Application of Hadoop-Based Cloud Computing in Teaching Platform Research

Chang Liu
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引用次数: 1

Abstract

This article explains the knowledge properties for characterization and research outcomes. It deals with developing and integrating the Hadoop cloud computing platform. The platform utilized in this paper is a one-piece learning algorithm, a statistical model and a cloud-based selection model. Hadoop supports this model, which is suitable for data size computing. We develop Cloud Computing integrated Autocorrelation Function (CCiACF) computation model based on Hadoop learning and implement an efficient teaching platform research data processing and correlation system. Multiple simulations are conducted on the Hadoop platform under various operating conditions to check the training ability’s exactness and characteristics. The Spark Structure of this research is to successfully and effectively develop computational system performance and improve teaching platform research models using Hadoop based cloud computing. Various experimental studies have been performed, and findings indicate that the method proposed is highly successful in data collection, governance and analysis.
基于hadoop的云计算在教学平台中的应用研究
本文解释了表征和研究成果的知识属性。它涉及Hadoop云计算平台的开发和集成。本文使用的平台是一个整体学习算法,一个统计模型和一个基于云的选择模型。Hadoop支持这种模型,适合于数据大小的计算。开发了基于Hadoop学习的云计算集成自相关函数(CCiACF)计算模型,实现了一个高效的教学平台研究数据处理与关联系统。在Hadoop平台上进行了多种操作条件下的多次仿真,验证了训练能力的准确性和特点。本研究的Spark结构是利用基于Hadoop的云计算成功有效地开发计算系统性能和改进教学平台研究模型。已经进行了各种实验研究,结果表明所提出的方法在数据收集,治理和分析方面非常成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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