RDF Query Answering Using Apache Spark: Review and Assessment
Giannis Agathangelos, Georgia Troullinou, Haridimos Kondylakis, Kostas Stefanidis, Dimitris Plexousakis · 2018
The explosion of the web and the abundance of linked data demand for effective and efficient methods for storage, management and querying. More specifically, the ever-increasing size and number of RDF data collections raises the need for efficient query answering, and dictates the usage of distributed data management systems for effectively partitioning and querying them. To this direction, Apache Spark is one of the most active big-data approaches, with more and more systems adopting it, for efficient, distributed data management. The purpose of this paper is to provide an overview of the existing works dealing with efficient query answering, in the area of RDF data, using Apache Spark. We discuss on the characteristics and the key dimension of such systems, we describe novel ideas in the area, and the corresponding drawbacks, and provide directions for future work.