sparklyr is an open-source and modern interface to scale data science and machine learning workflows using Apache Spark™, R, and a rich extension ecosystem. It enables using Apache Spark with ease using R by providing access to core functionality like installing, connecting and managing Spark and using Spark’s MLlib, Spark Structured Streaming and Spark Pipelines from R. sparklyr supports well-known R packages like dplyr, DBI and broom to reduce the cognitive overhead from having to re-learn libraries. Furthermore, it enables a rich-ecosystem of extensions to use in Spark and R: XGBoost, MLeap, GraphFrames, H2O, and optionally enable Apache Arrow to significantly improve performance. Through Spark, this allows you to scale your Data Science workflows in Hadoop YARN, Mesos, Kubernetes or Apache Livy.
sparklyr is an incubation-stage project of the LF AI & Data Foundation.
Contributed by: RStudio in December 2019