12 Automatic SQL Tuning

12.1.1.1 Normal mode

In normal mode, the optimizer compiles the SQL and generates an execution plan. The normal mode of the optimizer generates a reasonable execution plan for the vast majority of SQL statements. Under normal mode the optimizer operates with very strict time constraints, usually a fraction of a second, during which it must find a good execution plan.

12.1.1.2 Tuning mode

In tuning mode, the optimizer performs additional analysis to check whether the execution plan produced under normal mode can be further improved. The output of the query optimizer is not an execution plan, but a series of actions, along with their rationale and expected benefit for producing a significantly superior plan. When called under the tuning mode, the optimizer is referred to as the Automatic Tuning Optimizer. The tuning performed by the Automatic Tuning Optimizer is called Automatic SQL Tuning.

Under tuning mode, the optimizer can take several minutes to tune a single statement. It is both time and resource intensive to invoke the Automatic Tuning Optimizer every time a query has to be hard-parsed. The Automatic Tuning Optimizer is meant to be used for complex and high-load SQL statements that have non-trivial impact on the entire system. The Automatic Database Diagnostic Monitor (ADDM) proactively identifies high-load SQL statements which are good candidates for Automatic SQL Tuning. See Chapter 6, "Automatic Performance Diagnostics".

12.1.2.1 Statistics Analysis

The query optimizer relies on object statistics to generate execution plans. If these statistics are stale or missing, the optimizer does not have the necessary information it needs and can generate poor execution plans. The Automatic Tuning Optimizer checks each query object for missing or stale statistics, and produces two types of output:

• Recommendations to gather relevant statistics for objects with stale or no statistics.

  Because optimizer statistics are automatically collected and refreshed, this problem may be encountered only when automatic optimizer statistics collection has been turned off. See "Automatic Statistics Gathering".

• Auxiliary information in the form of statistics for objects with no statistics, and statistic adjustment factor for objects with stale statistics.

This auxiliary information is stored in an object called a SQL Profile.

12.1.2.2 SQL Profiling

The query optimizer can sometimes produce inaccurate estimates about an attribute of a statement due to lack of information, leading to poor execution plans. Traditionally, users have corrected this problem by manually adding hints to the application code to guide the optimizer into making correct decisions. For packaged applications, changing application code is not an option and the only alternative available is to log a bug with the application vendor and wait for a fix.

Automatic SQL Tuning deals with this problem with its SQL Profiling capability. The Automatic Tuning Optimizer creates a profile of the SQL statement called a SQL Profile, consisting of auxiliary statistics specific to that statement. The query optimizer under normal mode makes estimates about cardinality, selectivity, and cost that can sometimes be off by a significant amount resulting in poor execution plans. SQL Profile addresses this problem by collecting additional information using sampling and partial execution techniques to verify and, if necessary, adjust these estimates.

During SQL Profiling, the Automatic Tuning Optimizer also uses execution history information of the SQL statement to appropriately set optimizer parameter settings, such as changing the OPTIMIZER_MODE initialization parameter setting from ALL_ROWS to FIRST_ROWS for that SQL statement.

The output of this type of analysis is a recommendation to accept the SQL Profile. A SQL Profile, once accepted, is stored persistently in the data dictionary. Note that the SQL Profile is specific to a particular query. If accepted, the optimizer under normal mode uses the information in the SQL Profile in conjunction with regular database statistics when generating an execution plan. The availability of the additional information makes it possible to produce well-tuned plans for corresponding SQL statement without requiring any change to the application code.

The scope of a SQL Profile can be controlled by the CATEGORY profile attribute. This attribute determines which user sessions can apply the profile. You can view the CATEGORY attribute for a SQL Profile in CATEGORY column of the DBA_SQL_PROFILES view. By default, all profiles are created in the DEFAULT category. This means that all user sessions where the SQLTUNE_CATEGORY initialization parameter is set to DEFAULT can use the profile.

By altering the category of a SQL profile, you can determine which sessions are affected by the creation of a profile. For example, by setting the category of a SQL Profile to DEV, only those users sessions where the SQLTUNE_CATEGORY initialization parameter is set to DEV can use the profile. All other sessions do not have access to the SQL Profile and execution plans for SQL statements are not impacted by the SQL profile. This technique enables you to test a SQL Profile in a restricted environment before making it available to other user sessions.

