The size and number of knowledge graphs have increased tremendously in recent years. In the meantime, the distributed data processing technologies have also advanced to deal with big data and large scale knowledge graphs. This lecture introduces Scalable Semantic Analytics Stack (SANSA), which addresses the challenge of dealing with large scale RDF data and provides a uni ed framework for applications like link prediction, knowledge base completion, querying, and reasoning.
We discuss the motivation, background and architecture of SANSA. SANSA is built using general-purpose processing engines Apache Spark and Apache Flink. After reading this chapter, the reader should have an understanding of the different layers and corresponding APIs available to handle Knowledge Graphs at scale using SANSA.

The Lecture has been presented at the Big Data Analytics Summer School 2020 by Dr. Hajira Jabeen and Damien Graux.