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R-Programming

Environment for statistical computing and graphics

R is a programming language and environment commonly used in statistical computing, data analytics and scientific research.It is one of the most popular languages used by statisticians, data analysts, researchers and marketers to retrieve, clean, analyze, visualize and present data.  Due to its expressive syntax and easy-to-use interface, it has grown in popularity in recent years.Being an open source software and having a variety of built in statistical commands, R is the most widely used tool by statisticians and Data analysts. There are a lot of new packages being developed and old packages constantly updated in R to support and handle Big Data. This is an advantage mainly for R users as they don’t have to migrate to other platforms to handle their huge volumes of data.


 Explicit Parallelism

Parallel means having the flexibility to run several computations simultaneously by splitting your data processes across multiple cores. Explicit Parallelism means telling your system explicitly each step to follow.

 Implicit Parallelism

Unlike explicit parallelism where the user controls (and can mess up) most of the cluster settings, with implicit parallelism most of the messy legwork in setting up the system and distributing data is avoided

 

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