batch of updates. Various strategies have been proposed in the literature for updating a single warehouse view. These algorithms typically cannot be extended to come up with good strategies for updating an entire set of views. We develop an efficient algorithm that selects an optimal update strategy for any single warehouse view. Based on this algorithm, we develop an algorithm for selecting strategies to update a set of views. The performance of these algorithms is studied with experiments involving warehouse views based on TPC-D queries.
当源数据更改时,仓库视图需要更新。由于仓库规模的不断增长和变化速度的迅猛,减少减少更新仓库视图所花费的时间的压力越来越大。在本文中,我们着重于通过最小化计算和安装一批更新所需的工作来减少此“更新窗口”。文献中已经提出了各种策略来更新单个仓库视图。这些算法通常无法扩展以提供更新整个视图集的良好策略。我们开发了一种有效的算法,可以为任何单个仓库视图选择最佳的更新策略。基于此算法,我们开发了一种用于选择更新视图集的策略的算法。通过涉及基于TPC-D查询的仓库视图的实验,研究了这些算法的性能。 P>
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