It is important to note that the SQL Profile does not freeze the execution plan of a SQL statement, as done by stored outlines. As tables grow or indexes are created or dropped, the execution plan can change with the same SQL Profile. The information stored in it continues to be relevant even as the data distribution or access path of the corresponding statement change. However, over a long period of time, its content can become outdated and would have to be regenerated. This can be done by running Automatic SQL Tuning again on the same statement to regenerate the SQL Profile.

SQL Profiles apply to the following statement types:

• SELECT statements

• UPDATE statements

• INSERT statements (only with a SELECT clause)

• DELETE statements

• CREATE TABLE statements (only with the AS SELECT clause)

• MERGE statements (the update or insert operations)

A complete set of functions are provided for management of SQL Profiles. See "SQL Profiles".

12.1.2.3 Access Path Analysis

Indexes can tremendously enhance performance of a SQL statement by reducing the need for full table scans on large tables. Effective indexing is a common tuning technique. The Automatic Tuning Optimizer also explores whether a new index can significantly enhance the performance of a query. If such an index is identified, it recommends its creation.

Because the Automatic Tuning Optimizer does not analyze how its index recommendation can affect the entire SQL workload, it also recommends running a the SQLAccess Advisor utility on the SQL statement along with a representative SQL workload. The SQLAccess Advisor looks at the impact of creating an index on the entire SQL workload before making any recommendations. See "Automatic SQL Tuning Features".

12.1.2.4 SQL Structure Analysis

The Automatic Tuning Optimizer identifies common problems with structure of SQL statements than can lead to poor performance. These could be syntactic, semantic, or design problems with the statement. In each of these cases the Automatic Tuning Optimizer makes relevant suggestions to restructure the SQL statements. The alternative suggested is similar, but not equivalent, to the original statement.

For example, the optimizer may suggest to replace UNION operator with UNION ALL or to replace NOT IN with NOT EXISTS. An application developer can then determine if the advice is applicable to their situation or not. For instance, if the schema design is such that there is no possibility of producing duplicates, then the UNION ALL operator is much more efficient than the UNION operator. These changes require a good understanding of the data properties and should be implemented only after careful consideration.

12.2.5.1 Creating a SQL Tuning Task

You can create tuning tasks from the text of a single SQL statement, a SQL Tuning Set containing multiple statements, a SQL statement selected by SQL identifier from the cursor cache, or a SQL statement selected by SQL identifier from the Automatic Workload Repository.

For example, to use the SQL Tuning Advisor to optimize a specified SQL statement text, you need to create a tuning task with the SQL statement passed as a CLOB argument. For the following PL/SQL code, the user HR has been granted the ADVISOR privilege and the function is run as user HR on the employees table in the HR schema.

DECLARE
 my_task_name VARCHAR2(30);
 my_sqltext   CLOB;
BEGIN
 my_sqltext := 'SELECT /*+ ORDERED */ * '                      ||
               'FROM employees e, locations l, departments d ' ||
               'WHERE e.department_id = d.department_id AND '  ||
                     'l.location_id = d.location_id AND '      ||
                     'e.employee_id < :bnd';

 my_task_name := DBMS_SQLTUNE.CREATE_TUNING_TASK(
         sql_text    => my_sqltext,
         bind_list   => sql_binds(anydata.ConvertNumber(100)),
         user_name   => 'HR',
         scope       => 'COMPREHENSIVE',
         time_limit  => 60,
         task_name   => 'my_sql_tuning_task',
         description => 'Task to tune a query on a specified employee');
END;
/

In this example, 100 is the value for bind variable :bnd passed as function argument of type SQL_BINDS, HR is the user under which the CREATE_TUNING_TASK function analyzes the SQL statement, the scope is set to COMPREHENSIVE which means that the advisor also performs SQL Profiling analysis, and 60 is the maximum time in seconds that the function can run. In addition, values for task name and description are provided.

