XQzip: Querying compressed XML using structural indexing

XML makes data flexible in representation and easily portable on the Web but it also substantially inflates data size as a consequence of using tags to describe data. Although many effective XML compressors, such as XMill, have been recently proposed to solve this data inflation problem, they do not address the problem of running queries on compressed XML data. More recently, some compressors have been proposed to query compressed XML data. However, the compression ratio of these compressors is usually worse than that of XMill and that of the generic compressor gzip, while their query performance and the expressive power of the query language they support are inadequate. In this paper, we propose XQzip, an XML compressor which supports querying compressed XML data by imposing an indexing structure, which we call Structure Index Tree (SIT), on XML data. XQzip addresses both the compression and query performance problems of existing XML compressors. We evaluate XQzip's performance extensively on a wide spectrum of benchmark XML data sources. On average, XQzip is able to achieve a compression ratio 16.7% better and a querying time 12.84 times less than another known queriable XML compressor. In addition, XQzip supports a wide scope of XPath queries such as multiple, deeply nested predicates and aggregation.