Query Optimization in Teradata Warehouse

• Autorzy: Gosk A.
• Języki publikacji: EN

Abstrakty

EN

The time necessary for data processing is becoming shorter and shorter nowadays. This thesis presents a definition of the active data warehousing (ADW) paradigm. One of the data warehouses which is consistent with this paradigm is teradata warehouse. Therefore, the basic elements of the teradata architecture are described, such as processors parsing engine (PE) and access module processor (AMP). Emphasis was put on the analysis of query optimization methods. There is presented the impact of a primary index on the time of query execution. Furthermore, this paper shows different methods of optimization of data selection, data joins and data aggregation. All these methods can help to minimize the time for data processing. This paper presents experiments which show the usage of different methods of query optimization. At the end some conclusions about different index usage are included.

Słowa kluczowe

EN

active data warehouse; query optimization; tera-data

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2010
• Tom: nr 3
• Strony: 57--64
• Opis fizyczny: Bibliogr. 4 poz., rys., tab.

Twórcy

autor

Gosk A.

Bibliografia

• [1] S. Brobst and J. Rarey, “The five stages of an Active Data Warehouse evolution”, Teradata Magazine Online, 2001 [Online]. Available: http://www.ncr.com/online periodicals/brobst.pdf
• [2] M. Gonzales, “Getting Active”, DB2 Mag., iss. 1, Q1, 2005 [Online]. Available: http://www.dbmag.intelligententerprise.com/story/showArticle.jhtml?articleID=59300861
• [3] E. Kanana and M. Farhi, “Enhancing data preparation processes using triggers for active datawarehousing”, in Proc. Int. Conf. Data Mining, Las Vegas, USA, 2006, pp. 153–160.
• [4] Teradata Documentation, Database Design, pp. 335–561, Introduction to Teradata. NCR Corporation, 2005.