Abstract:NL2SQL refers to a technology that automatically converts query expressed in natural language into a structured SQL expression, which can be parsed and executed by the DBMS. NL2SQL can provide ordinary users with a natural interactive interface for database query access, thereby realizing question-answering atop database systems. NL2SQL for complex queries is now a research hotspot in the database community. The most prevalent approach uses the sequence-to-sequence (Seq2seq) encoder and decoder to convert complex natural language to SQL. However, most of the existing work focuses on English language. This approach is not ready to address the special colloquial expressions in Chinese queries. In addition, the existing work cannot correctly output query clauses containing complex calculation expressions. To solve the above problems, this study proposes to use a tree model instead of the sequence representation. The proposed approach disassembles complex queries from top to down to comprise a multi-way tree, where the tree nodes represent the elements of SQL. It uses a depth-first search to predict and generate SQL statements. The proposed approach has achieved the championship and 1st runner-up in two official tests of DuSQL Chinese NL2SQL Competition. The experimental results confirm the effectiveness of the proposed approach.