Peta-Scale Data Warehousing at Yahoo!

被引：0

作者：

Ahuja, Mona ^{[1
]}

Chen, Cheng Che ^{[1
]}

Gottapu, Ravi ^{[1
]}

Hallmann, Joerg ^{[1
]}

Hasan, Waqar ^{[1
]}

Johnson, Richard ^{[1
]}

Kozyrczak, Maciek ^{[1
]}

Pabbati, Ramesh ^{[1
]}

Pandit, Neeta ^{[1
]}

Pokuri, Sreenivasulu ^{[1
]}

Uppala, Krishna ^{[1
]}

机构：

[1] Yahoo Inc, Sunnyvale, CA 94089 USA

来源：

ACM SIGMOD/PODS 2009 CONFERENCE | 2009年

关键词：

Column Database; MPP Database; Vector Query Processing; Column Storage; Data Warehousing; Analytics; Business Intelligence;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Insights based on detailed data on consumer behavior, product performance and marketplace behavior are driving innovation and competition in the internet space. We introduce Everest, a SQL-compliant data warehousing engine, based on a column architecture that we have built and deployed at Yahoo!. In contrast to commercially available engines, this massively parallel engine, based on commodity hardware, offers scale, flexibility, specialized analytic operations, and lower administrative & hardware costs. In this paper, we describe the business motivation and the software and deployment architecture of Everest. The engine is in production at Yahoo! since 2007 and currently manages over six petabytes of data.

引用

页码：855 / 861

页数：7

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