Author, as appears in the article.: Eizaguirre, GT; Sánchez-Artigas, M
Department: Enginyeria Informàtica i Matemàtiques
URV's Author/s: Eizaguirre Suárez, Germán Telmo / Sanchez Artigas, Marc
Keywords: Shuffle Serverless computing Object storage I/o optimization
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.
Thematic Areas: Theoretical computer science Software Matemática / probabilidade e estatística Interdisciplinar Hardware and architecture Engenharias iv Engenharias iii Computer science, theory & methods Computer networks and communications Ciência da computação Artificial intelligence
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: germantelmo.eizaguirre@urv.cat germantelmo.eizaguirre@urv.cat marc.sanchez@urv.cat
Author identifier: 0000-0002-9700-7318
Record's date: 2024-08-03
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.sciencedirect.com/science/article/pii/S0743731523001338
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Journal Of Parallel And Distributed Computing. 183
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(), -. DOI: 10.1016/j.jpdc.2023.104763
Article's DOI: 10.1016/j.jpdc.2023.104763
Entity: Universitat Rovira i Virgili
Journal publication year: 2024
Publication Type: Journal Publications