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State Management in Apache Flink : Consistent Stateful Distributed Stream Processing

Carbone, Paris (författare)
KTH,Programvaruteknik och Datorsystem, SCS
Ewen, Stephan (författare)
data Artisans
Fóra, Gyula (författare)
King Digital Entertainment Limited
visa fler...
Haridi, Seif, 1953- (författare)
KTH,Programvaruteknik och Datorsystem, SCS
Richter, Stefan (författare)
data Artisans
Tzoumas, Kostas (författare)
data Artisans
visa färre...
 (creator_code:org_t)
2017-08
2017
Engelska.
Ingår i: Proceedings of the VLDB Endowment. - : ACM Digital Library. - 2150-8097. ; 10, s. 1718-1729
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • 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 large deployment insights exhibiting the low performance trade-offs of our approach and the general benefits of exploiting asynchrony in continuous, yet sustainable system deployments.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)

Nyckelord

stream processing
data management
computer systems
databases
data processing
data science
big data
Datalogi
Computer Science

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