Materialized Queries with Incremental Updates

  • Sonali Chakraborty
  • Jyotika Doshi
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 106)


Enterprise decision-making entails results extracted through Online Analytical Processing (OLAP) queries. The performance of result retrieval from data warehouse is a critical factor. Frequent OLAP queries have to access warehouse data repeatedly for generating the same results. To avoid executing the same OLAP query and access data warehouse, our approach suggests that queries are materialized and stored in a separate database named MQDB along with its results and other metadata information. When query is fired next time, results are fetched from MQDB, in case of no incremental updates. If incremental updates are required, then only incremental records from data warehouse are analyzed for retrieving updated results. Final results will be based on the results in MQDB and incremental result retrieved from data warehouse. Traversing through incremental records in data warehouse results in faster query result retrieval. This paper evaluates query execution time of materialized queries involving nonincremental as well as incremental updates using data warehouse.


Data warehouse Materialized query Incremental updates 


  1. 1.
    Serranoa, M., Trujillo, J., Calero, C., Piattini, M.: Metrics for data warehouse conceptual models understandability. Inf. Softw. Technol. 49(8), 851–870 (2007)CrossRefGoogle Scholar
  2. 2.
    Bara, A., Lungu, I., Velicanu, M., Diaconita, V., Botha, I.: Improving query performance in virtual data warehouses. WSEAS Trans. Inf. Sci. Appl. 5(5) (2008). ISSN: 1790-0832Google Scholar
  3. 3.
    Sultan, F., Aziz, A.: Ideal strategy to improve data warehouse performance. Int. J. Comput. Sci. Eng. 02(02), 409–415 (2010)Google Scholar
  4. 4.
    Vanichayobon, S.: Indexing techniques for data warehouses’ queries. Accessed 15 Sept 2016
  5. 5.
    Srinivasa, S.: Query processing issues in data warehouses.
  6. 6.
    O’Neil, P., Quass, D.: Improved query performance with variant indexes. In: Proceedings of the 1997 ACM SIGMOD International Conference on Management of Data, pp. 38–49Google Scholar
  7. 7.
    Chakraborty, S., Doshi, J.: Performance evaluation of materialized query. Int. J. Emerg. Technol. Adv. Eng. 8(1), 243–249 (2018)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Gujarat UniversityAhmedabadIndia
  2. 2.GLS UniversityAhmedabadIndia

Personalised recommendations