Query suggestion can effectively alleviate the input burden for users, eliminate the query ambiguity, and improve theconvenience and accuracy of information retrieval. With the development of e-commerce, query suggestion is also popular in the product search of e-commerce applications.However, traditional query suggestion methods for Web search are not fully applicable in e-commerce applications. Based on the analysis of different query suggestion techniques, an e-commerce query suggestion method based on log mining is presented, which considersboth the search behaviors and shopping behaviors of users.MapReduce is used in log mining to generate the query words in an offline mode, and query suggestions are offeredto users in an online mode. Experimental results show that the presented method can improves the accuracy of querysuggestions and has good performance.