OLAP Implementation (Cont.) Early OLAP systems precomputed all possible aggregates in order to provide online response Space and time requirements for doing so can be very high 2n combinations of group by It suffices to precompute some aggregates,and compute others on demand from one of the precomputed aggregates Can compute aggregate on(item-name,color)from an aggregate on (item-name,color,size) -For all but a few"non-decomposable"aggregates such as median -is cheaper than computing it from scratch Several optimizations available for computing multiple aggregates Can compute aggregate on (item-name,color)from an aggregate on (item-name,color,size) Can compute aggregates on (item-name,color,size), (item-name,color)and(item-name)using a single sorting of the base data Database System Concepts-5th Edition,Aug 26,2005 18.13 ©Silberschat乜，Korth and SudarshanDatabase System Concepts - 5 18.13 ©Silberschatz, Korth and Sudarshan th Edition, Aug 26, 2005 OLAP Implementation (Cont.) Early OLAP systems precomputed all possible aggregates in order to provide online response Space and time requirements for doing so can be very high  2 n combinations of group by It suffices to precompute some aggregates, and compute others on demand from one of the precomputed aggregates  Can compute aggregate on (item-name, color) from an aggregate on (item-name, color, size) – For all but a few “non-decomposable” aggregates such as median – is cheaper than computing it from scratch Several optimizations available for computing multiple aggregates Can compute aggregate on (item-name, color) from an aggregate on (item-name, color, size) Can compute aggregates on (item-name, color, size), (item-name, color) and (item-name) using a single sorting of the base data