Deterministic Model for Distributed Speculative Stream Processing

Igor E. Kuralenok, Artem Trofimov, Nikita Marshalkin, Boris Novikov

Research output

1 Citation (Scopus)

Abstract

Users of modern distributed stream processing systems have to choose between non-deterministic computations and high latency due to a need in excessive buffering. We introduce a speculative model based on MapReduce-complete set of operations that allows us to achieve determinism and low-latency. Experiments show that our prototype can outperform existing solutions due to low overhead of optimistic synchronization.

Original languageEnglish
Title of host publicationAdvances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings
EditorsAndras Benczur, Tomas Horvath, Bernhard Thalheim
PublisherSpringer
Pages233-246
Number of pages14
ISBN (Print)9783319983974
DOIs
Publication statusPublished - 1 Jan 2018
Event22nd East-European Conference on Advances in Databases and Information Systems, ADBIS 2018 - Budapest
Duration: 2 Sep 20185 Sep 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11019 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd East-European Conference on Advances in Databases and Information Systems, ADBIS 2018
CountryHungary
CityBudapest
Period2/09/185/09/18

Fingerprint

Stream Processing
Deterministic Model
Latency
Synchronization
Determinism
Distributed Processing
MapReduce
Processing
Choose
Experiments
Prototype
Model-based
Experiment

Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kuralenok, I. E., Trofimov, A., Marshalkin, N., & Novikov, B. (2018). Deterministic Model for Distributed Speculative Stream Processing. In A. Benczur, T. Horvath, & B. Thalheim (Eds.), Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings (pp. 233-246). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11019 LNCS). Springer. https://doi.org/10.1007/978-3-319-98398-1_16
Kuralenok, Igor E. ; Trofimov, Artem ; Marshalkin, Nikita ; Novikov, Boris. / Deterministic Model for Distributed Speculative Stream Processing. Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings. editor / Andras Benczur ; Tomas Horvath ; Bernhard Thalheim. Springer, 2018. pp. 233-246 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Kuralenok, IE, Trofimov, A, Marshalkin, N & Novikov, B 2018, Deterministic Model for Distributed Speculative Stream Processing. in A Benczur, T Horvath & B Thalheim (eds), Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11019 LNCS, Springer, pp. 233-246, Budapest, 2/09/18. https://doi.org/10.1007/978-3-319-98398-1_16

Deterministic Model for Distributed Speculative Stream Processing. / Kuralenok, Igor E.; Trofimov, Artem; Marshalkin, Nikita; Novikov, Boris.

Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings. ed. / Andras Benczur; Tomas Horvath; Bernhard Thalheim. Springer, 2018. p. 233-246 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11019 LNCS).

Research output

TY - GEN

T1 - Deterministic Model for Distributed Speculative Stream Processing

AU - Kuralenok, Igor E.

AU - Trofimov, Artem

AU - Marshalkin, Nikita

AU - Novikov, Boris

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Users of modern distributed stream processing systems have to choose between non-deterministic computations and high latency due to a need in excessive buffering. We introduce a speculative model based on MapReduce-complete set of operations that allows us to achieve determinism and low-latency. Experiments show that our prototype can outperform existing solutions due to low overhead of optimistic synchronization.

AB - Users of modern distributed stream processing systems have to choose between non-deterministic computations and high latency due to a need in excessive buffering. We introduce a speculative model based on MapReduce-complete set of operations that allows us to achieve determinism and low-latency. Experiments show that our prototype can outperform existing solutions due to low overhead of optimistic synchronization.

KW - Data streams

KW - Distributed processing

KW - Drifting state

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DO - 10.1007/978-3-319-98398-1_16

M3 - Conference contribution

AN - SCOPUS:85051088792

SN - 9783319983974

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 233

EP - 246

BT - Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings

A2 - Benczur, Andras

A2 - Horvath, Tomas

A2 - Thalheim, Bernhard

PB - Springer

ER -

Kuralenok IE, Trofimov A, Marshalkin N, Novikov B. Deterministic Model for Distributed Speculative Stream Processing. In Benczur A, Horvath T, Thalheim B, editors, Advances in Databases and Information Systems - 22nd European Conference, ADBIS 2018, Proceedings. Springer. 2018. p. 233-246. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-98398-1_16