Toward full-text searching middleware over hierarchical documents

Currently, full-text searching can benefit from the emerging NoSQL databases and traditional indexing tools in the big data era. However, there are some drawbacks of current solutions. On one hand, the indexing documents lack of the hierarchy. On the other hand, big data have become the bottleneck of full-text searching. In the context of big data, we design a full-text searching middleware over hierarchical documents. We discuss the architecture of this middleware in detail. In addition, we propose a structure-independent hierarchical document model to present the hierarchical document. Moreover, the transformation engine is designed to translate the rich files into models. The core log event listener is responsible for capturing the changed documents and push them to the indexing storage at the same time. The experimental results show that our middleware is more advantageous than RDBMS with indexes and RDBMS with Lucene solutions.