Big Data Platforms

Below is a list of big data platforms and their interfaces with R.

Hadoop

• Hadoop (or YARN) - a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models

  • RHadoop - a collection of five R packages that allow users to manage and analyze data with Hadoop, developed by Revolution Analytics

  • RHIPE - an R and Hadoop Integrated Programming Environment

• Hortonworks HDP

Spark

• • Spark - a fast and general engine for large-scale data processing, which can be 100 times faster than Hadoop

  • SparkR - R frontend for Spark

H2O

• • H2O - an open source in-memory prediction engine for big data science

  • Algorithms provided in H2O:

  • PCA, GBM, deep learning, random forest, BigData RF, GLM, k-means, Naive Bayes, anomaly detection

• Get started with H2O in 3 easy steps

• H2O documentation for R users

• Running H2O on Hadoop

MongoDB

• • MongoDB - an open-source document database

  • R packages: rmongodb, RMongo

• A nice example of rmongodb