R Programming Jobs

With large data being adopted by more enterprises, the compilation and production language of data processing and analysis algorithms have been widely concerned. and unknowingly, open source statistics language R has become a basic technology for large data scientists and developers. 　　In all programming languages and techniques, popularity has soared. The following is the translation through the integration with the large data processing tools, R provides the depth statistical capability of large datasets, including statistical analysis and data-driven visualization. In industries such as finance, pharmaceuticals, media, and sales, which can directly take decisions from data, R has been applied in depth. ...

Foreword in the first article of this series: using Hadoop for distributed parallel programming, part 1th: Basic concepts and installation deployment, introduced the MapReduce computing model, Distributed File System HDFS, distributed parallel Computing and other basic principles, and detailed how to install Hadoop, How to run a parallel program based on Hadoop in a stand-alone and pseudo distributed environment (with multiple process simulations on a single machine). In the second article of this series: using Hadoop for distributed parallel programming, ...

MapReduce: Simple data processing on large cluster

Translation: Esri Lucas The first paper on the Spark framework published by Matei, from the University of California, AMP Lab, is limited to my English proficiency, so there must be a lot of mistakes in translation, please find the wrong direct contact with me, thanks. (in parentheses, the italic part is my own interpretation) Summary: MapReduce and its various variants, conducted on a commercial cluster on a large scale ...

Hadoop Here's my notes about introduction and some hints for Hadoop based open source projects. Hopenhagen it ' s useful to you. Management Tool ambari:a web-based Tool for provisioning, managing, and Mon ...

MapReduce is a programming model for parallel computing of large-scale data sets (greater than 1TB) to solve the computational problems of massive data.

What we want to does in this short tutorial, I'll describe the required tournaments for setting up a single-node Hadoop using the Hadoop distributed File System (HDFS) on Ubuntu Linux. Are lo ...

Large data areas of processing, my own contact time is not long, formal projects are still in development, by the large data processing attraction, so there is the idea of writing articles. Large data is presented in the form of database technologies such as Hadoop and "NO SQL", Mongo and Cassandra. Real-time analysis of data is now likely to be easier. Now the transformation of the cluster will be more and more reliable, can be completed within 20 minutes. Because we support it with a table? But these are just some of the newer, untapped advantages and ...

These individual-level behaviors embedded in the original social media data represent customer preferences, purchase histories, significant life events, moods, personalities, and other attributes that are obtained through text mining, which can be stored in social media data marts. The social networking pioneers we know today came in the late the 1960s, when the bulletin board was one of the first interactive message sharing platforms. Later (in the 1990s, when Craigslist and AOL entered the spotlight), the social revolution was the basis for rapid growth. Social networking ...

This paper is an excerpt from the book "The Authoritative Guide to Hadoop", published by Tsinghua University Press, which is the author of Tom White, the School of Data Science and engineering, East China Normal University. This book begins with the origins of Hadoop, and integrates theory and practice to introduce Hadoop as an ideal tool for high-performance processing of massive datasets. The book consists of 16 chapters, 3 appendices, covering topics including: Haddoop;mapreduce;hadoop Distributed file system; Hadoop I/O, MapReduce application Open ...