Enhancing Database Query Performance: Analysis of Indexing Techniques

2024;
: pp. 65 - 73
1
Lviv Polytechnic National University, Information Systems and Networks Department
2
Lviv Polytechnic National University, Information Systems and Networks Department

The need to enhance query performance in databases within the contemporary information environment is crucial for ensuring efficient operations across various domains. This paper is dedicated to an analysis of database indexing techniques aimed at understanding their impact on query performance and efficiency. It meticulously examines various types of indexes, including B-trees, hash tables, and textual indexes, analyzing their advantages and limitations. The investigation into the influence of these techniques on query execution time reveals that performance depends on various factors such as query complexity and data volume.

Special attention is given to selecting the optimal index type based on specific database needs and characteristics. The research underscores the importance of considering data volume and database structure in choosing effective indexing methods. Additionally, the advantages and disadvantages of different indexing techniques are scrutinized, taking into account their impact on query execution speed and efficiency.

Of the study indicate that the correct selection and utilization of appropriate indexing strategies can significantly enhance the performance of database management systems, providing swift and efficient access to information for users. Ultimately, this work makes a significant contribution to understanding and practically applying indexing techniques to improve query performance in databases.

  1. Bâra, A., Lungu, I., Velicanu, M., & Diaconiţa, V. (2008). Improving query performance in virtual data warehouses. WSEAS Transactions on Information Science and Applications, 5(3), 295–302. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=aeccdfbab...
  2. Ahmad,              K.             (2020).              Query              Performance               in             Database              Operation. https://www.ftsm.ukm.my/v5/file/research/technicalreport/PS-FTSM-2020-045.pdf
  3. Böhm, C., Berchtold, S., & Keim, D. A. (2001). Searching in high-dimensional spaces: Index structures for improving the performance of multimedia databases. ACM Computing Surveys (CSUR), 33(3), 322–373. https://kops.uni-konstanz.de/server/api/core/bitstreams/5c71837c-9d42-4e...
  4. Boicea, A., Radulescu, F., Truica, C. O., & Urse, L. (2016). Improving Query Performance in Distributed Database. Journal of Control Engineering and Applied Informatics, 18(2), 10–17. http://www.ceai.srait.ro/index.php?journal=ceai&page=article&op=download&path%5B%5D=3159&path%5B%5D=1393
  5. Rupley, M., Jr. (2008). Introduction to query processing and optimization. Indiana University South Bend Computer Science and Informatics. https://clas.iusb.edu/computer-science-informatics/research/reports/TR-2...
  6. Bhajipale, R., Bisen, P., Meshram, A., & Thakur, S. S. (2016). SQL tuner. International Journal of Computer Trends and Technology, 33(1), 29–32. https://doi.org/10.14445/22312803/IJCTT-V33P106
  7. Karthik, P., Reddy, G. T., & Vanan, E. K. (2012). Tuning the SQL query in order to reduce time consumption. International Journal of Computer Science Issues, 9(4/3), 418–423. https://www.ijcsi.org/papers/IJCSI- 9-4-3-418-423.pdf
  8. Habimana, J. (2015). Query optimization techniques – tips for writing efficient and faster SQL queries. International Journal of Scientific & Technology Research, 4(10), 22–26. https://www.ijstr.org/final- print/oct2015/Query-Optimization-Techniques-Tips-For-Writing-Efficient-And-Faster-Sql-Queries.pdf
  9. Sahal, R., Nihad, M., Khafagy, M. H., & Omara, F. A. (2018). iHOME: Index based JOIN query optimization for limited big data storage. Journal of Grid Computing, 16(2), 345–380. https://doi.org/10.1007/s10723-018-9431-9
  10. Sharma, M. (2012). Query optimization using SQL transformations. International Journal of IT, Engineering and Applied Sciences Research, 1(1), 100–104. http://www.irjcjournals.org/ijieasr/Oct2012/20.pdf
  11. Srinivas, S. S., Naik, B. V., & Kumar, J. S. A. (2017). Query minimization methods. International Journal of Scientific & Engineering Research, 8(5), 30–33. https://www.ijser.org/researchpaper/Query-Minimization- Methods.pdf
  12. Patel, D., & Patel, P. (2015). An approach for query optimization by using schema object base view.International Journal of Computer Applications, 119(16), 21–24. https://doi.org/10.5120/21152-4146
  13. Patil, S., Damare, P., Sonawane, J., & Maitre, N. (2015). Study of performance tuning techniques.Journal            of           Emerging             Technologies              and           Innovative             Research,             2(3),          499–502.https://www.jetir.org/papers/JETIR1503018.pdf
  14. Corlatan, C. G., Lazar, M. M., Luca, V., & Petricica, O. T. (2014). Query optimization techniques in Microsoft SQL server. Database Systems Journal, 5(2), 33–48. https://www.dbjournal.ro/archive/16/16_4.pdf
  15. Lokhande, A. D., & Shete, R. M. (2012). The use of hints in SQL-Nested query optimization. Journal of Data Mining and Knowledge Discovery, 3(1), 54–57. https://bioinfopublication.org/files/articles/3_1_5_JDMKD.pdf
  16. Ozar,        B.       (2022,        July       21).       How       to       Download        the       Stack       Overflow         Database. https://www.brentozar.com/archive/2015/10/how-to-download-the-stack-overflow-database-via-bittorrent/