Packet classification is the fundamental function of network, and researchers have proposed many packet classification solutions in the past two decades. Among them, the decision tree algorithm for packet classification has received extensive attention and in-depth research due to its high throughput, suitable for multiple fields and pipelining. The recent research on the decision tree algorithm for packet classification was introduced, the geometric meaning, common techniques and test benchmarks of the decision tree algorithm were described, and the decision tree algorithm from the two dimensions of node cutting technology and rule set grouping technology were systematically analyzed. The typical algorithms of the two types of common technologies for building decision tree were introduced respectively, the design ideas and characteristics of various algorithms were compared, and their applicable scenarios were given. The conclusion and discuss the future work of decision tree algorithms were stated out.