Google Research Publication: Bigtable: A Distributed Storage System for Structured Data
Bigtable: A Distributed Storage System for Structured Data Fay Chang, Jeffrey Dean, Sanjay Ghemawat, Wilson C. Hsieh, Deborah A. Wallach, Mike Burrows, Tushar Chandra, Andrew Fikes, and Robert E. Gruber Abstract Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers. Many projec
Google Research Publications
Interpreting the Data: Parallel Analysis with Sawzall Rob Pike, Sean Dorward, Robert Griesemer, Sean Quinlan Abstract Very large data sets often have a flat but regular structure and span multiple disks and machines. Examples include telephone call records, network logs, and web document repositories. These large data sets are not amenable to study using traditional database techniques, if only
Google Research Publication: MapReduce: Simplified Data Processing on Large Clusters
MapReduce: Simplified Data Processing on Large Clusters Jeffrey Dean and Sanjay Ghemawat Abstract MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with t
Google Research Publication: The Google File System
The Google File System Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung Abstract We have designed and implemented the Google File System, a scalable distributed file system for large distributed data-intensive applications. It provides fault tolerance while running on inexpensive commodity hardware, and it delivers high aggregate performance to a large number of clients. While sharing many
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