Stream processing and scheduling: Petr Skoda
Petr Skoda received an extended M.Sc. degree at Masaryk University Brno, Faculty of Informatics
Title: Stream processing and scheduling (An open lecture)
Speaker: Petr Skoda
When and Where: Thursday the 23rd of March in room V102 at 12:00
Abstract: Big data processing is a hot topic of today's computer world. One of the key paradigms behind it is MapReduce - parallel and massively distributed model inspired by the map and reduce functions commonly used in functional programming. Due to its simplicity and general availability of standard implementations, the paradigm has been massively adopted on current computer clusters. Yet, MapReduce is not optimal for all big data problems. This talk focuses on the area of an alternative paradigm - stream processing - which has multiple advantages over the MapReduce, e.g., it avoids persistent data storing if not required. Even though, frameworks for stream processing are nowadays easily available as a part of many Hadoop ecosystems, to use these frameworks in the right way needs just another shift in thinking of system architects thus the wider understanding of underlying ideas is inevitable prerequisite.
About speaker: Petr Skoda received an extended M.Sc. degree at Masaryk University Brno, Faculty of Informatics. During his studies, he worked as a developer and analyst at Pears Health Cyber company concerning development of e-commerce systems. Nowadays he is a PhD student at Brno University of Technology, Faculty of Information Technology. At the same time, he continues at Pears Health Cyber as a researcher of new opportunities in the field of medical devices and life-science communication. Petr participated in several european projects dealing with cloud and high-performance computing. He is interested in distributed systems, cloud computing technologies, HPC, information systems, and user experience.