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 program-
ming models, fault tolerance as well as elasticity and cloud
support of these platforms.
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 program-
ming 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 |
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