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Author Kirsch, Adam ♦ Shute, Jeff ♦ Govig, Jason ♦ Cameron, Jamie ♦ Kumar, Abhilash Rajesh ♦ Agiwal, Ankur ♦ Wu, Shuo ♦ Venkataraman, Shivakumar ♦ Lai, Kevin ♦ Siddiqi, Masood ♦ Gupta, Ashish ♦ Chan, Kelvin ♦ Jones, David ♦ Bhansali, Sanjay ♦ Dhoot, Sandeep ♦ Hong, Mingsheng ♦ Agrawal, Divyakant ♦ Yang, Fan ♦ Gubarev, Andrey
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Abstract Mesa is a highly scalable analytic data warehousing system that stores critical measurement data related to Google's Internet advertising business. Mesa is designed to satisfy a complex and challenging set of user and systems requirements, including near real-time data ingestion and retrieval, as well as high availability, reliability, fault tolerance, and scalability for large data and query volumes. Specifically, Mesa handles petabytes of data, processes millions of row updates per second, and serves billions of queries that fetch trillions of rows per day. Mesa is geo-replicated across multiple datacenters and provides consistent and repeatable query answers at low latency, even when an entire datacenter fails. This paper presents the Mesa system and reports the performance and scale that it achieves.
Description Affiliation: Google, Inc. (Gupta, Ashish; Yang, Fan; Govig, Jason; Kirsch, Adam; Chan, Kelvin; Lai, Kevin; Wu, Shuo; Dhoot, Sandeep; Kumar, Abhilash Rajesh; Agiwal, Ankur; Bhansali, Sanjay; Hong, Mingsheng; Cameron, Jamie; Siddiqi, Masood; Jones, David; Shute, Jeff; Gubarev, Andrey; Venkataraman, Shivakumar; Agrawal, Divyakant)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2005-08-01
Publisher Place New York
Journal Communications of the ACM (CACM)
Volume Number 59
Issue Number 7
Page Count 9
Starting Page 117
Ending Page 125


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Source: ACM Digital Library