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162 Chapter 4 Data Warehousing and Online Analytical Processing 3:17 Page 162 #38

indexing maintains relationships between attribute values of a dimension (e.g., within
a dimension table) and the corresponding rows in the fact table. Join indices may span
multiple dimensions to form composite join indices. We can use join indices to identify
subcubes that are of interest.

Example 4.8 Join indexing. In Example 3.4, we defined a star schema for AllElectronics of the form
“sales star [time, item, branch, location]: dollars sold = sum (sales in dollars).” An exam-
ple of a join index relationship between the sales fact table and the location and item
dimension tables is shown in Figure 4.16. For example, the “Main Street” value in the
location dimension table joins with tuples T57, T238, and T884 of the sales fact table.
Similarly, the “Sony-TV” value in the item dimension table joins with tuples T57 and
T459 of the sales fact table. The corresponding join index tables are shown in Figure 4.17.

sales
location item
T57
Main Street Sony-TV
T238

T459

T884

Figure 4.16 Linkages between a sales fact table and location and item dimension tables.

Join index table for Join index table for
location/sales item/sales
location sales_key item sales_key
Main Street T57 Sony-TV T57
Main Street T238 Sony-TV T459
Main Street T884

Join index table linking
location and item to sales

location item sales_key
Main Street Sony-TV T57

Figure 4.17 Join index tables based on the linkages between the sales fact table and the location and item
dimension tables shown in Figure 4.16.