Real-time user-click recognition based on spark streaming

With the rapid development of internet, data produced by users tends to be larger. The web page structure is becoming more and more complex and contains more and more different types of embedded objects as well. How to identify the user click requests from a large number of data set, is the first step as well as one of the difficulty of analysis of user behavior. Based on the spark streaming algorithm and some other previous algorithms, this paper proposes a real-time user-click recognition algorithm. The experimental results show that our algorithm is with high accuracy and is suitable for large scale data processing.