A parallel sequence stream analysis algorithm named FTPSA (proactive fault-tolerant parallel sequence stream analysis algorithm) is proposed in order to deal with sequence stream’s adaptive analysis in noisy environment, which is based on proactive fault-tolerant knowledge learning. The algorithm utilizes learning network to describe sequence stream and stores those in 0-1 matrix, delaminates the low-proportion and the high-proportion noisy data and utilizes fault-tolerant and structure-optimize learning methods, utilizes global filtration to depress memory cost and communication cost. The experimental results on real stream show that FTPSA algorithm is more fault-tolerant, scaleable, accurate, and less memory.