Title : 
A foundation for conventional and temporal query optimization addressing duplicates and ordering
         
        
            Author : 
Slivinskas, Giedrius ; Jensen, Christian S. ; Snodgrass, Richard T.
         
        
            Author_Institution : 
Dept. of Comput. Sci., Aalborg Univ., Denmark
         
        
        
        
        
        
        
            Abstract : 
Most real-world databases contain substantial amounts of time-referenced, or temporal, data. Recent advances in temporal query languages show that such database applications may benefit substantially from built-in temporal support in the DBMS. To achieve this, temporal query representation, optimization, and processing mechanisms must be provided. This paper presents a foundation for query optimization that integrates conventional and temporal query optimization and is suitable for both conventional DBMS architectures and ones where the temporal support is obtained via a layer on top of a conventional DBMS. This foundation captures duplicates and ordering for all queries, as well as coalescing for temporal queries, thus generalizing all existing approaches known to the authors. It includes a temporally extended relational algebra to which SQL and temporal SQL queries may be mapped, six types of algebraic equivalences, concrete query transformation rules that obey different equivalences, a procedure for determining which types of transformation rules are applicable for optimizing a query, and a query plan enumeration algorithm
         
        
            Keywords : 
SQL; optimisation; query languages; query processing; relational algebra; temporal databases; SQL; algebraic equivalence; duplicate elimination; ordering; query transformation rules; temporal database; temporal query languages; temporal query optimization; temporally extended relational algebra; Algebra; Algorithm design and analysis; Concrete; Data warehouses; Database languages; Design optimization; Partitioning algorithms; Productivity; Programming profession; Query processing;
         
        
        
            Journal_Title : 
Knowledge and Data Engineering, IEEE Transactions on