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State Management in Apache Flink (R) Consistent Stateful Distributed Stream Processing
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-9351-8508
KTH, School of Information and Communication Technology (ICT), Software and Computer systems, SCS.ORCID iD: 0000-0002-6718-0144
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2017 (English)In: Proceedings of the VLDB Endowment, ISSN 2150-8097, E-ISSN 2150-8097, Vol. 10, no 12, p. 1718-1729Article in journal (Refereed) Published
Abstract [en]

Stream processors are emerging in industry as an apparatus that drives analytical but also mission critical services handling the core of persistent application logic. Thus, apart from scalability and low-latency, a rising system need is first-class support for application state together with strong consistency guarantees, and adaptivity to cluster reconfigurations, software patches and partial failures. Although prior systems research has addressed some of these specific problems, the practical challenge lies on how such guarantees can be materialized in a transparent, non-intrusive manner that relieves the user from unnecessary constraints. Such needs served as the main design principles of state management in Apache Flink, an open source, scalable stream processor. We present Flink's core pipelined, in-flight mechanism which guarantees the creation of lightweight, consistent, distributed snapshots of application state, progressively, without impacting continuous execution. Consistent snapshots cover all needs for system reconfiguration, fault tolerance and version management through coarse grained rollback recovery. Application state is declared explicitly to the system, allowing efficient partitioning and transparent commits to persistent storage. We further present Flink's backend implementations and mechanisms for high availability, external state queries and output commit. Finally, we demonstrate how these mechanisms behave in practice with metrics and largedeployment insights exhibiting the low performance trade-offs of our approach and the general benefits of exploiting asynchrony in continuous, yet sustainable system deployments.

Place, publisher, year, edition, pages
2017. Vol. 10, no 12, p. 1718-1729
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Computer Sciences
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URN: urn:nbn:se:kth:diva-220296ISI: 000416494000011Scopus ID: 2-s2.0-85036646347OAI: oai:DiVA.org:kth-220296DiVA, id: diva2:1169071
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QC 20171222

Available from: 2017-12-22 Created: 2017-12-22 Last updated: 2018-01-13Bibliographically approved

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Carbone, ParisHaridi, Seif

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