The Oracle Database Optimizer
Introduction to the Optimizer
The Oracle Database Optimizer is responsible for analyzing SQL queries and generating an optimal execution plan. An execution plan is a set of steps that the database follows to execute a query. The optimizer evaluates different methods to retrieve data, considering factors such as indexes, join methods, and access paths.
Types of Optimizers
Oracle Database includes two primary types of optimizers:
Cost-Based Optimizer (CBO)
The Cost-Based Optimizer evaluates multiple execution plans based on their estimated cost. The optimizer calculates the cost of each plan using various factors such as CPU, I/O, and memory usage. The plan with the lowest cost is chosen.
Key Components of CBO:
-
- Statistics: The optimizer relies on table and index statistics to estimate costs. Accurate statistics are crucial for effective optimization.
- Cost Calculation: The CBO uses a cost model to evaluate the performance and resource consumption of different plans.
Example:
EXPLAIN PLAN FOR SELECT * FROM employees WHERE department_id = 10;
Rule-Based Optimizer (RBO)
The Rule-Based Optimizer uses a set of fixed rules to determine the execution plan. It does not consider the cost of execution but follows predefined rules to decide the query execution strategy. Note that the RBO is deprecated and was removed in Oracle 10g.
Example: To use the RBO, you would have to explicitly set the optimizer mode in older versions of Oracle, like this:
ALTER SESSION SET OPTIMIZER_MODE = RULE;
Optimizer Modes
Oracle provides several optimizer modes that control the behavior of the optimizer:
ALL_ROWS
This mode aims to return all rows as quickly as possible, optimizing for throughput rather than response time. It’s suitable for queries that process large amounts of data.
Example:
ALTER SESSION SET OPTIMIZER_MODE = ALL_ROWS;
FIRST_ROWS_n
This mode optimizes for the fastest retrieval of the first n rows of a query. It is useful for queries where quick response time is crucial.
Example:
ALTER SESSION SET OPTIMIZER_MODE = FIRST_ROWS_10;
CHOOSE
In this mode, the optimizer decides whether to use the CBO or RBO based on the availability of statistics.
Example:
ALTER SESSION SET OPTIMIZER_MODE = CHOOSE;
ALL_ROWS (Default)
This mode is often the default mode and optimizes queries for overall efficiency, considering the cost of the entire query.
The Execution Plan
The execution plan is a detailed roadmap of how the optimizer will execute a query. It includes steps such as table scans, index usage, joins, and sort operations.
Viewing Execution Plans
You can view the execution plan for a query using the EXPLAIN PLAN statement or the DBMS_XPLAN package.
Example with EXPLAIN PLAN:
EXPLAIN PLAN FOR SELECT * FROM employees WHERE department_id = 10; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY);
Execution Plan Details
- Access Path: How the data is retrieved (e.g., full table scan, index scan).
- Join Methods: How tables are joined (e.g., nested loops, hash join).
- Sort Operations: How the results are sorted.
Statistics and Histograms
Accurate statistics are essential for the CBO to make informed decisions. Statistics include data about table sizes, index usage, and column value distributions.
Gathering Statistics
Use the DBMS_STATS package to gather statistics for tables and indexes.
Example:
EXEC DBMS_STATS.GATHER_TABLE_STATS('HR', 'EMPLOYEES');
Histograms
Histograms provide detailed information about the distribution of data within a column. They help the optimizer make better decisions when data distributions are skewed.
Example of Creating a Histogram:
EXEC DBMS_STATS.GATHER_COLUMN_STATS('HR', 'EMPLOYEES', 'SALARY', METHOD_OPT => 'FOR ALL COLUMNS SIZE 254');
Hints
Hints are directives included in SQL statements to influence the optimizer’s behavior. They override the optimizer’s decisions and force the use of specific execution plans.
Example:
SELECT /*+ INDEX(employees idx_last_name) */ * FROM employees WHERE last_name = 'Smith';
Common Hints:
- INDEX: Forces the use of a specified index.
- FULL: Forces a full table scan.
- LEADING: Specifies the order in which tables should be joined.
SQL Profiles and Baselines
SQL Profiles
SQL profiles provide additional information to the optimizer about how to execute queries more efficiently. They are automatically created by the Oracle Database when the SQL Tuning Advisor is used.
Example of Creating a SQL Profile:
EXEC DBMS_SQLTUNE.CREATE_SQL_PROFILE( PROFILE_NAME => 'profile_name', SQL_TEXT => 'SELECT * FROM employees WHERE department_id = 10' );
SQL Baselines
SQL baselines are sets of execution plans that the optimizer can use to ensure that SQL queries are executed in a consistent and predictable manner.
Example of Creating a SQL Baseline:
EXEC DBMS_SPM.LOAD_PLANS_FROM_CURSOR_CACHE();
Adaptive Query Optimization
Oracle’s adaptive query optimization techniques dynamically adjust execution plans based on runtime conditions.
Adaptive Plans
Adaptive plans allow the optimizer to adjust the execution plan during runtime based on actual data distribution and query execution.
Dynamic Sampling
Dynamic sampling gathers additional statistics at runtime to improve the accuracy of execution plans.
Example:
ALTER SESSION SET OPTIMIZER_DYNAMIC_SAMPLING = 2;
Monitoring and Tuning
Regularly monitor and tune the optimizer’s performance to ensure that your queries are executed efficiently.
Using AWR and ASH
- AWR (Automatic Workload Repository): Provides historical data on query performance and system metrics.
- ASH (Active Session History): Offers real-time data on active sessions and their performance.
SQL Tuning Advisor
The SQL Tuning Advisor analyzes SQL statements and provides recommendations for improving performance.
Example:
EXEC DBMS_SQLTUNE.CREATE_TUNING_TASK( SQL_ID => 'your_sql_id', TASK_NAME => 'task_name' );
Conclusion
The Oracle Database Optimizer is a sophisticated tool that plays a crucial role in query performance. By understanding how the optimizer works, including its different types, modes, and methods for influencing its behavior, you can effectively manage and tune your database queries. Leveraging features like SQL profiles, hints, and adaptive optimization can further enhance query performance and ensure that your database operates efficiently.