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.
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