Fast Foreign-Key Detection in Microsoft SQL Server PowerPivot for Excel

被引:15
作者
Chen, Zhimin [1 ]
Narasayya, Vivek [1 ]
Chaudhuri, Surajit [1 ]
机构
[1] Microsoft Res, Washington, DC 98052 USA
来源
PROCEEDINGS OF THE VLDB ENDOWMENT | 2014年 / 7卷 / 13期
关键词
D O I
10.14778/2733004.2733014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Microsoft SQL Server PowerPivot for Excel, or PowerPivot for short, is an in-memory business intelligence (BI) engine that enables Excel users to interactively create pivot tables over large data sets imported from sources such as relational databases, text files and web data feeds. Unlike traditional pivot tables in Excel that are defined on a single table, PowerPivot allows analysis over multiple tables connected via foreign-key joins. In many cases however, these foreign-key relationships are not known a priori, and information workers are often not be sophisticated enough to define these relationships. Therefore, the ability to automatically discover foreign-key relationships in PowerPivot is valuable, if not essential. The key challenge is to perform this detection interactively and with high precision even when data sets scale to hundreds of millions of rows and the schema contains tens of tables and hundreds of columns. In this paper, we describe techniques for fast foreign-key detection in PowerPivot and experimentally evaluate its accuracy, performance and scale on both synthetic benchmarks and real-world data sets. These techniques have been incorporated into PowerPivot for Excel.
引用
收藏
页码:1417 / 1428
页数:12
相关论文
共 14 条
[1]  
Agrawal Rakesh, 2012, COMPOSING STRUCTURED
[2]  
[Anonymous], 2010, CIKM, P3
[3]  
Bauckmann J., 2007, INT C DAT ENG
[4]  
Broder A., P ACM S THEOR COMP S
[5]  
Chaudhuri S., PROGRAM TPC D DATA G
[6]  
Chaudhuri S., 2003 ACMSIGMOD
[7]  
Chaudhuri S., COMMUNICATIONS ACM, V54, P88
[8]  
COHEN WW, 2003, WORKSH INF INT WEB
[9]   Discovering interesting inclusion dependencies: application to logical database tuning [J].
Lopes, S ;
Petit, JM ;
Toumani, F .
INFORMATION SYSTEMS, 2002, 27 (01) :1-19
[10]  
Morton K., 2012 ACM SIGMOD