Chapter 7 Scalable Knowledge Graph Processing Using SANSA

Abstract

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 chapter introduces Scalable Semantic Analytics Stack (SANSA), that addresses the challenge of dealing with large scale RDF data and provides a unified framework for applications like link prediction, knowledge base completion, querying, and reasoning. We discuss the motivation, background and the 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.

ABSTAT-HD: a scalable tool for profiling very large knowledge graphs

“…SANSA is a graph processing tool that has adopted distributed technologies to enhance scalability [25]. It provides a unified framework for several applications such as link prediction, knowledge base completion, querying, and reasoning.…”

“…In the domain of KG management and profiling, Sansa is the most notable example of a natively distributed solution. It provides a unified framework for several downstream tasks such as link prediction, knowledge base completion, querying, reasoning and, also, profiling [25]. Similarly to ABSTAT, it has a modular architecture and provides to the end user 32 RDF statistics (such as the number of triples, RDF terms, properties per entity, and usage of vocabularies across datasets), and apply quality assessment in a distributed manner.…”