Spark 3.0 introduces a new module: Spark Graph. Spark Graph adds the popular query language Cypher, its accompanying Property Graph Model and graph algorithms to the data science toolbox. Graphs have a plethora of useful applications in recommendation, fraud detection and research.
Morpheus is an open-source library that is API compatible with Spark Graph and extends its functionality by:
We will demonstrate how to explore data in Spark, use Morpheus to transform data into a Property Graph, and then build a Graph Solution in Neo4j.
Martin Junghanns is part of the Cypher for Apache Spark Engineering team at Neo4j. He is also the main developer of Gradoop, a system for graph analytics on distributed data flow systems. Martin holds a MSc Computer Science degree from the University of Leipzig.
Sören is a software engineer in the Neo4j Graph Analytics team concentrating on big data query execution and graph algorithms. His interests cover working with Cypher in big data environments such as Spark SQL. Prior to joining Neo4j, he was studying at Leipzig University.