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undergraduate thesis
Profiliranje i optimizacija baze podataka u sustavu SQL Server
2023. urn:nbn:hr:190:140842
Pekić, Lorena
University of Rijeka
Faculty of Engineering
Department of Computer Engineering

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Pekić, L. (2023). Profiliranje i optimizacija baze podataka u sustavu SQL Server (Undergraduate thesis). Rijeka: University of Rijeka, Faculty of Engineering. Retrieved from https://urn.nsk.hr/urn:nbn:hr:190:140842

Pekić, Lorena. "Profiliranje i optimizacija baze podataka u sustavu SQL Server." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:140842

Pekić, Lorena. "Profiliranje i optimizacija baze podataka u sustavu SQL Server." Undergraduate thesis, University of Rijeka, Faculty of Engineering, 2023. https://urn.nsk.hr/urn:nbn:hr:190:140842

Pekić, L. (2023). 'Profiliranje i optimizacija baze podataka u sustavu SQL Server', Undergraduate thesis, University of Rijeka, Faculty of Engineering, accessed 09 May 2024, https://urn.nsk.hr/urn:nbn:hr:190:140842

Pekić L. Profiliranje i optimizacija baze podataka u sustavu SQL Server [Undergraduate thesis]. Rijeka: University of Rijeka, Faculty of Engineering; 2023 [cited 2024 May 09] Available at: https://urn.nsk.hr/urn:nbn:hr:190:140842

L. Pekić, "Profiliranje i optimizacija baze podataka u sustavu SQL Server", Undergraduate thesis, University of Rijeka, Faculty of Engineering, Rijeka, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:190:140842

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Metadata
TitleProfiliranje i optimizacija baze podataka u sustavu SQL Server
Title (english)Database Profiling and Optimization in SQL Server
AuthorLorena Pekić
MentorSandi Ljubić (mentor)
Committee memberMiroslav Joler (predsjednik povjerenstva)
Committee memberSandi Ljubić (član povjerenstva)
GranterUniversity of Rijeka
Faculty of Engineering
(Department of Computer Engineering)
Rijeka
Defense date and country2023-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu analiziran je proces i učinak profiliranja i optimizacije baze podataka u sustavu SQL Server. Razvijen je ogledni sustav s potpornom bazom podataka u koju je uveden veliki broj inicijalnih zapisa i veći broj okidača. Na taj je način simulirano odgovarajuće opterećenje na sustav za upravljanje bazama podataka koje rezultira adekvatnim povećanjem vremena odziva na upite. Primjenom alata za automatsko profiliranje i optimizaciju unutar sustava SQL Server, postignuta su odgovarajuća poboljšanja performansi. Konkretno, korištenjem preporuka koje se zasnivaju na planu izvršavanja upita i procijenjenom trošku, provedene su akcije poput stvaranja negrupiranih indeksa i statistika nad odgovarajućim atributima u tablicama baze podataka. Detaljnom analizom eksperimentalnih rezultata dobiven je bolji uvid u učinak automatskog profiliranja i optimizacije. Pokazano je da prijedlozi za optimizaciju nisu uspješni u svakom scenariju te da je važno oprezno primjenjivati predložene indekse i statistike. Također, utvrđeno je da alatu za optimizaciju treba predati čim veće radno opterećenje kako bi generirane preporuke imale globalno pozitivan utjecaj na rad sustava.
Abstract (english)
This thesis analyzes the process and effect of database profiling and optimization in SQL Server. An example system was developed with a supporting database in which a large number of initial records and a large number of triggers were introduced. In this way, the corresponding load on the database management system was simulated, resulting in a respective increase in the response time to queries. By using tools for automatic profiling and optimization within SQL Server, corresponding performance improvements were achieved. In particular, recommendations based on the query execution plan and estimated costs were used to implement measures such as the creation of non- clustered indexes and statistics on the corresponding attributes in the database tables. A detailed analysis of the experimental results provided a better insight into the effect of automatic profiling and optimization. It is shown that the optimization suggestions are not successful in every scenario and that it is important to apply the suggested indexes and statistics judiciously. It was also found that the tuning advisor should be given a larger workload so that the generated recommendations have a global positive impact on the operation of the system.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:190:140842
Study programmeTitle: Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
Access conditionsOpen access
Terms of useLicence Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) icon
Created on2023-07-12 17:24:45