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A Seer knows best: Auto-tuned object storage shuffling for serverless analytics - imarina:9330486

URV's Author/s:Eizaguirre Suárez, Germán Telmo / Sanchez Artigas, Marc
Author, as appears in the article.:Eizaguirre, GT; Sánchez-Artigas, M
Author's mail:germantelmo.eizaguirre@urv.cat
germantelmo.eizaguirre@urv.cat
marc.sanchez@urv.cat
marc.sanchez@urv.cat
Author identifier:0000-0002-2865-9873
0000-0002-2865-9873
0000-0002-9700-7318
0000-0002-9700-7318
Journal publication year:2024-01-01
Publication Type:Journal Publications
APA:Eizaguirre, GT; Sánchez-Artigas, M (2024). A Seer knows best: Auto-tuned object storage shuffling for serverless analytics. Journal Of Parallel And Distributed Computing, 183(), 104763-. DOI: 10.1016/j.jpdc.2023.104763
Paper original source:Journal Of Parallel And Distributed Computing. 183 104763-
Abstract:Serverless platforms offer high resource elasticity and pay-as-you-go billing, making them a compelling choice for data analytics. To craft a “pure” serverless solution, the common practice is to transfer intermediate data between serverless functions via serverless object storage (IBM COS; AWS S3). However, prior works have led to inconclusive results about the performance of object storage systems, since they have left large margin for optimization. To verify that object storage has been underrated, we devise a novel shuffle manager for serverless data analytics called SEER. Specifically, SEER dynamically chooses between two shuffle algorithms to maximize performance. The algorithm choice is made online based on some predictive models, and very importantly, without end users having to specify intermediate shuffle data sizes at the time of the job submission. We integrate SEER with PyWren-IBM [31], a well-known serverless analytics framework, and evaluate it against both serverful (e.g., Spark) and serverless systems (e.g., Google BigQuery, Caerus [46] and SONIC [22]). Our results certify that our new shuffle manager can deliver performance improvements over them.
Article's DOI:10.1016/j.jpdc.2023.104763
Link to the original source:https://www.sciencedirect.com/science/article/pii/S0743731523001338
Paper version:info:eu-repo/semantics/publishedVersion
licence for use:https://creativecommons.org/licenses/by/3.0/es/
Department:Enginyeria Informàtica i Matemàtiques
Licence document URL:https://repositori.urv.cat/ca/proteccio-de-dades/
Thematic Areas:Theoretical computer science
Software
Hardware and architecture
Computer science, theory & methods
Computer networks and communications
Ciência da computação
Artificial intelligence
Keywords:Shuffle
Serverless computing
Object storage
I/o optimization
Entity:Universitat Rovira i Virgili
Record's date:2026-05-09
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