Tutorial: Elastic and Fault Tolerant Event Stream Processing Using StreamMine3G
Publikation: Beitrag zu Konferenzen › Paper › Beigetragen › Begutachtung
Beitragende
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
| Originalsprache | Englisch |
|---|---|
| Seitenumfang | 2 |
| Publikationsstatus | Veröffentlicht - 2013 |
| Peer-Review-Status | Ja |
Workshop
| Titel | Workshop on Distributed Cloud Computing (DCC 2013) (UCC '13), IEEE Computer Society, 2013 |
|---|---|
| Veranstaltungsnummer | |
| Dauer | 9 Dezember 2013 |
| Ort | |
| Stadt | Dresden |
| Land | Deutschland |
Externe IDs
| Scopus | 84901666225 |
|---|
Schlagworte
Forschungsprofillinien der TU Dresden
DFG-Fachsystematik nach Fachkollegium
Schlagwörter
- event stream processing, cep, fault tolerance, mapreduce, deterministic execution, elasticity, esp, cep, fault tolerance, mapreduce, deterministic execution, elasticity