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Failure Transparency in Stateful Dataflow Systems

Authors Aleksey Veresov , Jonas Spenger , Paris Carbone , Philipp Haller

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Author Details

Aleksey Veresov
  • EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
Jonas Spenger
  • EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
Paris Carbone
  • EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
  • Digital Systems, RISE Research Institutes of Sweden, Stockholm, Sweden
Philipp Haller
  • EECS and Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden

Funding

This work was partially funded by Digital Futures under a Research Pairs Consolidator grant (PORTALS).

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Aleksey Veresov, Jonas Spenger, Paris Carbone, and Philipp Haller. Failure Transparency in Stateful Dataflow Systems. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 42:1-42:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024) https://doi.org/10.4230/LIPIcs.ECOOP.2024.42

Abstract

Failure transparency enables users to reason about distributed systems at a higher level of abstraction, where complex failure-handling logic is hidden. This is especially true for stateful dataflow systems, which are the backbone of many cloud applications. In particular, this paper focuses on proving failure transparency in Apache Flink, a popular stateful dataflow system. Even though failure transparency is a critical aspect of Apache Flink, to date it has not been formally proven. Showing that the failure transparency mechanism is correct, however, is challenging due to the complexity of the mechanism itself. Nevertheless, this complexity can be effectively hidden behind a failure transparent programming interface. To show that Apache Flink is failure transparent, we model it in small-step operational semantics. Next, we provide a novel definition of failure transparency based on observational explainability, a concept which relates executions according to their observations. Finally, we provide a formal proof of failure transparency for the implementation model; i.e., we prove that the failure-free model correctly abstracts from the failure-related details of the implementation model. We also show liveness of the implementation model under a fair execution assumption. These results are a first step towards a verified stack for stateful dataflow systems.

Subject Classification

ACM Subject Classification
  • Theory of computation → Operational semantics
  • Software and its engineering → Checkpoint / restart
Keywords
  • Failure transparency
  • stateful dataflow
  • operational semantics
  • checkpoint recovery

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