Pathfinder/MonetDB: making XQuery scale using the relational approach

Опубликовано 6 сентября 2016, 5:16

Using a relational DBMS as back-end engine for an XQuery processing system leverages relational query optimization and scalable query processing strategies provided by mature DBMS engines in the XML domain. Though a lot of theoretical work has been done in this area and various solutions have been proposed, no complete systems have been made available so far to give the hard (practical) evidence that this is a viable approach. In this talk, I describe our first iteration of using an extensible RDBMS to build a relational XQuery processor. Performance results for the XMark benchmark show that the system is capable of evaluating XQuery queries efficiently, even if the input XML documents become huge. We additionally present further contributions such as loop-lifted staircase join, techniques to derive order properties and to reduce sorting effort in the generated relational algebra plans, as well as a method for recognizing XQuery join patterns, which ΓÇô taken together ΓÇô enabled us to reach our performance and scalability goals.