OLAP (online analytical processing) queries usually involve multi-table joining. As a result, how to improve the performance of multi-table joining becomes a key issue for OLAP query processing. A method of distortional multi-table joining index is proposed, which can achieve better performance on the aspect of multi-table joining than parallel multi-joining algorithm and joining index. Based on query model-base, in which queries are expressed in SQL, the algorithm is used to build a series of distortional multi-table joining fact tables and indexes of them. In particular queries, dimensional tables join with distortional multi-table joining fact tables instead of fact tables, and further more, distortional multi-join indexes can be dynamically updated in query processing. Theoretical analysis and experimental results show that distortional multi-table joining index is an efficient method for multi-table joining in data warehouse.