Google Cluster Architecture
"Web Search for a Planet: The Google Cluster Architecture," IEEE Micro, Mar-Apr., 2003, 22-28.
The central idea of this IEEE Micro article is that Google has designed a search engine which is energy efficient, reliable, and so cost effective that it allows them to provide superior service. The article begins by pointing out that every request to a search engine requires complex computations. When Google gets a request, it reads hundreds of megabytes of data and uses tens of billions of CPU cycles. With thousands of such requests happening every second, Google's infrastructure compares in size to a supercomputer installation! Energy efficiency and price-performance ratio are the most important factors to its design. Easy parallelism is the main priority so that different queries can run on different processors (the overall index is partitioned so that a single query can use multiple processors).
Google's architecture provides reliability by using many commodity PCs to build computing clusters. The design is tailored for "best aggregate request throughput" rather than peak server response time -- reponse times are managed by parallelizing individual requests. Thus, a reliable computing infrastructure is fashioned from clusters of unreliable commodity PCs. At the software level reliability is achieved by replicating services across many different machines and automatically detecting failures.
When a user queries Google, the user's browser first identifies the nearest domain. Multiple clusters are distributed worldwide with sufficient capacity to handle query traffic. The system selects the nearest cluster. This minimizes the time required to respond to the user's query. The user's browser sends a hypertext transport protocol (HTTP) request to that cluster which processes the query. Each cluster has its...
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