The CREATE_TUNING_TASK function returns the task name that you have provided or generates a unique task name. You can use the task name to specify this task when using other APIs. To view the task names associated with a specific owner, you can run the following:

SELECT task_name FROM DBA_ADVISOR_LOG WHERE owner = 'HR';

12.2.5.2 Executing a SQL Tuning Task

After you have created a tuning task, you need to execute the task and start the tuning process. For example:

BEGIN
  DBMS_SQLTUNE.EXECUTE_TUNING_TASK( task_name => 'my_sql_tuning_task' );
END;
/

12.2.5.3 Checking the Status of a SQL Tuning Task

You can check the status of the task by reviewing the information in the USER_ADVISOR_TASKS view or check execution progress of the task in the V$SESSION_LONGOPS view. For example:

SELECT status FROM USER_ADVISOR_TASKS WHERE task_name = 'my_sql_tuning_task';

12.2.5.4 Checking the Progress of the SQL Tuning Advisor

You can check the execution progress of the SQL Tuning Advisor in the V$ADVISOR_PROGRESS view. For example:

SELECT sofar, totalwork FROM V$ADVISOR_PROGRESS WHERE user_name = 'HR' AND task_name = 'my_sql_tuning_task';

12.2.5.5 Displaying the Results of a SQL Tuning Task

After a task has been executed, you display a report of the results with the REPORT_TUNING_TASK function. For example:

SET LONG 1000
SET LONGCHUNKSIZE 1000
SET LINESIZE 100
SELECT DBMS_SQLTUNE.REPORT_TUNING_TASK( 'my_sql_tuning_task')
  FROM DUAL;

The report contains all the findings and recommendations of Automatic SQL Tuning. For each proposed recommendation, the rationale and benefit is provided along with the SQL commands needed to implement the recommendation.

Additional information about tuning tasks and results can be found in DBA views. See "SQL Tuning Information Views".

12.2.5.6 Additional Operations on a SQL Tuning Task

You can use the following APIs for managing SQL tuning tasks:

• INTERRUPT_TUNING_TASK to interrupt a task while executing, causing a normal exit with intermediate results

• RESUME_TUNING_TASK to resume a previously interrupted task

• CANCEL_TUNING_TASK to cancel a task while executing, removing all results from the task

• RESET_TUNING_TASK to reset a task while executing, removing all results from the task and returning the task to its initial state

• DROP_TUNING_TASK to drop a task, removing all results associated with the task

12.3.2.1 Creating a SQL Tuning Set

The CREATE_SQLSET procedure is used to create an empty STS object in the database. For example, the following procedure creates an STS object that could be used to tune I/O intensive SQL statements during a specific period of time:

BEGIN
  DBMS_SQLTUNE.CREATE_SQLSET(
    sqlset_name => 'my_sql_tuning_set', 
    description  => 'I/O intensive workload');
END;
/

where my_sql_tuning_set is the name of the STS in the database and 'I/O intensive workload' is the description assigned to the STS.

12.3.2.2 Loading a SQL Tuning Set

The LOAD_SQLSET procedure populates the STS with selected SQL statements. The standard sources for populating an STS are the workload repository, another STS, or the cursor cache. For both the workload repository and STS, there are predefined table functions that can be used to select columns from the source to populate a new STS.

In the following example, procedure calls are used to load my_sql_tuning_set from an AWR baseline called peak baseline. The data has been filtered to select only the top 30 SQL statements ordered by elapsed time. First a ref cursor is opened to select from the specified baseline. Next the statements and their statistics are loaded from the baseline into the STS.

DECLARE
 baseline_cursor DBMS_SQLTUNE.SQLSET_CURSOR;
BEGIN
 OPEN baseline_cursor FOR
    SELECT VALUE(p)
    FROM TABLE (DBMS_SQLTUNE.SELECT_WORKLOAD_REPOSITORY(
                  'peak baseline',
                   NULL, NULL,
                   'elapsed_time',
                   NULL, NULL, NULL,
                   30)) p;

    DBMS_SQLTUNE.LOAD_SQLSET(
             sqlset_name     => 'my_sql_tuning_set',
             populate_cursor => baseline_cursor);
END;
/

12.3.2.3 Displaying the Contents of a SQL Tuning Set

The SELECT_SQLSET table function reads the contents of the STS. After an STS has been created and populated, you can browse the SQL in the STS using different filtering criteria. The SELECT_SQLSET procedure is provided for this purpose.

