How Google Works: Exotic but Not UniqueBy David F. Carr Print
For all the razzle-dazzle surrounding Google, the company must still work through common business problems such as reporting revenue and tracking projects. But it sometimes addresses those needs in unconventional—yet highly efficient—ways. Other
Exotic but Not Unique; Would it Work for You?
Google's systems seem to work well for Google. But if you could run your own systems on the Google File System, would you want to? Or is this an architecture only a search engine could love?
Distributed file systems have been around since the 1980s, when the Sun Microsystems Network File System and the Andrew File System, developed at Carnegie Mellon University, first appeared. Software engineer and blogger Jeff Darcy says the system has a lot in common with the HighRoad system he worked on at EMC.
Despite those caveats, Darcy says he also sees many aspects of the GFS as "cool and useful," and gives Google credit for "bringing things that might have been done mostly as research projects and turning them into a system stable enough and complete enough to be used in commercial infrastructure."
Google software engineers considered and rejected modifying an existing distributed file system because they felt they had different design priorities, revolving around redundant storage of massive amounts of data on cheap and relatively unreliable computers.
Despite having published details on technologies like the Google File System, Google has not released the software as open source and shows little interest in selling it. The only way it is available to another enterprise is in embedded form—if you buy a high-end version of the Google Search Appliance, one that is delivered as a rack of servers, you get Google's technology for managing that cluster as part of the package.
However, the developers working on Nutch, an Apache Software Foundation open-source search engine, have created a distributed software environment called Hadoop that includes a distributed file system and implementation of MapReduce inspired by Google's work.
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