Store Mi phone M

advertisement


Store
Devices Microsoft Surface PCs & tablets Xbox Virtual reality Accessories Windows
phone Microsoft Band Software Office Windows Additional software Apps All apps
Windows apps Windows phone apps Games Xbox One games Xbox 360 games PC
games Windows games Windows phone games Entertainment All Entertainment
Movies & TV Music Business & Education Business Store Education Store Developer
Sale Back-to-school essentials Sale Products
Software & services Windows Office Free downloads & security Internet Explorer
Microsoft Edge Skype OneNote OneDrive Microsoft Health MSN Bing Microsoft
Groove Microsoft Movies & TV Devices & Xbox All Microsoft devices Microsoft
Surface All Windows PCs & tablets PC accessories Xbox & games Microsoft Band
Microsoft Lumia All Windows phones Microsoft HoloLens For business Cloud
Platform Microsoft Azure Microsoft Dynamics Windows for business Office for
business Skype for business Surface for business Enterprise solutions Small business
solutions Find a solutions provider Volume Licensing For developers & IT pros
Develop Windows apps Microsoft Azure MSDN TechNet Visual Studio For students
& educators Office for students OneNote in classroom Shop PCs & tablets perfect
for students Microsoft in Education Support
Sign in


Research Research
o Research Home
o Research areas
 Algorithms
 Artificial intelligence and machine learning
 Computer systems and networking
 Computer vision
 Data visualization, analytics, and platform
 Ecology and environment
 Economics
 Graphics and multimedia
 Hardware, devices, and quantum computing
 Human-centered computing
 Mathematics







o
o
o
o
o



Medical, health, and genomics
Natural language processing and speech
Programming languages and software engineering
Search and information retrieval
Security, privacy, and cryptography
Social Sciences
Technology for emerging markets
Products & Downloads
Programs & Events
 Academic Programs
 Events & Conferences
People
Careers
About
 About
 Microsoft Research blog
 Asia Lab
 Cambridge Lab
 India Lab
 New England Lab
 New York City Lab
 Redmond Lab
 Applied Sciences Lab
Research areas
o Algorithms
o Artificial intelligence and machine learning
o Computer systems and networking
o Computer vision
o Data visualization, analytics, and platform
o Ecology and environment
o Economics
o Graphics and multimedia
o Hardware, devices, and quantum computing
o Human-centered computing
o Mathematics
o Medical, health, and genomics
o Natural language processing and speech
o Programming languages and software engineering
o Search and information retrieval
o Security, privacy, and cryptography
o Social Sciences
o Technology for emerging markets
Products & Downloads
Programs & Events
o Academic Programs
o



Events & Conferences
People
Careers
About
o About
o Microsoft Research blog
o Asia Lab
o Cambridge Lab
o India Lab
o New England Lab
o New York City Lab
o Redmond Lab
o Applied Sciences Lab
A Robust, Optimization-Based Approach
for Approximate Answering of Aggregate
Queries
May 1, 2001

Download Document

BibTex
Authors

Surajit Chaudhuri

Gautam Das

Vivek Narasayya
Published In

SIGMOD
Publication Type
Inproceedings
Book Title
SIGMOD
Pages
45
Number
MSR-TR-2001-37
Publisher
Association for Computing Machinery, Inc.
Copyright © 2007 by the Association for Computing Machinery, Inc. Permission to make
digital or hard copies of part or all of this work for personal or classroom use is granted without
fee provided that copies are not made or distributed for profit or commercial advantage and that
copies bear this notice and the full citation on the first page. Copyrights for components of this
work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy
otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific
permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212)
869-0481, or [email protected] The definitive version of this paper can be found at
ACM’s Digital Library --http://www.acm.org/dl/.

Abstract

Related Info
Abstract
The ability to approximately answer aggregation queries accurately and efficiently is of great
benefit for decision support and data mining tools. In contrast to previous sampling-based
studies, we treat the problem as an optimization problem whose goal is to minimize the error in
answering queries in the given workload. A key novelty of our approach is that we can tailor the
choice of samples to be robust even for workloads that are “similar― but not necessarily
identical to the given workload. Finally, our techniques recognize the importance of taking into
account the variance in the data distribution in a principled manner. We show how our solution
can be implemented on a database system, and present results of extensive experiments on
Microsoft SQL Server 2000 that demonstrate the superior quality of our method compared to
previous work.
Related Info
Related Files
 SIG01-AQP.pdf
Groups
 Data Management, Exploration and Mining (DMX)
Research Areas
 Search and information retrieval
Research Labs
 Microsoft Research Lab - Redmond
Follow Microsoft Research


Follow @MSFTResearch

Share this page


Tweet

Learn

Windows

Office

Skype

Outlook

OneDrive

MSN
Devices

Microsoft Surface

Xbox

PC and laptops

Microsoft Lumia

Microsoft Band

Microsoft HoloLens
Microsoft Store

View account

Order tracking

Retail store locations

Returns

Sales & support
Downloads

Download Center

Windows downloads

Windows 10 Apps

Office Apps

Microsoft Lumia Apps

Internet Explorer
Values

Diversity and inclusion

Accessibility

Environment

Microsoft Philanthropies

Corporate Social Responsibility

Privacy at Microsoft
Company

Careers

About Microsoft

Company news

Investors

Research

Site map

English (United States)

Contact us

Privacy & cookies

Terms of use

Trademarks

About our ads

© 2016 Microsoft
​
Download