In the following example, the SQL statements in the STS are displayed for statements with a disk-reads to buffer-gets ratio greater than or equal to 75%.

SELECT * FROM TABLE(DBMS_SQLTUNE.SELECT_SQLSET( 
   'my_sql_tuning_set',
   '(disk_reads/buffer_gets) >= 0.75'));

Additional details of the SQL Tuning Sets that have been created and loaded can also be displayed with DBA views, such as DBA_SQLSET, DBA_SQLSET_STATEMENTS, and DBA_SQLSET_BINDS.

12.3.2.4 Modifying a SQL Tuning Set

SQL statements can be updated and deleted from a SQL Tuning Set based on a search condition. In the following example, the DELETE_SQLSET procedure deletes SQL statements from my_sql_tuning_set that have been executed less than fifty times.

BEGIN
  DBMS_SQLTUNE.DELETE_SQLSET(
      sqlset_name  => 'my_sql_tuning_set',
      basic_filter => 'executions < 50');
END;
/

12.3.2.5 Transporting a SQL Tuning Set

SQL Tuning Sets can be transported to another system by first exporting the STS from one system to a staging table, then importing the STS from the staging table into another system.

To transport a SQL Tuning Set:

1. Use the CREATE_STGTAB_SQLSET procedure to create a staging table where the SQL Tuning Sets will be exported.

   The following example shows how to create a staging table named staging_table.

   BEGIN
     DBMS_SQLTUNE.CREATE_STGTAB_SQLSET( table_name => 'staging_table' );
   END;
   /
   

2. Use the PACK_STGTAB_SQLSET procedure to export SQL Tuning Sets into the staging table.

   The following example shows how to export a SQL Tuning Set named my_sts to the staging table.

   BEGIN
     DBMS_SQLTUNE.PACK_STGTAB_SQLSET(
         sqlset_name  => 'my_sts',
         staging_table_name => 'staging_table');
   END;
   /
   

3. Move the staging table to the system where the SQL Tuning Sets will be imported using the mechanism of choice (such as datapump or database link).

4. On the system where the SQL Tuning Sets will be imported, use the UNPACK_STGTAB_SQLSET procedure to import SQL Tuning Sets from the staging table.

   The following example shows how to import SQL Tuning Sets contained in the staging table.

   BEGIN
     DBMS_SQLTUNE.UNPACK_STGTAB_SQLSET(
         sqlset_name  => '%',
         replace  => TRUE,
         staging_table_name => 'staging_table');
   END;
   /
   

12.3.2.6 Dropping a SQL Tuning Set

The DROP_SQLSET procedure is used to drop an STS that is no longer needed. For example:

BEGIN
  DBMS_SQLTUNE.DROP_SQLSET( sqlset_name => 'my_sql_tuning_set' );
END;
/

12.3.2.7 Additional Operations on SQL Tuning Sets

You can use the following APIs to manage an STS:

• Updating the attributes of SQL statements in an STS

  The UPDATE_SQLSET procedure updates the attributes of SQL statements (such as PRIORITY or OTHER) in an existing STS identified by STS name and SQL identifier.

• Capturing the full system workload

  The CAPTURE_CURSOR_CACHE_SQLSET function enables the capture of the full system workload by repeatedly polling the cursor cache over a specified interval. This function is a lot more efficient than repeatedly using the SELECT_CURSOR_CACHE and LOAD_SQLSET procedures to capture the cursor cache over an extended period of time. This function effectively captures the entire workload, as opposed to the AWR—which only captures the workload of high-load SQL statements—or the LOAD_SQLSET procedure, which accesses the data source only once.

• Adding and removing a reference to an STS

  The ADD_SQLSET_REFERENCE function adds a new reference to an existing STS to indicate its use by a client. The function returns the identifier of the added reference. The REMOVE_SQLSET_REFERENCE procedure is used to deactivate an STS to indicate it is no longer used by the client.