A Look Inside Facebook’s Graph Search
Special lecture from the course Info 240. Principles of Information Retrieval
Unicorn is an online, in-memory social graph-aware indexing system designed to search trillions of connections between tens of billions of users and entities on thousands of commodity servers. Unicorn is based on standard concepts in information retrieval, but it includes features to promote results with good social proximity. It also supports queries that require multiple round-trips to leaf servers in order to retrieve objects that are more than one edge away from source nodes. Unicorn is designed to answer billions of queries per day at latencies in the hundreds of milliseconds, and it serves as an infrastructural building block for Facebook's Graph Search product.
Mike Curtiss has been an engineer on Facebook’s search infrastructure team since 2010. In that time, he has helped to develop Unicorn, a search indexing system that powers Facebook Graph Search. Prior to Facebook, Mike joined Google in 2002, where he helped to invent GoogleNews and contributed to many other projects including GoogleMaps, GMail, and data center development. His interests include open source software, economics, angel investing, and watching Star Trek with his family. He holds a B.S. in computer engineering and M.S. in computer science from Case Western Reserve University.
