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Row-wise Parallel Predicate Evaluation

机译:行式并行谓词评估

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摘要

Table scans have become more interesting recently due to greater use of ad-hoc queries and greater availability of multi-core, vector-enabled hardware. Table scan performance is limited by value representation, table layout, and processing techniques. In this paper we propose a new layout and processing technique for efficient one-pass predicate evaluation. Starting with a set of rows with a fixed number of bits per column, we append columns to form a set of banks and then pad each bank to a supported machine word length, typically 16, 32, or 64 bits. We then evaluate partial predicates on the columns of each bank, using a novel evaluation strategy that evaluates column level equality, range tests, IN-list predicates, and conjuncts of these predicates, simultaneously on multiple columns within a bank, and on multiple rows within a machine register. This approach outperforms pure column stores, which must evaluate the partial predicates one column at a time. We evaluate and compare the performance and representation overhead of this new approach and several proposed alternatives.
机译:由于越来越多地使用即席查询和多核,启用了矢量的硬件的可用性,表扫描最近变得越来越有趣。表扫描性能受到值表示,表布局和处理技术的限制。在本文中,我们提出了一种新的布局和处理技术,以进行有效的一次通过谓词评估。从每列固定位数的一组行开始,我们附加列以形成一组存储体,然后将每个存储体填充到支持的机器字长度,通常为16、32或64位。然后,我们使用一种新颖的评估策略对每个存储库的列进行局部谓词评估,该策略对列级别相等性,范围测试,IN列表谓词以及这些谓词的合取词同时在库中的多个列上以及在其中的多行上进行评估机器寄存器。此方法优于纯列存储,后者必须一次评估部分谓词一个列。我们评估并比较了这种新方法和几种建议的替代方法的性能和表示开销。

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