Fragment and replicate algorithms for non-equi-join evaluation on Smart Disks

Vassilis Stoumpos, A. Delis
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引用次数: 2

Abstract

The predicates in a non-equi-join can be anything but equality relations. Non-equi-join predicates can be as simple as an inequality expression between two join relation fields, or as complex as a user-defined function that carries out arbitrary complex comparisons. The nature of non-equi-join calls for predicate evaluation over all possible combinations of tuples in a two-way join. In this paper, we consider the family of fragment and replicate join algorithms that facilitates non-equijoin evaluation and adapt it in a Smart Disk environment. We use Smart Disk as an umbrella term for a variety of different storage devices featuring an embedded processor that may offload data processing from the main CPU. Our approach partially replicates one of the join relations in order to harness all processing capacity in the system. However, partial replication introduces problems with synchronizing concurrent algorithmic steps, load balancing, and selection among different join evaluation alternatives.We use a processing model to avoid performance pitfalls and autonomously select algorithm parameters. Through experimentation we find our proposed algorithms to utilize all system resources and, thus, yield better performance.
智能硬盘非等联接评估的分片和复制算法
非相等连接中的谓词可以是任何关系,但不能是相等关系。非等连接谓词可以像两个连接关系字段之间的不等式表达式一样简单,也可以像执行任意复杂比较的用户定义函数一样复杂。非等联接的性质要求对双向联接中元组的所有可能组合进行谓词计算。在本文中,我们考虑了一系列片段和复制连接算法,这些算法促进了非等连接评估,并将其应用于智能磁盘环境。我们使用智能磁盘作为各种不同存储设备的总称,这些设备具有嵌入式处理器,可以从主CPU卸载数据处理。我们的方法部分地复制了其中一个连接关系,以便利用系统中的所有处理能力。但是,部分复制引入了同步并发算法步骤、负载平衡以及在不同连接求值备选方案之间进行选择等问题。我们使用处理模型来避免性能缺陷并自主选择算法参数。通过实验,我们发现我们提出的算法能够充分利用系统资源,从而产生更好的性能。
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