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Creates a set using the default IEqualityComparer<T> for the type T Creates a set using the default IEqualityComparer<T>, populated with the contents of the IEnumerable<T> Creates a set using the specified IEqualityComparer<T> for item comparison Creates a set using the specified IEqualityComparer<T> for item comparisons and populated with the contents of the IEnumerable<T>

Even if your choice of hardware is appropriate, your data design is reasonable, your indexing is carefully thought out, your SQL is well structured, and you haven t introduced inefficiencies in the outer levels of code, you could still have performance problems because the optimizer can t cope with your SQL You have seen that you may be able to pinpoint a bug in the optimizer by stripping complicated production code back to the minimum You have also seen that it s possible to find optimization strategies that are obvious to the human eye but not yet coded into the optimizer Apart from these issues, you also know that the optimizer can pick the wrong path because it is simply not possible for it to determine how much data it is going to have to process.

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Once the child object has been created and added to the parent, the UI code can access the child via the parent s interface. Typically, the parent will provide an indexer that allows the UI to access child objects directly. Though the factory method is called by the parent object rather than the UI code, this is the same process that s used to create a root object. The same is true if the object needs to load itself with default values from the database. 1. The factory method (internal scope) is called. 2. The factory method calls DataPortal.Create() to get the child business object. 3. The data portal uses its channel adapter and message router functionality as described in 4; the result is that the data portal creates a new instance of the business object. 4. The child object can do basic initialization in the constructor method. 5. The DataPortal_Create() method is called, and this is where the child object implements data access code to load its default values.

Although some of the problems of estimating data volumes are inherently impossible for the optimizer to handle, in some cases we can supply statistical information that helps the optimizer produce better estimates of volume and (equally important) the pattern of data scatter The critical strategy then is to do the minimum amount of work while ensuring that the optimizer gets good enough figures Whatever the problems the optimizer has with statistics, though, we need to recognize that a single, simple, strategy for gathering statistics is unlikely to produce an ideal set of statistics for anything other than the simpler applications We need to design a mechanism that is easy to manage but allows special handling for critical objects at a detailed level.

The obvious difficulty is that some applications have literally tens of thousands of tables (or partitions thereof) and indexes and it would be undesirable to have to worry about every object (and subobject) separately Given the potential complexity (and sheer size) of a framework for controlling statistics, the best bet seems to be to use a basic generic approach to generate most statistics and then follow this up with a table-driven approach for exceptions Although there are difficulties in implementing such a system, it can be done incrementally Usually only a few special cases need to be corrected after an easily implemented driving mechanism has run (such as a call to Oracle s automatic statscollection routine with histogram collection disabled).

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