Processing of large amounts of data in data warehouses is increasingly being done in cluster architectures to achieve scalability. In this paper we look into the problem of ad hoc star join query processing in clusters architectures. We propose a new technique, the Star Hash Join (SHJ), which exploits a combination of multiple bit filter strategies in such architectures. SHJ is a generalization of the Pushed Down Bit Filters for clusters. The objectives of the technique are to reduce (ⅰ) the amount of data communicated, (ⅱ) the amount of data spilled to disk during the execution of intermediate joins in the query plan, and (ⅲ) amount of memory used by auxiliary data structures such as bit filters.
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机译：在集群架构中越来越多地完成数据仓库中大量数据以实现可扩展性。在本文中，我们研究了群体架构中的Ad Hoc Star加入查询处理的问题。我们提出了一种新的技术，星哈希连接（SHJ），它利用这种架构中的多个比特滤波器策略的组合。 SHJ是用于簇的推下位过滤器的泛化。该技术的目标是减少（Ⅰ）传送的数据量，（Ⅱ）在查询计划中的中间连接期间溢出到磁盘的数据量，（Ⅲ）辅助数据结构使用的内存量如误码器。
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