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Facebook engineers identify Graph Search's big data challenges

Zach Miners | Feb. 22, 2013
Facebook’s engineers have many challenges ahead of them as they work to scale up Graph Search, the site’s new social search tool. One stumbling block: an over-abundance of data to sift through.

Facebook engineers

Facebook engineer Soren Lassen and product manager for Graph Search,Tom Stocky, describe their future hopes for Graph Search at a small whiteboard session with 11 journalists in San Mateo, Calif.

Facebooks engineers have many challenges ahead of them as they work to scale up Graph Search, the sites new social search tool. One stumbling block: an over-abundance of data to sift through.

Take the example of searching for Japanese restaurants in New York City liked by people from Japan. A search that would seem to generate hundreds if not thousands of results only spits back two measly businesses.

The search engine, in its current beta form, simply does not have the processing power to sift through the millions of connections among Japanese people on the site to perform the search, Facebook engineers said Thursday during a small media briefing at the companys headquarters in Menlo Park, California.

Theres still a lot of work we have to do, said software engineer Michael Curtiss. A query like this is very difficult computationally, to start with the 100 million in Japan, and then in a fraction of a second to sort through all the pages liked by people in Japan, he said.

This is virtually intractable in the limited amount of time that we have, said the engineer, who helped to design the sites Unicorn search engine that provides Graph Searchs infrastructure. What we end up having to do is cut out possibly good results.

Facebook is taking a variety of approaches to solve this and other big data problems associated with Graph Search.

One strategy involves a concept in computer databases known as query optimization, to improve the speed and efficiency of certain types of searches.

In the case of the Japanese restaurant search, the technique could be applied to start first with the restaurants that are liked instead of starting with Japan, and then filtering down the likes by people, Facebook engineers said.

The company is also addressing the challenges at the hardware level, by adding additional flash memory and other new features to the servers it uses at data centers, to accommodate the increase in search traffic caused by Graph Search.

We need to do extra work in data centers, buying new hardware platforms, [with] new types of servers being put up to support the computational needs of Unicorn, said Soren Lassen, who led the search infrastructure team behind Graph Search.

Facebook began rolling out Graph Search last month to a limited number of users in the U.S. The search tool is designed to let people comb through the social networks 1 trillion connections among users to search for people, places, photos and interests using phrases in plain English.

 

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