Focused on the characteristics of processing semi-structure eXtensible Markup Language (XML) streaming data such as the stream real-time arriving continuously, requiring to be read sequentially and only once into memory, the query must be processed on the fly and usable buffer size is very little, and concerned the current status for limitation of query expression and inefficiency in practical applications of processing large scale data, QXList method was proposed for massive data processing based on SAX parsing XML. Data model and algorithm integrated framework were defined firstly. The integrated methods to process predicate and wildcard were discussed in detail. Layer value was used to determine the relationship of two elements and relational pointer was constructed to link multiple candidate nodes' lists to get query results in this method. Two optimal points were analyzed for decreasing buffer size. The experimental results show that the proposed approach is effective and efficient to this problem, and outperforms the state-of-the-art algorithms about 30 percent such as QStream++ and query engines MonetDB and SAXSON especially for large processed data. At the same time, memory usage is nearly constant.