A Parallel Community Detection in Multi-Modal Social Network With Apache Spark

Getting Started with Apache Spark

Parallel Maritime Traffic Clustering Based on Apache Spark

Maritime traffic patterns extraction is an essential part for maritime security and surveillance and DBSCANSD is a density based clustering algorithm extracting the arbitrary shapes of the normal lanes from AIS data. This paper presents a parallel DBSCANSD algorithm on top of Apache Spark. The project is an experimental research work and the results shown in this paper is preliminary. The exper...

An Introduction to Community Detection in Multi-layered Social Network

Social communities extraction and their dynamics are one of the most important problems in today’s social network analysis. During last few years, many researchers have proposed their own methods for group discovery in social networks. However, almost none of them have noticed that modern social networks are much more complex than few years ago. Due to vast amount of different data about variou...

Good parallel software development practices. Apache Spark case

Recently, Spark as data processing engine, gained huge popularity because of better performance in terms of the speed. Developers of Spark claim that it may outperform Hadoop MapReduce in 100 times in memory and 10 times on disk [1]. This paper outlines which innovations improved speed and how. In order to investigate improvements, I analysed technical documentation, which is available, since b...

Balanced Graph Partitioning with Apache Spark

A significant part of the data produced every day by online services is structured as a graph. Therefore, there is the need for efficient processing and analysis solutions for large scale graphs. Among the others, the balanced graph partitioning is a well known NP-complete problem with a wide range of applications. Several solutions have been proposed so far, however most of the existing state-...