The incremental updating research of frequent itemsets is an important data mining problem in data mining fields. Many sequential algorithms have been proposed for incremental updating of frequent itemsets. However, very little work has been done in updating frequent itemsets in distributed environment. In this paper, the algorithm FUAGFI (fast updating algorithm for globally frequent itemsets) is introduced in the case of inserting, which efficiently utilizes the created locally frequent pattern trees and the mined globally frequent itemsets. Therefore, FUAGFI uses far less communication overhead and obviously improves updating efficiency of globally frequent itemsets. Experimental results show the feasibility and effectiveness of the algorithm.