The invention discloses a dynamic mining method for distributed data streaming, which comprises the following steps of: S1, by each local node, collecting current data blocks at a current t moment andcarrying out micro cluster processing; S2, by each local node, carrying out incremental micro cluster updating of a local mode; S3, executing a local mode transmission stage, i.e., uploading the local mode of each local node at the t moment to a central node; S4, by the central node, after receiving the local modes of all the local nodes at the t moment, reconstructing a global sample data set onthe basis of a micro cluster; and S5, by the central node, executing a basic learner for new learning on the basis of the global sample data set, and carrying out incremental updating of a global mode in a current state on the basic learner for new learning. According to the invention, in a local mining mode, data can be processed locally to the greatest extent, so as to reduce the probability that the data is discarded.