Repositori institucional URV
| Autor/s de la URV: | Eizaguirre Suárez, Germán Telmo / Sanchez Artigas, Marc |
| Autor segons l'article: | Eizaguirre, GT; Sánchez-Artigas, M |
| Adreça de correu electrònic de l'autor: | germantelmo.eizaguirre@urv.cat germantelmo.eizaguirre@urv.cat marc.sanchez@urv.cat marc.sanchez@urv.cat |
| Identificador de l'autor: | 0000-0002-2865-9873 0000-0002-2865-9873 0000-0002-9700-7318 0000-0002-9700-7318 |
| Any de publicació de la revista: | 2024-01-01 |
| Tipus de publicació: | Journal Publications |
| Referència de l'ítem segons les normes 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 |
| Referència a l'article segons font original: | Journal Of Parallel And Distributed Computing. 183 104763- |
| Resum: | 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. |
| DOI de l'article: | 10.1016/j.jpdc.2023.104763 |
| Enllaç font original: | https://www.sciencedirect.com/science/article/pii/S0743731523001338 |
| Versió de l'article dipositat: | info:eu-repo/semantics/publishedVersion |
| Accès a la llicència d'ús: | https://creativecommons.org/licenses/by/3.0/es/ |
| Departament: | Enginyeria Informàtica i Matemàtiques |
| URL Document de llicència: | https://repositori.urv.cat/ca/proteccio-de-dades/ |
| Àrees temàtiques: | Theoretical computer science Software Hardware and architecture Computer science, theory & methods Computer networks and communications Ciência da computação Artificial intelligence |
| Paraules clau: | Shuffle Serverless computing Object storage I/o optimization |
| Entitat: | Universitat Rovira i Virgili |
| Data d'alta del registre: | 2026-05-09 |
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