Many-query join: efficient shared execution of relational joins on modern hardware

被引:0
|
作者
Darko Makreshanski
Georgios Giannikis
Gustavo Alonso
Donald Kossmann
机构
[1] ETH Zurich,Department of Computer Science
[2] Oracle Labs Zurich,undefined
[3] Microsoft Research,undefined
来源
The VLDB Journal | 2018年 / 27卷
关键词
RDBMS; OLAP; Analytics; Join; MQJoin; Shared join; Main memory; TPC-H; Xeon Phi; MCDRAM;
D O I
暂无
中图分类号
学科分类号
摘要
Database architectures typically process queries one at a time, executing concurrent queries in independent execution contexts. Often, such a design leads to unpredictable performance and poor scalability. One approach to circumvent the problem is to take advantage of sharing opportunities across concurrently running queries. In this paper, we propose many-query join (MQJoin), a novel method for sharing the execution of a join that can efficiently deal with hundreds of concurrent queries. This is achieved by minimizing redundant work and making efficient use of main-memory bandwidth and multi-core architectures. Compared to existing proposals, MQJoin is able to efficiently handle larger workloads regardless of the schema by exploiting more sharing opportunities. We also compared MQJoin to two commercial main-memory column-store databases. For a TPC-H-based workload, we show that MQJoin provides 2–5×\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\times $$\end{document} higher throughput with significantly more stable response times.
引用
收藏
页码:669 / 692
页数:23
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