DocumentCode :
2730880
Title :
Partial Materialized Views
Author :
Gang Luo
fYear :
2007
fDate :
15-20 April 2007
Firstpage :
756
Lastpage :
765
Abstract :
Early access to partial query results is highly desirable during exploration of massive data sets. However, it is challenging to provide transactionally consistent, immediate partial results without significantly increasing queries´ execution time. To address this problem, this paper proposes a partial materialized view (PMV) method to cache some of the most frequently accessed results rather than all the possible results. Compared to traditional materialized views, the proposed PMVs do not require maintenance during insertion into base relations, and have much smaller storage and maintenance overhead. Upon the arrival of a query, the RDBMS first searches the PMV and returns to the user the cached partial results. Since a large portion of the PMV is cached in memory, this usually finishes within a millisecond. Then the RDBMS continues to execute the query to find the remaining results. The efficiency of our PMV method is evaluated through a simulation study, a theoretical analysis, and an initial implementation in PostgreSQL.
Keywords :
SQL; cache storage; query processing; relational databases; PostgreSQL; RDBMS; cached partial results; partial materialized views; partial query results; query execution time; Analytical models; Customer service; Databases; Delay; Marketing and sales; Material storage; Query processing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on
Conference_Location :
Istanbul
Print_ISBN :
1-4244-0802-4
Type :
conf
DOI :
10.1109/ICDE.2007.367921
Filename :
4221724
Link To Document :
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