Building user-defined runtime adaptation routines for stream processing applications

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dc.citation.epage1837en_US
dc.citation.issueNumber12en_US
dc.citation.spage1826en_US
dc.citation.volumeNumber5en_US
dc.contributor.authorJacques-Silva, G.en_US
dc.contributor.authorGedik, B.en_US
dc.contributor.authorWagle, R.en_US
dc.contributor.authorWu, Kun-Lungen_US
dc.contributor.authorKumar, V.en_US
dc.date.accessioned2016-02-08T09:45:24Z
dc.date.available2016-02-08T09:45:24Z
dc.date.issued2012en_US
dc.departmentDepartment of Computer Engineeringen_US
dc.description.abstractStream processing applications are deployed as continuous queries that run from the time of their submission until their cancellation. This deployment mode limits developers who need their applications to perform runtime adaptation, such as algorithmic adjustments, incremental job deployment, and application-specific failure recovery. Currently, developers do runtime adaptation by using external scripts and/or by inserting operators into the stream processing graph that are unrelated to the data processing logic. In this paper, we describe a component called orchestrator that allows users to write routines for automatically adapting the application to runtime conditions. Developers build an orchestrator by registering and handling events as well as specifying actuations. Events can be generated due to changes in the system state (e.g., application component failures), built-in system metrics (e.g., throughput of a connection), or custom application metrics (e.g., quality score). Once the orchestrator receives an event, users can take adaptation actions by using the orchestrator actuation APIs. We demonstrate the use of the orchestrator in IBM's System S in the context of three different applications, illustrating application adaptation to changes on the incoming data distribution, to application failures, and on-demand dynamic composition. © 2012 VLDB Endowment.en_US
dc.description.provenanceMade available in DSpace on 2016-02-08T09:45:24Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 70227 bytes, checksum: 26e812c6f5156f83f0e77b261a471b5a (MD5) Previous issue date: 2012en
dc.identifier.doi10.14778/2367502.2367521en_US
dc.identifier.issn2150-8097
dc.identifier.urihttp://hdl.handle.net/11693/21373
dc.language.isoEnglishen_US
dc.publisherVLDB Endowmenten_US
dc.relation.isversionofhttp://doi.org/10.14778/2367502.2367521en_US
dc.source.titleProceedings of the VLDB Endowmenten_US
dc.subjectApplication adaptationen_US
dc.subjectApplication componentsen_US
dc.subjectApplication failureen_US
dc.subjectBuilt - in systemen_US
dc.subjectContinuous queriesen_US
dc.subjectData distributionen_US
dc.subjectDynamic compositionen_US
dc.subjectFailure recoveryen_US
dc.subjectRuntime adaptationen_US
dc.subjectRuntimesen_US
dc.subjectStream processingen_US
dc.subjectSystem stateen_US
dc.subjectData processingen_US
dc.titleBuilding user-defined runtime adaptation routines for stream processing applicationsen_US
dc.typeArticleen_US

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