Application of Workflow Technology for Big Data Analysis Service

This study presents a lightweight representational state transfer-based cloud workflow system to construct a big data intelligent software-as-a-service (SaaS) platform. The system supports the dynamic construction and operation of an intelligent data analysis application, and realizes rapid development and flexible deployment of the business analysis process that can improve the interaction and response time of the process. The proposed system integrates offline-batch and online-streaming analysis models that allow users to conduct batch and streaming computing simultaneously. Users can rend cloud capabilities and customize a set of big data analysis applications in the form of workflow processes. This study elucidates the architecture and application modeling, customization, dynamic construction, and scheduling of a cloud workflow system. A chain workflow foundation mechanism is proposed to combine several analysis components into a chain component that can promote efficiency. Four practical application cases are provided to verify the analysis capability of the system. Experimental results show that the proposed system can support multiple users in accessing the system concurrently and effectively uses data analysis algorithms. The proposed SaaS workflow system has been used in network operators and has achieved good results.