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Implicit Parallelism through Deep Language Embedding

Authors:

Alexander Alexandrov,

Asterios Katsifodimos,

Georgi Krastev, and

Volker MarklAuthors Info & Claims

ACM SIGMOD Record, Volume 45, Issue 1

Pages 51 - 58

https://doi.org/10.1145/2949741.2949754

Published: 02 June 2016 Publication History

Abstract

Parallel collection processing based on second-order functions such as map and reduce has been widely adopted for scalable data analysis. Initially popularized by Google, over the past decade this programming paradigm has found its way in the core APIs of parallel dataflow engines such as Hadoop's MapReduce, Spark's RDDs, and Flink's DataSets. We review programming patterns typical of these APIs and discuss how they relate to the underlying parallel execution model. We argue that fixing the abstraction leaks exposed by these patterns will reduce the cost of data analysis due to improved programmer productivity. To achieve that, we first revisit the algebraic foundations of parallel collection processing. Based on that, we propose a simplified API that (i) provides proper support for nested collection processing and (ii) alleviates the need of certain second-order primitives through comprehensions -- a declarative syntax akin to SQL. Finally, we present a metaprogramming pipeline that performs algebraic rewrites and physical optimizations which allow us to target parallel dataflow engines like Spark and Flink with competitive performance.

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Cited By

Villarroya SBaumann P(2023)A survey on machine learning in array databasesApplied Intelligence10.1007/s10489-022-03979-253:9(9799-9822)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10489-022-03979-2
Simonov VKhairetdinov M(2022)Automatic Decomposition of a Sequential Algorithm for MapReduce Frameworks2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)10.1109/SIBIRCON56155.2022.10017034(1780-1783)Online publication date: 11-Nov-2022
https://doi.org/10.1109/SIBIRCON56155.2022.10017034
Smith JBenedikt MMoore BNikolic M(2021)TraNCEProceedings of the VLDB Endowment10.14778/3476311.347633014:12(2727-2730)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.14778/3476311.3476330
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Index Terms

Implicit Parallelism through Deep Language Embedding
1. Information systems
  1. Data management systems
    1. Query languages

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image ACM SIGMOD Record

ACM SIGMOD Record Volume 45, Issue 1

March 2016

73 pages

ISSN:0163-5808

DOI:10.1145/2949741

Editors:
Yanlei Diao
University of Massachusetts Amherst
,
Vanessa Braganholo
Universidade Federal Fluminense
,
Marco Brambilla
Politecnico di Milano
,
Chee Yong Chan
National University of Singapore
,
Rada Chirkova
North Carolina State University
,
Zackary Ives
University of Pennsylvania
,
Anastasios Kementsietsidis
Google Research
,
Jeffrey Naughton
University of Wisconsin-Madison
,
Olga Papaemmanoui
Brandeis Univesity
,
Aditya Parameswaran
University of Illinois
,
Anish Das Sarma
Google Research
,
Alkis Simitsis
HP Labs
,
Wang-Chiew Tan
University of California Santa Cruz
,
Nesime Tatbul
MIT CSAIL
,
Marianne Winslett
University of Illinois
,
Jun Yang
Duke University

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Copyright © 2016 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 02 June 2016

Published in SIGMOD Volume 45, Issue 1

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Cited By

Villarroya SBaumann P(2023)A survey on machine learning in array databasesApplied Intelligence10.1007/s10489-022-03979-253:9(9799-9822)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10489-022-03979-2
Simonov VKhairetdinov M(2022)Automatic Decomposition of a Sequential Algorithm for MapReduce Frameworks2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences (SIBIRCON)10.1109/SIBIRCON56155.2022.10017034(1780-1783)Online publication date: 11-Nov-2022
https://doi.org/10.1109/SIBIRCON56155.2022.10017034
Smith JBenedikt MMoore BNikolic M(2021)TraNCEProceedings of the VLDB Endowment10.14778/3476311.347633014:12(2727-2730)Online publication date: 1-Jul-2021
https://dl.acm.org/doi/10.14778/3476311.3476330
Makrynioti NVassalos V(2021)Declarative Data Analytics: A SurveyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2019.295808433:6(2392-2411)Online publication date: 1-Jun-2021
https://doi.org/10.1109/TKDE.2019.2958084
Smith JBenedikt MNikolic MShaikhha A(2020)Scalable querying of nested dataProceedings of the VLDB Endowment10.5555/3430915.344244114:3(445-457)Online publication date: 14-Dec-2020
Smith JBenedikt MNikolic MShaikhha A(2020)Scalable querying of nested dataProceedings of the VLDB Endowment10.14778/3430915.343093314:3(445-457)Online publication date: 1-Nov-2020
https://dl.acm.org/doi/10.14778/3430915.3430933
Alexandrov AKrastev GMarkl V(2019)Representations and Optimizations for Embedded Parallel Dataflow LanguagesACM Transactions on Database Systems10.1145/328162944:1(1-44)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3281629
Markl V(2018)Mosaics in Big DataProceedings of the 12th ACM International Conference on Distributed and Event-based Systems10.1145/3210284.3214344(7-13)Online publication date: 25-Jun-2018
https://dl.acm.org/doi/10.1145/3210284.3214344
Ahmad MCheung ADas GJermaine CBernstein P(2018)Automatically Leveraging MapReduce Frameworks for Data-Intensive ApplicationsProceedings of the 2018 International Conference on Management of Data10.1145/3183713.3196891(1205-1220)Online publication date: 27-May-2018
https://dl.acm.org/doi/10.1145/3183713.3196891
Fegaras LNoor M(2018)Compile-Time Code Generation for Embedded Data-Intensive Query Languages2018 IEEE International Congress on Big Data (BigData Congress)10.1109/BigDataCongress.2018.00008(1-8)Online publication date: Jul-2018
https://doi.org/10.1109/BigDataCongress.2018.00008
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