S. Venkataraman, Zongheng Yang, Davies Liu, Eric Liang, H. Falaki, Xiangrui Meng, Reynold Xin, A. Ghodsi, M. Franklin, I. Stoica, M. Zaharia
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R is a popular statistical programming language with a number of extensions that support data processing and machine learning tasks. However, interactive data analysis in R is usually limited as the R runtime is single threaded and can only process data sets that fit in a single machine's memory. We present SparkR, an R package that provides a frontend to Apache Spark and uses Spark's distributed computation engine to enable large scale data analysis from the R shell. We describe the main design goals of SparkR, discuss how the high-level DataFrame API enables scalable computation and present some of the key details of our implementation.
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