Mesa: A Geo-Replicated Online Data Warehouse for Google's Advertising System

被引：9

作者：

Gupta, Ashish ^{[1
]}

Yang, Fan ^{[1
]}

Govig, Jason ^{[1
]}

Kirsch, Adam ^{[1
]}

Chan, Kelvin ^{[1
]}

Lai, Kevin ^{[1
]}

Wu, Shuo ^{[1
]}

Dhoot, Sandeep ^{[1
]}

Kumar, Abhilash Rajesh ^{[1
]}

Agiwal, Ankur ^{[1
]}

Bhansali, Sanjay ^{[1
]}

Hong, Mingsheng ^{[1
]}

Cameron, Jamie ^{[1
]}

Siddiqi, Masood ^{[1
]}

Jones, David ^{[1
]}

Shute, Jeff ^{[1
]}

Gubarev, Andrey ^{[1
]}

Venkataraman, Shivakumar ^{[1
]}

Agrawal, Divyakant ^{[1
]}

机构：

[1] Google Inc, Mountain View, CA 94043 USA

来源：

COMMUNICATIONS OF THE ACM | 2016年 / 59卷 / 07期

关键词：

Fault tolerance;

D O I：

10.1145/2936722

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：117 / 125

页数：9

共 15 条

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