Portrait of Vivek Narasayya

Vivek Narasayya

Principal Researcher

About

Research Interests

  • Self-tuning database systems, Physical database design
  • Performance monitoring, diagnostics and tuning of databases
  • Query processing and optimization
  • Multi-tenant database systems, Performance isolation
  • Data cleaning, data profiling

Professional Activities

PC Co-Chair

VLDB 2012 (Industrial track)
SMDB 2011, DBTEST 201

Editorial Board of VLDB Journal
Track/Area Chair

CIKM 2014: Query Language, Query Processing, Access Methods and Concurrency Control

Program Committee:

ACM SIGMOD 2003, 2008 (Industrial track), 2012, 2014 (Industrial track), 2016
VLDB 2006, PVLDB 2008-2010, PVLDB 2015, PVLDB 2016, PVLDB 2017
IEEE ICDE 2002, 2011 (Industrial Track), 2012, 2017
EDBT 2014 (Demo track)
ACM SIGKDD 2013
ACM CIKM 2004, 2012 (Senior PC member), 2013
Clean DB Workshop 2007
COMAD 2009, 2011, 2012
DBTest 2010
SMDB 2008

National Science Foundation (NSF) Panelist
National Academy of Sciences (NAS) Panelist: Committee on State Voter Registration Databases, 2007.
National Academy of Engineering (NAE), Frontiers of Engineering Symposium Attendee, 2008.
Co-organized the UW-MSR 2010 Summer Institute on Cloud Data Services: Challenges and Opportunities

Invited Talks, Tutorials

  • Vivek Narasayya. New Frontiers in Business Intelligence. Keynote at Web Age Information Management (WAIM), 2011, China.
  • Surajit Chaudhuri, Vivek Narasayya. New Frontiers in Business Intelligence. VLDB 2011, Seattle, USA.
  • Vivek Narasayya. SQL Server Query Optimizer, and Reflections on Query Optimization. May 2010, Stanford University.
  • Surajit Chaudhuri, Vivek Narasayya. “Self-Tuning Database Systems: A Decade of Progress”. VLDB 2007, Vienna, Austria. Invited Talk for 10-year Best Paper Award.
  • Vivek Narasayya. “Recent Advances in Self-Tuning Database Systems”. Keynote talk at International Workshop on Automated Performance Tuning (iWAPT) 2007, Tokyo, Japan.
  • Vivek Narasayya. “Microsoft SQL Server Query Optimizer”. May 2007, Stanford University.
  • Vivek Narasayya. “AutoAdmin: Towards Self-Tuning Databases”. Nov 2002, Nov 2003, Stanford University.

 

Projects

SQLVM: Performance Isolation in Multi-Tenant Relational Database-as-a-Service

Established: February 14, 2013

Multi-tenancy and resource sharing are essential to make a Database-as-a-Service (DaaS). However, resource sharing usually results in the performance of one tenant’s workload to be affected by other co-located tenants. In the SQLVM project, our approach to performance isolation in a DaaS is to isolate the key resources, such as CPU, I/O and memory, needed by the tenants’ workload. Mechanisms designed in the SQLVM project are now in production in Azure SQL Database Service Tiers…

Web Data Extraction and Search

Established: February 9, 2013

The goal of this project is to extract structured data on the web (like html tables, lists, spreadsheets etc.) and make it accessible/searchable on Bing and Office 365. Some of the technical challenges: Table classification and understanding: The vast majority of html tables are used for formatting/layout purposes; they do not any contain useful content . How do we automatically filter out such tables? Furthermore, there are various types of tables like relational tables (each row…

Data Exploration

Established: June 8, 2004

This is a project area rather than a specific project. This project area focuses on novel ways to query, browse, extract, explore, mine and manage various kinds of data residing within the enterprise and on the web: structured data in relational databases, tabular data embedded in web pages, enterprise documents and spreadsheets as well as unstructured data in query logs, text documents and social media. Our research is relevant to both enterprise and consumer scenarios…

