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An efficient processing of queries with joins and aggregate functions in data warehousing environment

机译:在数据仓库环境中使用联接和聚合函数高效处理查询

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It is very important to process efficiently expensive queries including joins and/or aggregate functions in a data warehousing environment since there resides an enormous volume of data and the processing of these queries takes a lot of time. In this paper, we propose a new method for processing the queries including both joins and aggregate functions. The proposed method performs grouping of dimension tables with group-by conditions at first and then processes joins by using bitmap join indices. This allows us to process aggregate functions by accessing fact tables only, thus it can reduce the serious performance degradation of existing methods. In order to show the superiority of the proposed method, we develop a cost model for both the proposed and the existing ones, and perform extensive simulations based on the TPC-H benchmark.
机译:在数据仓库环境中高效地处理昂贵的查询(包括联接和/或聚合函数)非常重要,因为其中存在大量数据,并且处理这些查询会花费大量时间。在本文中,我们提出了一种用于处理查询的新方法,包括联接和聚合函数。所提出的方法首先使用分组条件对维度表进行分组,然后使用位图联接索引处理联接。这允许我们仅通过访问事实表来处理聚合函数,从而可以减少现有方法的严重性能下降。为了展示所提出方法的优越性,我们针对所提议的方法和现有模型都开发了成本模型,并基于TPC-H基准进行了广泛的仿真。

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