Columnstore and B plus tree - Are Hybrid Physical Designs Important?

被引:9
作者
Dziedzic, Adam [1 ,2 ]
Wang, Jingjing [1 ,3 ]
Das, Sudipto [1 ]
Ding, Bolin [1 ]
Narasayya, Vivek R. [1 ]
Syamala, Manoj [1 ]
机构
[1] Microsoft Res, Redmond, WA 98052 USA
[2] Univ Chicago, Chicago, IL 60637 USA
[3] Univ Washington, Seattle, WA 98195 USA
来源
SIGMOD'18: PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA | 2018年
关键词
Columnstore; B plus tree; Hybrid physical designs; operational analytics; hybrid transactional and analytical processing;
D O I
10.1145/3183713.3190660
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Commercial DBMSs, such as Microsoft SQL Server, cater to diverse workloads including transaction processing, decision support, and operational analytics. They also support variety in physical design structures such as B+ tree and columnstore. The benefits of B+ tree for OLTP workloads and columnstore for decision support workloads are well-understood. However, the importance of hybrid physical designs, consisting of both columnstore and B+ tree indexes on the same database, is not well-studied - a focus of this paper. We first quantify the trade-offs using carefully-crafted micro-benchmarks. This micro-benchmarking indicates that hybrid physical designs can result in orders of magnitude better performance depending on the workload. For complex real-world applications, choosing an appropriate combination of columnstore and B+ tree indexes for a database workload is challenging. We extend the Database Engine Tuning Advisor for Microsoft SQL Server to recommend a suitable combination of B+ tree and columnstore indexes for a given workload. Through extensive experiments using industry-standard benchmarks and several real-world customer workloads, we quantify how a physical design tool capable of recommending hybrid physical designs can result in orders of magnitude better execution costs compared to approaches that rely either on columnstore-only or B+ tree-only designs.
引用
收藏
页码:177 / 190
页数:14
相关论文
共 44 条
[1]  
Abadi D., 2006, P ACM SIGMOD INT C M, P671, DOI [10.1145/1142473.1142548, DOI 10.1145/1142473.1142548]
[2]  
Abadi D, 2012, FOUND TRENDS DATABAS, V5, P198, DOI 10.1561/1900000024
[3]  
Abadi Daniel J, 2008, SIGMOD, P967, DOI [10.1145/1376616.1376712, DOI 10.1145/1376616.1376712]
[4]  
Agrawal S., 2004, P 30 INTERATIONALCON, P1110, DOI [10.1145/1066157.1066292, DOI 10.1016/B978-012088469-8.50097-8]
[5]  
[Anonymous], 2005, VLDB
[6]  
[Anonymous], 2017, MICROSOFT SQL SERVER
[7]  
[Anonymous], 2018, OR DAT IN MEM OR DAT
[8]   Bridging the Archipelago between Row-Stores and Column-Stores for Hybrid Workloads [J].
Arulraj, Joy ;
Pavlo, Andrew ;
Menon, Prashanth .
SIGMOD'16: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON MANAGEMENT OF DATA, 2016, :583-598
[9]  
Bayer R., 2002, SOFTWARE PIONEERS, P245
[10]  
Boncz Peter A., 2005, CIDR