Data Cleaning

Established: July 1, 2002

Poor data quality is a well-known problem in data warehouses that arises for a variety of reasons such as data entry errors and differences in data representation among data sources. For example, one source may use abbreviated state names while another source may use fully expanded state names. However, high quality data is essential for accurate data analysis. Data cleaning is the process of detecting and correcting errors and inconsistencies in data. Goal…

AutoAdmin

Established: November 2, 2001

Database management systems provide functionality that is central to developing business applications. Therefore, database management systems are increasingly being used as an important component in applications. Yet, the problem of tuning database management systems for achieving required performance is significant, and results in high total cost of ownership (TCO). The goal of our research in the AutoAdmin project is to make database systems self-tuning and self-administering. We achieve this by enabling databases to track the…

Data Mining

Established: November 2, 2001

Goal The Knowledge Discovery and Data Mining (KDD) process consists of data selection, data cleaning, data transformation and reduction, mining, interpretation and evaluation, and finally incorporation of the mined "knowledge" with the larger decision making process. The goals of this research project include development of efficient computational approaches to data modeling (finding patterns), data cleaning, and data reduction of high-dimensional large databases. Methods from databases, statistics, algorithmic complexity, and optimization are used to build efficient…

Publications

2016

2015

2014

2013

2012

2011

2010

2009

2008

2007

2006

2005

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1996

1995

1994

Projects

Link description

Big Data Platforms

Date

July 15, 2013

Speakers

Ion Stoica, Raghu Ramakrishnan, and Vivek Narasayya

Affiliation

Microsoft, University of California, eXtreme Computing Group

Downloads

Program for TPC-H Data Generation with Skew

April 2016

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  • Website

Other

Research Interests

  • Self-tuning database systems, Physical database design
  • Performance monitoring, diagnostics and tuning of databases
  • Query processing and optimization
  • Multi-tenant database systems, performance isolation

Professional Activities

Professional Activities

  • PC Co-Chair
    • VLDB 2012 (Industrial track)
    • SMDB 2011, DBTEST 201
  • Editorial Board of VLDB Journal
  • Track/Area Chair
    • CIKM 2014: Query Language, Query Processing, Access Methods and Concurrency Control
  • Program Committee:
    • ACM SIGMOD 2003, 2008 (Industrial track), 2012, 2014 (Industrial track)
    • VLDB 2006, PVLDB 2008-2010, PVLDB 2015
    • IEEE ICDE 2002, 2011 (Industrial Track), 2012
    • EDBT 2014 (Demo track)
    • ACM SIGKDD 2013
    • ACM CIKM 2004, 2012 (Senior PC member), 2013
    • Clean DB Workshop 2007
    • COMAD 2009, 2011, 2012
    • DBTest 2010
    • SMDB 2008
  • National Science Foundation (NSF) Panelist
  • National Academy of Sciences (NAS) Panelist: Committee on State Voter Registration Databases, 2007.
  • National Academy of Engineering (NAE), Frontiers of Engineering Symposium Attendee, 2008.
  • Co-organized the UW-MSR 2010 Summer Institute on Cloud Data Services: Challenges and Opportunities

Invited Talks, Tutorials

Invited Talks, Tutorials

  • Vivek Narasayya. New Frontiers in Business Intelligence. Keynote at Web Age Information Management (WAIM), 2011, China.
  • Surajit Chaudhuri, Vivek Narasayya. New Frontiers in Business Intelligence. VLDB 2011, Seattle, USA.
  • Vivek Narsayya. SQL Server Query Optimizer, and Reflections on Query Optimization. May 2010, Stanford University.
  • Surajit Chaudhuri, Vivek Narasayya. “Self-Tuning Database Systems: A Decade of Progress”. VLDB 2007, Vienna, Austria. Invited Talk for 10-year Best Paper Award.
  • Vivek Narasayya. “Recent Advances in Self-Tuning Database Systems”. Keynote talk at International Workshop on Automated Performance Tuning (iWAPT) 2007, Tokyo, Japan.
  • Vivek Narasayya. “Microsoft SQL Server Query Optimizer”. May 2007, Stanford University.
  • Vivek Narasayya. “AutoAdmin: Towards Self-Tuning Databases”. Nov 2002, Nov 2003, Stanford University.

Collaborators

Collaborators