Title :
Tutorial: Elastic and Fault Tolerant Event Stream Processing using StreamMine3G
Author :
Martin, Andrew ; Le Quoc, Do
Author_Institution :
Tech. Univ. Dresden, Dresden, Germany
Abstract :
The massive amount of new data being generated each day by data sources such as smartphones and sensor devices calls for new techniques to process such continues streams of data. Event Stream Processing (ESP) addresses this problem and enables users to process such data streams in (soft) realtime allowing the detection as well as a quick reaction to relevant situations. In this tutorial, we will introduce the participants to ESP techniques as well as ESP systems such as Storm, Apache S4 and StreamMine3G. We will cover aspects such as programming models, fault tolerance as well as elasticity and cloud support of these platforms.
Keywords :
cloud computing; data mining; fault tolerant computing; Apache S4; ESP; Storm; StreamMine3G; cloud support; elasticity; fault tolerance; fault tolerant event stream processing; programming models; sensor devices; smartphones; Cloud computing; Data processing; Elasticity; Fault tolerance; Fault tolerant systems; Tutorials; cep; deterministic execution; elasticity; esp; event stream processing; fault tolerance; mapreduce;
Conference_Titel :
Utility and Cloud Computing (UCC), 2013 IEEE/ACM 6th International Conference on
Conference_Location :
Dresden
DOI :
10.1109/UCC.2013.18