Distributed R

<p>Distributed R is an open source, high-performance platform for the <a href="/facts/R_/LSrkr8K8">R</a> language. It splits tasks between multiple processing nodes to reduce execution time and analyze large data sets. Distributed R enhances R by adding distributed <a href="/facts/Data_structure/yNsNvL1I">data structures</a>, parallelism primitives to run functions on distributed data, a task scheduler, and multiple data loaders. It is mostly used to implement distributed versions of machine learning tasks. Distributed R is written in <a href="/facts/C%2B%2B/Et0F2qn9">C++</a> and <a href="/facts/R_/LSrkr8K8">R</a>, and retains the familiar look and feel of R. As of February 2015<a href="https://en.wikipedia.org/w/index.php?title=Distributed_R&action=edit">[update]</a>, <a href="/facts/Hewlett-Packard/abuNSYNu">Hewlett-Packard</a> (HP) provides enterprise support for Distributed R with proprietary additions such as a fast data loader from the <a href="/facts/Vertica/SGJBWtrr">Vertica</a> database.
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Distributed R open-in-new

Distributed R