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486 – Internet-Scale Statistical Computing

Estimating Traffic for Millions of Queries in Real Time

Sponsor: Section on Statistical Computing
Keywords: Online learning, Poisson regression, updating, web traffic, spike detection, online algorithm

Oliver Dain

MIT Lincoln Laboratory

Tim Hesterberg

Google

Laramie Leavitt

Google

Yogita Mehta

Google

Google estimates traffic for millions of queries continuously. This is used for many applications, such as caching results for frequent queries, and looking for spikes. We describe how Google efficiently processes a wide variety of queries with frequencies ranging from tens to millions of hits per day, with widely varying activity across time of day and week, and updates these models continuously as new data is observed.

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