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ine chapters into the book, and I still haven t got as far as a two-table join And I m going to avoid joins for just one more chapter while I discuss features such as subqueries, view merging, unnesting, and the star transformation The reason for examining some of the more subtle options before looking at joins is that the optimizer tries to restructure the SQL you write, generally turning it into a simpler form consisting of just a straight join between tables, before optimizing it This means the first step in understanding how the optimizer evaluates an execution plan requires you to work out the structure of the SQL that is actually being optimized Since this chapter is about transformation mechanisms, there won t be a lot about cost in it.

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A key point to remember about some of these transformations and the strange consequences that you sometimes see is that the code driving the decision to transform your SQL is still partly rule-based (or, as they say in the manuals, heuristically driven) In one version of the database, you may see a particular execution plan appear because that s what the rules say; and then you upgrade and the optimizer works out the cost of two execution plans, one with the transformation and one without, and takes the cheaper one which may not be the one you saw before the upgrade, and may not be faster It seems that a common life cycle of the internal code for a typical query transformation is as follows: Beta-like state: The internal code exists, and you can make it happen with a (possibly) hidden parameter or undocumented hint.

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Here is the output of Listing 5-21: first second If you use a size greater than the number of elements provided, the uninitialized elements are included in the length, as in Listing 5-22. Listing 5-22. Initializing Only Part of an Array // arrays_uninitialized_elements.cpp using namespace System; int main() { array<String^>^ stringArray = gcnew array<String^>(5) { "one", "two" }; for (int i = 0; i < stringArray->Length; i++) { Console::WriteLine( stringArray[i] ); } Console::WriteLine("End."); } The uninitialized elements are null String handles, which are rendered as extra blank lines: one two

First official publication: The internal code is enabled by default, but not costed, so the transformation always happens Final state: The optimizer works out the cost of the original and the transformed SQL and takes the cheaper option The hint is deprecated (as, for example, hash_aj has been in 10g) In cases like this, you may have to fall back on the 10053 trace to figure out which state the feature and its supporting code is currently in..

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We ll start with an example to demonstrate the way in which sections of optimizer code can change. As ever, we stick with an 8KB block size in locally managed tablespaces, with 1MB uniform extent size, avoid ASSM, and disable system statistics to make the test case reproducible (see script filter_cost_01.sql in the online code suite). create table emp( dept_no not null, sal, emp_no not null, padding, constraint e_pk primary key(emp_no) ) as with generator as ( select --+ materialize rownum id from all_objects where rownum <= 1000 ) select mod(rownum,6), rownum, rownum, rpad('x',60) from generator v1, generator v2 where rownum <= 20000 ; In this script, I have created a table of 20,000 employees, scattered over six departments. Each employee has a different identifier, and a different salary. The code sample demonstrates the 9i feature of subquery factoring (with subquery), which I often use to generate a lot of rows from a row source that might otherwise not be large enough. (The 8i version of the script creates a scratch table.) We now run a query to list all the employees who earn more than the average salary for their department, and check the execution plans that we get from autotrace in different versions of Oracle. However, to highlight an important point, the SQL uses the no_unnest hint to force the optimizer to use a particular execution plan, because in this case the change in the internal code produces a dramatic change in the predicted cost and cardinality of the execution plan.