TAILIEUCHUNG - Database Systems: The Complete Book- P13

Database Systems: The Complete Book- P13: Database Systems and Database Design and Application courses offered at the junior, senior and graduate levels in Computer Science departments. Written by well-known computer scientists, this introduction to database systems offers a comprehensive approach, focusing on database design, database use, and implementation of database applications and database management systems | 1082 CHAPTER 20. INFORMATION INTEGRATION tells us that total sales of all Aardvark models in all colors over all time at all dealers is 198 000 cars for a total price of 3 521 727 000. Consider how to answer a query in which we specify conditions on certain attributes of the Sales relation and group by some other attributes while asking for the sum count or average price. In the relation CUBE Sales we look for those tuples t with the following properties 1. If the query specifies a value v for attribute a then tuple i has v in its component for a. 2. If the query groups by an attribute a then i has any non- value in its component for a. 3. If the query neither groups by attribute a nor specifies a value for a then t has in its component for a. Each tuple t has the sum and count for one of the desired groups. If we want the average price a division is performed on the sum and count components of each tuple t. Example The query SELECT color AVG price FROM Sales WHERE model Gobi GROUP BY color is answered by looking for all tuples of CUBE Sales with the form Gobi c. v n where c is any specific color. In this tuple v will be the sum of sales of Gobis in that color while n will be the number of sales of Gobis in that color. The average price although not an attribute of Sales or CUBE Sales directly is v n. The answer to the query is the set of c v n pairs obtained from all Gobi c v n tuples. Cube Implementation by Materialized Views We suggested in Fig. that adding aggregations to the cube doesn t cost much in terms of space and saves a lot in time when the common kinds of decision-support queries are asked. However our analysis is based on the assumption that queries choose either to aggregate completely in a dimension or not to aggregate at all. For some dimensions there are many degrees of granularity that could be chosen for a grouping on that dimension. Wo have already mentioned the case of time where numerous options such as aggregation by weeks

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