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联邦学习场景中Piraeus存储网络应用系统设计

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随着大数据与云原生的不断融合,大数据云原生已逐渐成为大数据技术框架未来的发展趋势.传统大数据平台是指以处理海量数据存储、计算及不间断流数据的实时计算等场景为主的一套基础设施.典型的大数据平台包括Hadoop系列、Spark、Flume、Flink、Kafka等大数据生态组件.如今,面对海量数据爆发式的增长,对大数据的管理和使用提出了更高、更新的要求,在此背景下,以"弹性、敏捷、开放"著称的云原生技术赋予了大数据平台新的含义,云原生大数据平台开始登场,发挥大数据的真正生产力.介绍了如何利用好云原生技术对大数据进行技术创新、场景落地,最终赋能企业的数字化战略.
Application System Design of Storage Network Piraeus in Federated Learning Scenario
With the continuous integration of big data and cloud native,big data cloud native becomes the future development trend of big data technology framework.A traditional big data platform refers to a set of infrastructure that mainly deals with scenarios such as massive data storage,computing,and real-time computing of uninterrupted streaming data.Typical big data platforms include big data ecosystem components such as Hadoop series,Spark,Flume,Flink,and Kafka.Today,in the face of the explosive growth of massive data,higher and updated requirements are put forward for the management and use of big data.Cloud-native technology known as"elastic,agile,and open"gives big data platforms new meaning,cloud-native big data platforms appear,bringing into play the true productivity of big data.This article introduces how to make good use of cloud n-ative technology to carry out technological innovation and scenario implementation of big data,and finally empower the digital strategy of enterprises.

big datacloud nativePiraeus storage network system

刘帅华、郭峰

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上海道客网络科技有限公司,上海 200233

大数据 云原生 Piraeus存储网络系统

2024

微型电脑应用
上海市微型电脑应用学会

微型电脑应用

CSTPCD
影响因子:0.359
ISSN:1007-757X
年,卷(期):2024.40(9)