A Near Metal Platform for Intensive Big Data Processing Using A Novel Approach

Autor:	Khalid Moussaid, Noureddine Abghour, Amina El Omri, Mohamed Rida, Noussair Fikri
Rok vydání:	2020
Předmět:	Big data processing Computer science Order (business) business.industry Distributed computing Spark (mathematics) Big data business
Zdroj:	Proceedings of the 2020 5th International Conference on Big Data and Computing.
Popis:	In this paper we present a new Golang based framework for distributed intensive data processing and also micro batching. It uses a novel approach, the persistent distributed channels, based on the concept of Share memory by communicating, and inspired from Resilient distributed datasets of Apache Spark. The architecture of our proposed system is considered as near-metal platform for Big Data operations in order to enhance the speed of massive data processing.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1f8406d9977e457f5999147103bb842f https://doi.org/10.1145/3404687.3404692 Zobrazit plný text záznamu