Chen, Kun and Wang, Jia (2023) Scheduling Hybrid Spark Jobs Based on Deep Reinforcement Learning. In: Proceedings of the 2nd International Conference on Bigdata Blockchain and Economy Management, ICBBEM 2023, May 19–21, 2023, Hangzhou, China.
![[thumbnail of 55439.pdf]](http://eprints.eai.eu/style/images/fileicons/application_pdf.png "55439.pdf")
PDF
55439.pdf
Download (2MB)
Abstract
As a popular big data computing framework, Spark requires effective job scheduling to optimize resource utilization and execute applications efficiently. However, the hy-brid jobs (jobs with and without deadlines) and the heterogeneous clusters bring great challenges for job scheduling. In this pape
| Item Type: | Conference or Workshop Item (UNSPECIFIED) |
|---|---|
| Date Deposited: | 04 Mar 2026 16:34 |
| Last Modified: | 17 Apr 2026 02:30 |
| URI: | http://eprints.eai.eu/id/eprint/44357 |
Actions (login required)
- View Item