Abstract: As the most existing stream clustering algorithms can not generate online clustering results in real-time,an online data stream clustering algorithm is proposed by using sliding windows and density-based grid storage structure.The algorithm achieves a rapid speed for online clustering data stream and it can provide users with real-time clustering results and reflect the dynamic evolution of data streams.Experimental results show that the algorithm proposed has a good capacity of dealing with rapid evolutional data stream and have a good clustering quality.