Adaptive memory reservation strategy for heavy workloads in the Spark environment

The rise of the Internet of Things (IoT) and Industry 2.0 has spurred a growing need for extensive data computing, and Spark emerged as a promising Big Data platform, attributed to its distributed in-memory computing capabilities. However, practical heavy workloads often lead to memory bottleneck is...

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Autors principals:	Bohan Li, Xin He, Junyang Yu, Guanghui Wang, Yixin Song, Shunjie Pan, Hangyu Gu
Format:	Artigo
Idioma:	Inglês
Publicat:	PeerJ Inc. 2024-11-01
Col·lecció:	PeerJ Computer Science
Matèries:	Adaptive memory reservation Task parallelism Storage location selection Spark environment
Accés en línia:	https://peerj.com/articles/cs-2460.pdf
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