TAILIEUCHUNG - Database Systems: The Complete Book- P12

Database Systems: The Complete Book- P12: 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 | 1080 CHAPTER 20. INFORMATION INTEGRATION it appears. Figure suggests the process of adding a border to the cube in each dimension to represent the value and the aggregated values that it implies. In this figure we see three dimensions with the lightest shading representing aggregates in one dimension darker shading for aggregates over two dimensions and the darkest cube in the corner for aggregation over all three dimensions. Notice that if the number of values along each dimension is reasonably large but not so large that most points in the cube are unoccupied then the border represents only a small addition to the volume of the cube . the number of tuples in the fact table . In that case the size of the stored data CUBE F is not much greater than the size of F itself. Figure The cube operator augments a data cube with a border of aggregations in all combinations of dimensions A tuple of the table CUBE F that has in one or more dimensions will have for each dependent attribute the sum or another aggregate function of the values of that attribute in all the tuples that we can obtain by replacing the s by real values. In effect we build into the data the result of aggregating along any set of dimensions. Notice however that the CUBE operator does not support aggregation at intermediate levels of granularity based on values in the dimension tables. For instance we may either leave data broken down by day or whatever the finest granularity for time is or we may aggregate time completely but we cannot with the CUBE operator alone aggregate by weeks months or years. Example Let us reconsider- the Aardvark database from Example in the light of what the CUBE opera or can give us. Recall the fact table from that example is Sales serialNo date dealer price However the dimension represented by serialNo is not well suited for the cube since the serial number is a key for Sales. Thus summing the price over all dates or over all dealers but keeping .

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