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Google

A publicly-traded company primarily offering a web portal. Originally a search engine in the 1990s and early 2000s, Google expanded to online messaging, e-mail services, web video, mobile phones and so forth. Google monetizes its operations primarily through advertisements. It was founded in 1998. See also: Yahoo.
References in periodicals archive ?
Furthermore, our MapReduce program (M2) takes, on average, 20 seconds to infer a gene regulatory network on a DREAM4 dataset while the average time used by the TimeDelay-ARACNE R program is 3,500 seconds.
This platform consists of two primary components: a reliable shared storage (Hadoop Distributed File System) and analysis system (MapReduce).
Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," in Proceedings of the 6th Conference on Symposium on Operating Systems Design Implementation, vol.
This indexed-value column, unique for every row, causes MapReduce to sort the KV stores for every one of the iterations that can increase the integrity of the data and increase its secured access once distributed.
MapReduce [13] is a programming model proposed by Dean and Ghemawat.
In Section 4, we propose parallel versions of kernel-density-based and partial linear regression model algorithms, based on SPARK MapReduce paradigm.
O baixo custo proporcionado por essas novas plataformas de computacao, a facilidade de programacao proporcionada por modelos como o MapReduce e a popularizacao de tais tecnicas fazem com que problemas de Big Data aparecam nas mais diversas areas.
The core of Hadoop consists of two parts: a storage component known as Hadoop Distributed File System (HDFS) and a processing component called MapReduce.
Hadoop has become popular because it is designed to cheaply store data in the Hadoop Distributed File System (HDFS) and run large-scale MapReduce jobs for batch analysis.
Tez improves the MapReduce paradigm by dramatically improving its speed while maintaining MapReduce's ability to scale to petabytes of data.
When all the reduce machine outputs are complete, the master returns control to the user program, which then has available a final output file with the MapReduce results.
Inspired by Google's Mapreduce and GFS, Hadoop succeeds in developing a distributing file system HDFS (Hadoop Distributed File System) and the realization of the open source of Mapreduce.