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A Hardware-Accelerated Solution for Hierarchical Index-Based Merge-Join(Extended Abstract)

机译:基于分层索引的Merge-Join(扩展摘要)的硬件加速解决方案

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摘要

Hardware acceleration through field programmable gate arrays (FPGAs) has recently become a technique of growing interest for many data-intensive applications. Join query is one of the most fundamental database query types useful in relational database management systems. However, the available solutions so far have been beset by higher costs in comparison with other query types. In this paper, we develop a novel solution to accelerate the processing of sort-merge join queries with low match rates. Specifically, our solution makes use of hierarchical indexes to identify result-yielding regions in the solution space in order to take advantage of result sparseness. Further, in addition to one-dimensional equi-join query processing, our solution supports processing of multidimensional similarity join queries. Experimental results show that our solution is superior to the best existing method in a low match rate setting; the method achieves a speedup factor of 4.8 for join queries with a match rate of 5%.
机译:通过现场可编程门阵列(FPGA)的硬件加速最近成为许多数据密集型应用兴趣的技术。加入查询是在关系数据库管理系统中最有用的最基本的数据库查询类型之一。然而,与其他查询类型相比,到目前为止,到目前为止的可用解决方案已经通过更高的成本困扰。在本文中,我们开发了一种新的解决方案,以加速具有低匹配速率的排序合并加入查询的处理。具体而言,我们的解决方案利用分层索引来识别解决方案空间中的结果产生区域,以便利用结果稀疏性。此外,除了一维等级查询处理之外,我们的解决方案还支持处理多维相似度加入查询。实验结果表明,我们的解决方案优于低匹配率设置中的最佳现有方法;该方法对于加入率为5%的加入率,该方法实现了4.8的加速因子。

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