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Interior pointers are another way of navigating an array that allows you to use pointer arithmetic. The interior pointer is a pointer to some part of a managed object, in this case an array. Interior pointers get updated, just as handles do, when the objects they point to get moved around by the garbage collection process. 12 will discuss them in more detail. Listing 5-26 is a preliminary example of using an interior pointer to navigate a managed array. Listing 5-26. Using an Interior Pointer to Traverse an Array // arrays_interior_ptr.cpp using namespace System; ref class Buf { // ... }; int main() { array<Buf^>^ array_of_buf = gcnew array<Buf^>(10); // Create a Buf object for each array position. for each (Buf^ bref in array_of_buf) { bref = gcnew Buf(); } // Create an interior pointer to elements of the array. interior_ptr<Buf^> ptr_buf; // Loop over the array with the interior pointer. // using pointer arithmetic on the interior pointer for (ptr_buf = &array_of_buf[0]; ptr_buf <= &array_of_buf[9]; ptr_buf++) { // Dereference the interior pointer with *. Buf^ buf = *ptr_buf; // use the Buf class } } What happens when you run off the end of the array If you attempt to access an index that doesn t exist in the array, an IndexOutOfRangeException will be thrown, as shown in Listing 5-27.

Summary

3. 4. 5.

Before doing any arithmetic, the optimizer may rewrite your query in a form that is easier to model and potentially has more optimization options available Sometimes it is better to block the rewrite, and there are hints available to allow you to do this Increasingly, though, the optimizer will run cost calculations for the original query and the restructured query, so in theory such blocking activity should become unnecessary (I understand that in 10g release 2, all transformations are driven by cost this is generally a good thing, but you may find that some complex queries may now take longer to optimize) There are cases where the execution plan cannot adequately describe exactly what the execution engine is going to do.

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Listing 5-27. Going Past the End of an Array // array_exception.cpp using namespace System; int main() { int i; array<int>^ array1 = { 0, 1, 2}; try { i = array1[3]; } catch(IndexOutOfRangeException^ e) { Console::WriteLine( "{0}, {1}" , e->ToString(), e->Message); } } The output of Listing 5-27 is as follows: System.IndexOutOfRangeException: Index was outside the bounds of the array. at main(), Index was outside the bounds of the array.

Moreover, the work that has to be done by the run-time engine may vary dramatically because of minor differences in the target data set, so a plan that seems to work well on even a carefully generated test set of data may behave very badly on production data The optimizer s ability to transform queries can be seriously affected by the presence (or usually absence) of not null constraints Make sure that if a column is mandatory, it is declared as such to the database Similarly, the presence, or absence, of uniqueness constraints can make a difference to the legal options and table ordering when the optimizer is trying to transform subqueries.

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In general, if you are going to write SQL with subqueries, you might as well start by writing code that reads like the natural language version of a problem, as this may be the easiest for other people to understand Generally, the optimizer can transform such queries into more efficient representations Sometimes, though, you will find that an obvious transformation will not take place, and you will have to do a manual transformation of your code If you do, make sure that it is logically the same as the original Star transformations are a popular join strategy for data warehouses But it is possible that when you enable the feature, some of your execution plans may show dramatic changes in cardinality This may be due to a collision between your design strategy for dimension tables and the arithmetic the optimizer does for the driving bitmap and.