This article discusses the classification and research performance information properties. It also discusses construction and application of the Hadoop cloud computing platform. The model presented in this article is a one piece learning algorithm which is a predictive model and a model of cloud based data collection. This model is supported by Hadoop which is suitable for computing with different data sizes. A large number of simulations are performed on the Hadoop platform, under different working conditions, to verify the accuracy and characteristics of the training skill. Spark framework of this research is to develop computational engine efficiency and improve rain prediction models successfully and effectively using big data and Hadoop learning. Therefore, the planned high timeliness and accuracy of real-time hurricane forecast with rain, can solve the problem.

本文讨论分类和研究性能信息属性。它还讨论了Hadoop云计算平台的构建和应用。本文介绍的模型是一种整体学习算法，它是一种预测模型和一种基于云的数据收集模型。Hadoop支持该模型，该模型适用于使用不同数据大小的计算。在不同的工作条件下，在Hadoop平台上进行了大量模拟，以验证培训技能的准确性和特征。这项研究的Spark框架旨在利用大数据和Hadoop学习来成功，有效地开发计算引擎效率并改善降雨预测模型。因此，计划的实时性和降雨预报的实时性和准确性很高，