This module will cover the setup, APIs and different layers of SANSA. At the end of this module, the audience will be able to execute examples and create programs that use SANSA APIs. The final part of this lecture is planned to be an interactive session to wrap up the introduced concepts and present attendees some open research questions which are nowadays studied by the community.
This module will cover the needs and challenges of distributed analytics and then dive into the details of scalable semantic analytics stack (SANSA) used to perform scalable analytics for knowledge graphs. It will cover different SANSA layers and the underlying principles to achieve scalability for knowledge graph processing.
In the practical level, the Big Data frameworks use different APIs for graph computations and graph processing. In this lecture, the important libraries built on top of Apache Spark will be covered. These include SparkSQL, GraphX and MLlib. The audience will learn to build scalable algorithms in Spark using Scala.