Spark framework

Spark contributors have utilized the core Spark framework and have developed different libraries on top of Spark to enhance its capabilities. These libraries can be plugged in to Spark as per the requirement:

Spark SQL

Spark SQL is a wrapper of SQL on top of Spark. It transforms SQL queries into Spark jobs to produce results. Spark SQL can work with a variety of data sources, such as Hive tables, Parquet files, and JSON files.

GraphX

GraphX, as the name suggests, enables working with graph-based algorithms. It has a wide variety of graph-based algorithms already implemented and is still growing. Some examples are PageRank, Connected components, Label propagation, SVD++, strongly connected components, Triangle count, and so on.

MLib

MLib is a scalable machine learning library that works on top of Spark. It is considerably easier to use and deploy, and its performance can be optimized to be 100 times faster than MapReduce.

Spark streaming

Spark streaming is a library that enables Spark...