Hadoop is the most popular open-source software platform. It is also addressed as Apache Hadoop. It was developed by the Apache software foundation. This software is used to deal with the massive and huge amount of data and computation. It is one of the fastest distributed big data framework. The Hadoop is measurable which makes it suitable for handling any kind of data, whether it is the structure or unstructured or semi-structured.


If you want to extract analytics from it then you must extend its capabilities and it is necessary to integrate Hadoop with R programming. First, it is important to understand the meaning of R programming. It is the language which is used for analyzing statistical and graphical data. It is best-suited language which was developed for this purpose. If you looking for a source which best analytics and visual features then you must combine R programming with Hadoop for better results. However, you can take R Hadoop assignment writing help from the professionals of BookMyEssay if you are looking for more information on its integration.

There are some specific reasons why R programming is the most suitable option for data analytics:

  • It is the object-oriented programming language with rigid graphical capabilities.
  • It is easier to use this language for graphics applications.
  • It has strong data structure.
  • It comes with the special features of statistical programming
  • It has advanced data visualization tools.

Having these features and integrating this language with Hadoop makes it easier for data visualization, analysis, statistics, and modeling. It becomes highly extensible with object-oriented features. There are some of the most common methods that you can use for integrating R programming with Hadoop. Some of these methods are mentioned below:

  • RHadoop: It is the package provided by revolution analytics which can be used for analyzing the working of R programming with Hadoop framework data.
  • RHIVE: This provides huge statistical libraries and algorithms that are featured in R programming language to the information that is stored in Hadoop. It extends the HiveQL with R language functions.
  • RHIPE: It has a combined programming atmosphere which was developed by divide and recombines. It is facilities the analysis process of a large amount of data.
  • ORCH: The Oracle R Connector for Hadoop is used for locating R on oracle big data appliance or non-oracle framework like Hadoop. This network allows you to have access to Hadoop cluster via R programming.
  • Hadoop Streaming: It uses MapReduce codes in R programming language which makes it more user-friendly. It aims at making R more accessible and compatible with HadoopStreaming applications.

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