rJava provides a low-level bridge between R and Java (via JNI). It is comparable to the .C/.Call C interface. Integration of R and java using package ‘rJava’ Ideally, if you are developing a web application in Java, where you need some demand prediction or classification result and you want to show it in your User Interface (UI), then this is the integration you are looking for – Use Cases where Integration plays a vital role:Ĭlustering, Classification or Regression analysis written in R script can originate from legacy implementation or conscious decisions to use R for certain use cases. To integrate R and Java using packages, we can use: There are three possible ways to connect R and Java. This blog touches upon the benefits and architectures where such kind of integration may be required. Integrating R with Java could create some real-time, high end Machine Learning based applications. R is enriched with Machine Learning and Statistical Libraries.
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On that note, this blog explores the opportunities of integrating Java with the R language, which is widely used among statisticians and data miners for developing statistical software and data analysis. It is also well-suited for developing new machine learning schemes. Weka is empowered with tools for data pre-processing, classification, regression, clustering, association rules, and visualization. Of course, there are effective tools like Weka, whose algorithms could be called from Java codes. Java is undisputedly a great language for building enterprise solutions, but has miles to scale on the analytics front.