Tutorial: Elastic and Fault Tolerant Event Stream Processing Using StreamMine3G
Research output: Contribution to conferences › Paper › Contributed › peer-review
Contributors
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.
Details
| Original language | English |
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| Number of pages | 2 |
| Publication status | Published - 2013 |
| Peer-reviewed | Yes |
Workshop
| Title | Workshop on Distributed Cloud Computing (DCC 2013) (UCC '13), IEEE Computer Society, 2013 |
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| Conference number | |
| Duration | 9 December 2013 |
| Location | |
| City | Dresden |
| Country | Germany |
External IDs
| Scopus | 84901666225 |
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Keywords
Research priority areas of TU Dresden
DFG Classification of Subject Areas according to Review Boards
Keywords
- event stream processing, cep, fault tolerance, mapreduce, deterministic execution, elasticity, esp, cep, fault tolerance, mapreduce, deterministic execution, elasticity