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Aggregations can be classified into two types: identified and ad hoc. Identified aggregations are those that the data warehouse already has stated requirements for. Ad hoc aggregations are those that are created to solve particular performance problems. These will be created and deleted as necessary, and are impossible to test.
Each identified aggregation should be tested thoroughly. There are often a number of ways in which a given aggregation can be created or maintained. Each method should be checked and the best compromise of performance and resource usage chosen. These tests are important, because they will often show up the fact that a particular aggregation is impractical.
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Index build times are an important operational measurement to gather. The tests made to check the data warehouse management systems should check, in particular, the effects of using differing degrees of parallelism. This can prove to be very important in keeping the overnight processing within the limits required. In a data warehouse, indexes are often required to be re-created because, for data loads and other bulk data movements, it is generally quicker to drop indexes, perform the data movement and create a new index, than to perform the data move with indexes in place.
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Query performance is one of the most difficult things to measure in a data warehouse, not least because of the ad hoc nature of the queries that will be run. There will probably be a set of fixed queries that have to be run regularly, and they should be tested. To measure the ad hoc queries, the best that can be done is to use the documented user requirements along with knowledge of the business to generate some queries that are meaningful to the business, and test those.
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The aim of the Data Warehouse system test is to test all of the systems and procedures involved such as data warehouse application code, day-to-day operational procedures, overnight processing backup recovery strategy, scheduling software, query performance management and monitoring tools. There is one other point that needs consideration, and that is scalability. Many of the operations in a data warehouse do not scale linearly, and so the results of tests made on smaller systems may not be valid on the live system.
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During the system testing the disk configuration should be tested thoroughly to identify any potential I/O bottlenecks. This is where decisions on stripe widths and versions of RAID technology will be tested, and any problems with the chosen configuration will be highlighted. For a detailed discussion of disk configuration options see Chapter 12. From a testing point of view it will be necessary to test each configuration both for bulk operations, such as restoring a data file, and for daily operations, such as data load and querying.
