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arXiv:1907.08302cs.PF

Quantitative Impact Evaluation of an Abstraction Layer for Data Stream Processing Systems

Guenter Hesse, Christoph Matthies, Kelvin Glass, Johannes Huegle, Matthias Uflacker

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

With the demand to process ever-growing data volumes, a variety of new data stream processing frameworks have been developed. Moving an implementation from one such system to another, e.g., for performance reasons, requires adapting existing applications to new interfaces. Apache Beam addresses these high substitution costs by providing an abstraction layer that enables executing programs on any of the supported streaming frameworks. In this paper, we present a novel benchmark architecture for comparing the performance impact of using Apache Beam on three streaming frameworks: Apache Spark Streaming, Apache Flink, and Apache Apex. We find significant performance penalties when using Apache Beam for application development in the surveyed systems. Overall, usage of Apache Beam for the examined streaming applications caused a high variance of query execution times with a slowdown of up to a factor of 58 compared to queries developed without the abstraction layer. All developed benchmark artifacts are publicly available to ensure reproducible results.

arXiv comments
Journal reference
2019 International Conference on Distributed Computing Systems (ICDCS), pp. 1381-1392
DOI
doi:10.1109/ICDCS.2019.00137
Subjects
cs.PFPerformance cs.DCDistributed, Parallel, and Cluster Computing

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Linked by 1 identifiable commenter in 2 comments across 2 threads, from Nov 2019 to Dec 2019. Found in 1 HN submission from Mar 2020 to Mar 2020. Open submission discussions.

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Discussed in comments2 threads

    • Check this reference out: https://arxiv.org/pdf/1907.08302.pdf “ Our benchmark results show that Apache Beam has a noticeable impact on the performance of DSPSs in almost all cases. Programs developed using Apache Beam suffered from a slowdown of up to a factor of 58 in the…

      faizshahView on HNParent context

    • So I have a bad history with Cloud Dataflow. I like BigQuery and Flink a lot, but a lot of companies seem to be switching over to Cloud Dataflow. In my experience Cloud Dataflow's cost is really unpredictable and DataPrep's pipelines (on DataFlow) were far more inefficient…

      faizshahView on HNParent context

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