Application of Batch and Stream Collaborative Computing in Urban Traffic Data Processing

Analysis of urban traffic data has obtained a great attention in recent years. In the study of urban traffic data processing, the batch computing based on historical data and the stream computing based on real-time data are isolated, and the two computing frameworks are not synergized. Therefore, a method of urban traffic data processing based on batch and stream collaborative computing is proposed. Batch computing has the advantage of high throughput, so it is more suitable for calculating the historical data of urban traffic and the results of stream computing deeply. Stream computing with the advantage of low delay can be used to calculate the traffic data in real time, combined with the results of batch computing, then the conclusion of urban traffic data processing are more comprehensive and accurate.