Querying Semistructured Data with Compression in Distributed Environments

Abstract

As data management applications grow more complex, they are likely to need efficient distributed query processing. In Distributed Database Systems complete replication consists of maintaining complete copies of the database at each site; this has advantages such as highest locality of reference, highest reliability, availability, and is best for reading. The most promising and dominant data format for data processing and representing on the Internet is the semistructured data form termed XML. XML data has no fixed schema; it evolved and is self describing which results in management difficulties compared to, for example relational data. It is therefore a major challenge for the database community to design query languages and storage methods that can retrieve semistructured data. In this paper, we present a storing and querying scheme for semistructured data views of relational form in distributed environments. The proposed technique stores path dictionary, word dictionary, attribute dictionary, and the complete compressed replication of semistructured data in each distributed site of the DDBS. The presented technique provides query performance improvement due to the compression of semistructured data.