- 7.5 Optimizing the MySQL Server
- 7.5.1 How Compiling and Linking Affects the Speed of MySQL
- 7.5.2 System Factors and Startup Parameter Tuning
- 7.5.3 Tuning Server Parameters
- 7.5.4 Controlling Query Optimizer Performance
- 7.5.5 The MySQL Query Cache
- 7.5.6 Examining Thread Information
- 7.5.7 How MySQL Uses Threads for Client Connections
- 7.5.8 How MySQL Uses Memory
- 7.5.9 Enabling Large Page Support
- 7.5.10 How MySQL Uses Internal Temporary Tables
- 7.5.11 How MySQL Uses DNS
The task of the query optimizer is to find an optimal plan for executing an SQL query. Because the difference in performance between “good” and “bad” plans can be orders of magnitude (that is, seconds versus hours or even days), most query optimizers, including that of MySQL, perform a more or less exhaustive search for an optimal plan among all possible query evaluation plans. For join queries, the number of possible plans investigated by the MySQL optimizer grows exponentially with the number of tables referenced in a query. For small numbers of tables (typically less than 7–10) this is not a problem. However, when larger queries are submitted, the time spent in query optimization may easily become the major bottleneck in the server's performance.
MySQL 5.0.1 introduces a more flexible method for query optimization that allows the user to control how exhaustive the optimizer is in its search for an optimal query evaluation plan. The general idea is that the fewer plans that are investigated by the optimizer, the less time it spends in compiling a query. On the other hand, because the optimizer skips some plans, it may miss finding an optimal plan.
The behavior of the optimizer with respect to the number of plans it evaluates can be controlled via two system variables:
The
optimizer_prune_levelvariable tells the optimizer to skip certain plans based on estimates of the number of rows accessed for each table. Our experience shows that this kind of “educated guess” rarely misses optimal plans, and may dramatically reduce query compilation times. That is why this option is on (optimizer_prune_level=1) by default. However, if you believe that the optimizer missed a better query plan, this option can be switched off (optimizer_prune_level=0) with the risk that query compilation may take much longer. Note that, even with the use of this heuristic, the optimizer still explores a roughly exponential number of plans.The
optimizer_search_depthvariable tells how far into the “future” of each incomplete plan the optimizer should look to evaluate whether it should be expanded further. Smaller values ofoptimizer_search_depthmay result in orders of magnitude smaller query compilation times. For example, queries with 12, 13, or more tables may easily require hours and even days to compile ifoptimizer_search_depthis close to the number of tables in the query. At the same time, if compiled withoptimizer_search_depthequal to 3 or 4, the optimizer may compile in less than a minute for the same query. If you are unsure of what a reasonable value is foroptimizer_search_depth, this variable can be set to 0 to tell the optimizer to determine the value automatically.
User Comments
I had a view with probably 20 joins in. tables typically only had 100 rows. query would initially take 20-30seconds. i set the optimiser search depth down to 3 and got that time down to 90ms.
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