基于贝叶斯网络的复杂事件大数据处理系统测试数据生成方法研究

伴随流式数据处理需求而产生的复杂事件处理技术，在处理具有多样性和流式特征数据方面性能表现突出，被广泛应用于复杂事件大数据处理系统中。针对复杂事件大数据处理系统测试需求，提出一种基于贝叶斯网络的复杂事件大数据处理系统测试数据生成方法，该方法以部分真实数据中的复杂事件结构关系及概率分布特征构建贝叶斯网络预测模型，生成具有真实数据结构特征与分布特征的复杂事件测试数据集。实验结果表明，提出的方法具有可行性。

Research on Complex Event Big data Processing System Test Data Generation Method Based on Bayesian Network

The complex event processing technology, which was accompanied by the requirement of streaming data processing, is widely used in complex event big data processing system in dealing with data that has diversity and flow features. Aiming at the requirements of testing for complex event big data processing system, a test data generation method for complex event big data processing system was proposed which based on Bayesian network. The method constructs Bayesian network prediction model relies on complex event structure relation and probability distribution feature in some real data, and generates a complex event test data set which have similarity structure and distribution characteristics with real data. The results of experiments show that the proposed method is feasible.