Distributed Query Processing Using Partitioned Inverted Files

In this paper, we study query processing in a distributed text database. The novelty is a real distributed architecture implementation that offers concurrent query service. The distributed system adopts a network of workstations model and the client-server paradigm. The document collection is indexed with an inverted file. We adopt two distinct strategies of index partitioning in the distributed system, namely local index partitioning and global index partitioning. In both strategies, documents are ranked using the vector space model along with a document filtering technique for fast ranking. We evaluate and compare the impact of the two index partitioning strategies on query processing performance. Experimental results on retrieval efficiency show that, within our framework, the global index partitioning outperforms the local index partitioning.