MMLSpark, originally released last year, is a collection of projects intended to make Spark more useful in many contexts—mainly machine learning, but also in some general-purpose ways.
MMLSpark wraps all these functions in a set of APIs available for both Scala and Python. The repository contains some quick-start examples, such as using web services in Spark, using OpenCV on Spark for image manipulation, and training a deep image classifier using Azure VMs with GPUs.
MMLSpark itself can be installed on existing Spark clusters as a package, used in the Databricks cloud (or a Databricks appliance on Azure), installed directly in an instance of Python or Anaconda, or run in a Docker container. Integration is also available for the R language, but right now only via a beta auto-generated wrapper.