Summary: A fast incremental updating technique is presented for maintaining the constrained association rules discovered in the cases including insertion and deletion of transactions in the distributed databases. The concept of induced set is introduced. The efficient algorithm DUCAR (Distributed Updating of Constrained Association Rules), which includes algorithms ULFC (Updating of Local Frequent Constrained itemsets) and UGFC (Updating of Global Frequent Constrained itemsets), is proposed to update constrained association rules in distributed databases. The algorithm makes full use of the previous mining result to cut down the cost of updating frequent itemsets with item constraints in the distributed databases. The algorithm starts by computing the highest \(n\) level frequent itemsets in the original databases, and generates small number of candidate itemsets by exploring pruning technique. Finally, algorithm DUCAR is implemented by Java and a group of dataset is applied to test the performance of algorithm and the experiment result is compared with other algorithm. The experiment results show that the algorithm is effective and efficient.