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Once the optimizer chooses the join method, it determines the order in which the tables are joined. The goal of the optimizer is always to join tables in such a way that the driving table eliminates the largest number of rows. A query with four tables has a maximum of 4 factorial, or 24, possible ways in which the tables can be joined. Each such join order would lead to a number of different execution plans, based on the available indexes and the access methods. The search for an optimal join strategy could take a long time in a query with a large number of tables, so Oracle depends on an adaptive search strategy to limit the time it takes to find the best execution plan. An adaptive search strategy means that the time taken for optimization is always a small percentage of the total time that is taken for execution of the query itself.

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The CBO is systematic, but the optimizer is not guaranteed to follow the same plan in similar cases. However, the CBO isn t always perfect, and you need to watch out for the following: The CBO isn t fixed across Oracle versions. Execution plans can change over time as versions change. Later in this chapter, you ll see how to use stored outlines so the optimizer always uses a known plan to maintain plan stability. Application developers may know more than the CBO when it comes to choosing the best access path. Application developers know the needs of the users, of which the CBO is completely unaware. This could lead to a situation where the CBO may be optimizing throughput, when the users would rather have a quick set of results on their screen. By using hints such as FIRST_ROWS_n, you can overcome this drawback in the CBO. The CBO depends enormously on correct statistics gathering. If the statistics are absent or outdated, the optimizer can make poor decisions.

The CBO can follow optimal execution paths only if it has detailed knowledge of the database objects. Starting with Oracle Database 10g, the recommended way to provide these statistics is by letting the database automatically collect statistics for you. This is known as the Automatic Optimizer Statistics Collection feature, which I explained in 17. You can also manually provide statistics to the optimizer with the DBMS_STATS package. Note that whether you rely on automatic collection of statistics or collect them yourself manually, Oracle uses the DBMS_STATS package to collect statistics.

Although letting the database automatically collect optimizer statistics is the recommended approach, you can still manually collect optimizer statistics using the DBMS_STATS package.

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Tip For large tables, Oracle recommends just sampling the data, rather than looking at all of it. Oracle lets you specify row or block sampling, and it sometimes seems to recommend sampling sizes as low as 5 percent. The default sampling size for an estimate is low too. Oracle also recommends using the DBMS_STATS automatic sampling procedure. However, statistics gathered with sampled data aren t reliable. The difference between collecting optimizer statistics with the estimate at 30 percent and 50 percent is startling at times in terms of performance. Always choose the option of collecting full statistics for all your objects, even if the frequency is not as high as it could be if you just sampled the data.

As I explained in 17, you must manually collect optimizer statistics under the following conditions: When you use external tables When you need to collect system statistics To collect statistics on fixed objects, such as the dynamic performance tables (For dynamic tables, you should use the GATHER_FIXED_OBJECTS_STATS procedure to collect optimizer statistics.) Immediately after you run a bulk load job, because this makes your automatically collected statistics unrepresentative The following sections show you how to make use of the DBMS_STATS package to gather statistics.

Figure 6-2. A State Machine diagram showing trigger guard conditions You can also label transitions to show their effects, called actions. Actions represent behaviors of the system and are shown on transitions using the notation: <trigger> / <action> Figure 6-3 shows an example using transitions with actions. In addition to actions produced by state transitions, there are actions that can be associated with each state. These actions can be performed when a state is entered or exited. You can also define actions to execute while the system is in a given state. State Machine diagrams also support composite states, in which a state can be decomposed into a number of substates.