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Join queries involving many relations pose a severe challenge to today'squery optimisation techniques. To some extent, this is due to the fact thatthese techniques do not pay sufficient attention to structural properties ofthe query. In stark contrast, the Database Theory community has intensivelystudied structural properties of queries (such as acyclicity and variousnotions of width) and proposed efficient query evaluation techniques throughvariants of Yannakakis' algorithm. However, although most queries in practiceactually are acyclic or have low width, structure-guided query evaluationtechniques based on Yannakakis' algorithm have not found their way intomainstream database technology yet. The goal of this work is to address thisgap between theory and practice and to demonstrate that the consideration ofquery structure can improve query evaluation performance on modern DBMSssignificantly in cases that have been traditionally challenging. In particular,we study the performance of structure-guided query evaluation in threearchitecturally distinct DBMSs by rewriting SQL queries into a sequence of SQLstatements that express an execution of Yannakakis' algorithm. Moreover, weidentify a class of queries that is particularly well suited for our approachand allows query answering in a variety of common scenarios withoutmaterializing any join. Through empirical evaluation we show thatstructure-guided query evaluation can make the evaluation of many difficultjoin queries feasible whereas their evaluation requires a prohibitive amount oftime and memory on current DBMSs.

Structure-Guided Query Evaluation: Towards Bridging the Gap from Theory to Practice