Publications

Detailed Information

Aggressive buffer pool warm-up after restart in SQL Server

Cited 0 time in Web of Science Cited 2 time in Scopus
Authors

Park, Kwang Hyun; Do, Jae Young; Teletia, Nikhil; Patel, Jignesh M.

Issue Date
2016-05
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016, pp.31-38
Abstract
In many settings, a database server has to be restarted either in response to a failure event, or in response to an operational decision such as moving a database service from one machine to another. However, such restarts pose a potential performance problem as the new database server starts off with a cold buffer pool. As a result, the database application experiences a dramatic reduction in performance right after the restart, since just before the restart the database buffer pool was filled with hot pages and after the restart the database buffer pool is empty. To address these issues, traditional database systems use mechanisms such as SQL Server's aggressive page expansion and MySQL's buffer pool preloading. However, these approaches have key limitations including long warm-up times, possible early hot page eviction, user query performance saturation, and failure restart. In this paper, we present a new framework for SQL Server that allows continual capturing of the state of the buffer pool, and restoring the server state quickly with a snapshot of the buffer pool at restart. Our empirical evaluation demonstrates that our method reduces the time to regain peak performance by a factor of 2X or more over the previous approaches.
URI
https://hdl.handle.net/10371/201374
DOI
https://doi.org/10.1109/ICDEW.2016.7495612
Files in This Item:
There are no files associated with this item.
Appears in Collections:

Related Researcher

  • College of Engineering
  • Department of Electrical and Computer Engineering
Research Area AI 애플리케이션을 위한 알고리즘-시스템 공동 설계, AI-powered Big Data Management, Generative AI, Large Language Model, ML, 고성능 대규모 AI 데이터 분석 및 처리, 모달 AI

Altmetrics

Item View & Download Count

  • mendeley

Items in S-Space are protected by copyright, with all rights reserved, unless otherwise indicated.

Share