Big Data Processing with Apache Spark - Part 4: Spark Machine Learning

This is the fourth article of the "Big Data Processing with Apache Spark" series. Please see also: Part 1: Introduction, Part 2: Spark SQL and Part 3: Spark Streaming. Machine learning, predictive analytics, and data science topics are getting a lot of attention in recent years for solving real world problems in different business domains in several organizations. Spark MLlib, Spark's Machine Learning library, includes several different machine learning algorithms for Collaborative Filtering, Clustering, Classification and other machine learning tasks. In the previous articles in "Big Data Processing with Apache Spark" series, we have looked at what Apache Spark framework is (Part 1), how to leverage the SQL interface to access data using Spark SQL library (Part 2) and real-time data processing & analytics of streaming data using Spark Streaming (Part 3). Compose makes it simple to deploy production-ready databases in minutes in the cloud or on your own servers. In this article, we'll discuss machine learning concepts and how to use Apache Spark MLlib library for running predictive analytics.