Optimizing updates of recursive XML views of relations

XML publishing has been an emerging technique for transforming (portions of) a relational database into an XML document, for example, to facilitate interoperability between heterogeneous applications. Such applications may update the XML document and the source relational database must be updated accordingly. In this paper, we consider such XML documents as (possibly) recursively defined XML views of relations. We propose new optimization techniques to efficiently support XML view updates specified via an XPATH expression with recursion and complex filters. The main novelties of our techniques are: (1) we propose a space-efficient relational encoding of recursive XML views; and (2) we push the bulk of update processing inside a relational database. Specifically, a compressed representation of the XML views is stored as extended shared-inlining relations. A space-efficient and updatable 2-hop index is used to optimize XPATH evaluation on XML views. Updates of the XML views are evaluated on these relations and index. View update translation is handled by a heuristic procedure inside a relational database, as opposed to previous middleware approaches. We present an experimental study to demonstrate the effectiveness of our proposed techniques.     

Sort-sharing-aware query processing

Many database applications require sorting a table (or relation) over multiple sort orders. Some examples include creation of multiple indices on a relation, generation of multiple reports from a table, evaluation of a complex query that involves multiple instances of a relation, and batch processing of a set of queries. In this paper, we study how to optimize multiple sortings of a table. We investigate the correlation between sort orders and exploit sort-sharing techniques of reusing the (partial) work done to sort a table on a particular order for another order. Specifically, we introduce a novel and powerful evaluation technique, called cooperative sorting, that enables sort sharing between seemingly non-related sort orders. Subsequently, given a specific set of sort orders, we determine the best combination of various sort-sharing techniques so as to minimize the total processing cost. We also develop techniques to make a traditional query optimizer extensible so that it will not miss the truly cheapest execution plan with the sort-sharing (post-) optimization turned on. We demonstrate the efficiency of our ideas with a prototype implementation in PostgreSQL and evaluate the performance using both TPC-DS benchmark and synthetic data. Our experimental results show significant performance improvement over the traditional evaluation scheme.