Query Performance Optimization in XML Data Warehouses

TL;DR

This paper introduces optimization techniques for XML data warehouses, including a join index and a view selection strategy, significantly improving query response times in decision-support applications.

Contribution

It presents novel join indexing and view clustering methods tailored for XML warehouses, enhancing performance over existing native XML DBMSs.

Findings

Optimized query response times demonstrated in experiments.

Join index reduces the need for costly join operations.

Clustering-based view selection improves query efficiency.

Abstract

XML data warehouses form an interesting basis for decision-support applications that exploit complex data. However, native-XML database management systems (DBMSs) currently bear limited performances and it is necessary to research for ways to optimize them. In this chapter, we present two such techniques. First, we propose a join index that is specifically adapted to the multidimensional architecture of XML warehouses. It eliminates join operations while preserving the information contained in the original warehouse. Second, we present a strategy for selecting XML materialized views by clustering the query workload. To validate these proposals, we measure the response time of a set of decision-support XQueries over an XML data warehouse, with and without using our optimization techniques. Our experimental results demonstrate their efficiency, even when queries are complex and data are voluminous.