Mira: Sharing Resources for Distributed Analytics at Small Timescales

dc.contributor.author	Kaufmann, Michael
dc.contributor.author	Kourtis, Kornilios
dc.contributor.author	Schuepbach, Adrian
dc.contributor.author	Zitterbart, Martina
dc.contributor.editor	David, Klaus
dc.contributor.editor	Geihs, Kurt
dc.contributor.editor	Lange, Martin
dc.contributor.editor	Stumme, Gerd
dc.date.accessioned	2019-08-27T12:55:23Z
dc.date.available	2019-08-27T12:55:23Z
dc.date.issued	2019
dc.identifier.isbn	978-3-88579-688-6
dc.identifier.issn	1617-5468
dc.identifier.uri	http://dl.gi.de/handle/20.500.12116/24984
dc.description.abstract	Mira is a system for optimized elastic execution of short-running and interactive dataanalytics applications with low-latency execution startup, fast resource management and efficient resource utilization on shared clusters. We highlight the key insights and the Mira approach and summarize the most important results.	en
dc.language.iso	en
dc.publisher	Gesellschaft für Informatik e.V.
dc.relation.ispartof	INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft
dc.relation.ispartofseries	Lecture Notes in Informatics (LNI) - Proceedings, Volume P-294
dc.subject	Data Science
dc.subject	Distributed Analytics
dc.subject	Elastic Computing
dc.title	Mira: Sharing Resources for Distributed Analytics at Small Timescales	en
dc.type	Text/Conference Paper
dc.pubPlace	Bonn
mci.reference.pages	265-266
mci.conference.sessiontitle	Data Science
mci.conference.location	Kassel
mci.conference.date	23.-26. September 2019
dc.identifier.doi	10.18420/inf2019_36