Procella

Abstract

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 superset 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.

Video advertising: Using YouTube analytics for the target audience

“…To accomplish this, YouTube uses an SQL query engine called Procella to deal with the volume of users and meet their needs. Procella is able to address "reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis" to use data to drive applications (Chattopadhyay et al, 2019). Unfortunately, some content still reflects user bias, rather than being able to influence public opinion.…”