Apache Spark MLlib is a distributed framework that provides many utilities useful for machine learning tasks, such as: Classification, Regression, Clustering, Dimentionality reduction and, Linear algebra, statistics and data handling. R is a popular statistical programming language with a number of packages that support data processing and machine learning tasks. To address R’s scalability issue, the Spark community developed SparkR package which is based on a distributed data frame that enables structured data processing with a syntax familiar to R users.
Related Posts
-
Building a real-time big data pipeline 9: Spark MLlib, Regression, Python
Apache Spark expresses parallelism by three sets of APIs – DataFrames, DataSets and RDDs (Resilient -
Building a real-time big data pipeline 10: Spark Streaming, Kafka, Java
Spark Streaming is an extension of the core Apache Spark platform that enables scalable, high-throughput, -
Building a real-time big data pipeline 7 : Spark MLlib, Regression, Java
Apache Spark MLlib is a distributed framework that provides many utilities useful for machine learning