支持实时流计算应用的关键技术研究进展

In order to perform knowledge mining and management, information systems need to process various forms of data, including stream data. Stream data have the characteristics of large data scale, fast generation speed, and strong timeliness of the knowledge contained in them. Therefore, it is very important for knowledge management of information systems to develop stream processing technology that supports real-time stream processing applications. Stream processing systems (SPSs) can be traced back to the 1990s, and they have undergone significant development since then. However, current diverse knowledge management needs and the new generation of hardware architectures have brought new challenges and opportunities for SPSs, and a series of technical research on stream processing ensues. This study introduces the basic requirements and development history of SPSs and then analyzes relevant technologies in the SPS field in terms of four aspects: programming interface, execution plan, resource scheduling, and fault tolerance. Finally, this study predicts the research directions and development trends of stream processing technology in the future.