4.4 Article

Procella: Unifying serving and analytical data at YouTube

Journal

PROCEEDINGS OF THE VLDB ENDOWMENT
Volume 12, Issue 12, Pages 2022-2034

Publisher

ASSOC COMPUTING MACHINERY
DOI: 10.14778/3352063.3352121

Keywords

-

Ask authors/readers for more resources

Large organizations like YouTube are dealing with exploding data volume and increasing demand for data driven applications. Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. Typically, organizations build specialized infrastructure for each of these use cases. This, however, creates silos of data and processing, and results in a complex, expensive, and harder to maintain infrastructure. At YouTube, we solved this problem by building a new SQL query engine - Procella. Procella implements a super-set of capabilities required to address all of the four use cases above, with high scale and performance, in a single product. Today, Procella serves hundreds of billions of queries per day across all four workloads at YouTube and several other Google product areas.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.4
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available