Adaptive Optimisation For Continuous Multi-Way Joins Over RDF Streams

Danh Le-Phuoc
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引用次数: 1

Abstract

The join operator is a core component of an RDF Stream Processing engine. The join operations usually dominate the processing load of a query execution plan. Due to the constantly updating nature of continuous queries, the query optimiser has to frequently change the optimal execution plan for a query. However, optimising the join executing plan for every execution step might be prohibitively expensive, hence, dynamic optimisation of continuous join operations is still a challenging problem so far. Therefore, this paper proposes the first adaptive optimisation approach towards this problem in the context of RDF Stream Processing. The approach comes with two dynamic cost-based optimisation algorithms which use a light-weight process to search for the best execution plan for every execution step. The experiments show the encouraging results towards this direction.
RDF流上连续多路连接的自适应优化
连接操作符是RDF流处理引擎的核心组件。连接操作通常主导查询执行计划的处理负载。由于连续查询具有不断更新的特性,查询优化器必须经常更改查询的最佳执行计划。然而,为每个执行步骤优化连接执行计划的成本可能过高,因此,到目前为止,连续连接操作的动态优化仍然是一个具有挑战性的问题。因此,本文在RDF流处理的背景下提出了针对该问题的第一个自适应优化方法。该方法采用两种基于成本的动态优化算法,使用轻量级过程为每个执行步骤搜索最佳执行计划。实验表明,这一方向取得了令人鼓舞的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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