Interactive SQL query suggestion: Making databases user-friendly

SQL is a classical and powerful tool for querying relational databases. However, it is rather hard for inexperienced users to pose SQL queries, as they are required to be proficient in SQL syntax and have a thorough understanding of the underlying schema. To give users gratification, we propose SQLSUGG, an effective and user-friendly keyword-based method to help various users formulate SQL queries. SQLSUGG suggests SQL queries as users type in keywords, and can save users' typing efforts and help users avoid tedious SQL debugging. To achieve high suggestion effectiveness, we propose queryable templates to model the structures of SQL queries. We propose a template ranking model to suggest templates relevant to query keywords. We generate SQL queries from each suggested template based on the degree of matchings between keywords and attributes. For efficiency, we propose a progressive algorithm to compute top-k templates, and devise an efficient method to generate SQL queries from templates. We have implemented our methods on two real data sets, and the experimental results show that our method achieves high effectiveness and efficiency.