Avatara: OLAP for webscale analytics products

17Citations
Citations of this article
52Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Multidimensional data generated by members on websites has seen massive growth in recent years. OLAP is a well-suited solution for mining and analyzing this data. Providing insights derived from this analysis has become crucial for these websites to give members greater value. For example, LinkedIn, the largest professional social network, provides its professional members rich analytics features like "Who's Viewed My Profile?" and "Who's Viewed This Job?" The data behind these features form cubes that must be efficiently served at scale, and can be neatly sharded to do so. To serve our growing 160 million member base, we built a scalable and fast OLAP serving system called Avatara to solve this many, small cubes problem. At LinkedIn, Avatara has been powering several analytics features on the site for the past two years. © 2012 VLDB Endowment.

Cite

CITATION STYLE

APA

Wu, L., Sumbaly, R., Riccomini, C., Koo, G., Kim, H. J., Kreps, J., & Shah, S. (2012). Avatara: OLAP for webscale analytics products. Proceedings of the VLDB Endowment, 5(12), 1874–1877. https://doi.org/10.14778/2367502.2367525

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free