External hashing

Hlavním cílem předložené práce je usnadnit výuku předmětu Organizace a zpracování dat a to metod externího hašování. Jedná se konkrétně o Cormackovo perfektní hašování, perfektní hašování Larsona a Kajli, Faginovo rozšiřitelné hašování, Litwinovo lineární hašování a Skupinové štěpení stránek. Výstupem této práce je 5 programů v programovacím jazyce java, které simulují chování výše uvedených metod externího hašování. Programy umožňují záznamy vkládat a vyhledávat. Je také možné zadat hašovací funkce, kterou metody používají.In this work we describe ve methods of external hashing: Cormack Perfect Hashing, Perfect Hashing from Larson and Kajla, Fagin's Extendible hashing, Litwin's Linear Hashing and Breaking of Pages by Groups. Our main goal is to enhance the lecturer experience of the subject "Data organization and processing". We created ve programs in the Java programming language, one for each of these hashing methods. All of these programs enable the user to insert and nd arbitrary keys and let him set the hash function, used by the respective method.Katedra softwarového inženýrstvíDepartment of Software EngineeringFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult

Dedicated Object Management System Benchmarks for Software Engineering Applications

Non-standard database systems become available now, even as commercial products. They overcome a lot of deficiencies of relational systems w.r.t. their use in engineering applications like computer-aided design or software engineering. Their rather sophisticated functionality especially concerning the manipulation of complex objects makes them highly attractive for engineering applications. If being used as the central database of a rather complex application they could however still become a bottleneck w.r.t. performance. This paper presents a new way how to define a special purpose benchmark which enables to select the fastest database system for a particular software engineering application. It is argued that existing benchmarks are not appropriate to support such a selection, because they neglect important application specific characteristics which significantly influence the database performance