Spark 大数据集群环境下数据采集由采集单元部署的大量节点完成，是网

In the Spark big data cluster environment, data collection is completed by a large number of nodes deployed by the collection unit, which is the basis for network data security monitoring. After the data stream collection is completed, it will be securely stored for use in security monitoring. The data stream collected in the Spark environment includes structured data and unstructured data. The collection nodes need to be scattered in a complex network. The distributed data collection nodes are centralized and managed through the parallel node management strategy to optimize the Network data collection effect and efficiency

In spark big data cluster environment, data collection is completed by a large number of nodes deployed by the collection unit, which is the basis of network data security monitoring. After data flow collection, it will be safely stored for security monitoring. The data flow collected in spark environment includes structured data and unstructured data. The collection nodes need to be scattered in the complex network. The decentralized data collection nodes are centralized and managed through the parallelization node management strategy, so as to optimize the effect and efficiency of network data collection

In Spark big data cluster environment, data collection is completed by a large number of nodes deployed by the collection unit, which is the basis of network data security monitoring. After the data stream is collected, it will be safely stored for security monitoring. The data stream collected in Spark environment includes structured data and unstructured data. The collection nodes need to be scattered in a complex network. The scattered data collection nodes are centralized and managed by parallelization node management strategy to optimize the network data collection effect and efficiency.