SparkR

SparkR is an R package that provides a high-level interface to Apache Spark from the R language. It acts as the R API for Spark, allowing users to perform distributed data processing and analytics on large datasets within the Spark engine. SparkR is shipped with Apache Spark and can connect to a local or remote Spark cluster, enabling scalable computation from R.

The core feature of SparkR is the Spark DataFrame API, which represents distributed collections of data organized into named columns. Users can create DataFrames from local R data, read data from distributed storage systems, and perform operations such as selection, filtering, aggregation, joins, and sorting. SparkR also exposes a SQL interface; users can register DataFrames as temporary views and run SQL queries directly. The API includes functions for configuring Spark sessions, reading and writing common data formats, handling schemas, and working with user-defined functions to extend functionality.

SparkR integrates with Spark's machine learning library to support scalable ML tasks through dedicated APIs, enabling distributed model training and evaluation on large datasets. This includes algorithms for regression, classification, clustering, and more, accessible from within the R environment.

The library is designed to interoperate with other Spark components and is most useful for R users who want to leverage Spark's scalability and SQL capabilities without leaving R. Limitations include API maturity relative to Python and Scala interfaces and potential overhead when transferring data between R and Spark. SparkR evolves with Spark releases, with compatibility tied to the underlying Spark version in use.