SQL tuning is the attempt to diagnose and repair SQL statements that fail to meet a performance standard.
This chapter contains the following topics:
SQL tuning is the iterative process of improving SQL statement performance to meet specific, measurable, and achievable goals.
SQL tuning implies fixing problems in deployed applications. In contrast, application design sets the security and performance goals before deploying an application.
A SQL statement becomes a problem when it fails to perform according to a predetermined and measurable standard.
After you have identified the problem, a typical tuning session has one of the following goals:
Reduce user response time, which means decreasing the time between when a user issues a statement and receives a response
Improve throughput, which means using the least amount of resources necessary to process all rows accessed by a statement
For a response time problem, consider an online book seller application that hangs for three minutes after a customer updates the shopping cart. Contrast with a three-minute parallel query in a data warehouse that consumes all of the database host CPU, preventing other queries from running. In each case, the user response time is three minutes, but the cause of the problem is different, and so is the tuning goal.
SQL tuning requires a foundation of database knowledge.
If you are tuning SQL, then this manual assumes that you have the following knowledge and skills:
Familiarity with database architecture
Database architecture is not the domain of administrators alone. As a developer, you want to develop applications in the least amount of time against an Oracle database, which requires exploiting the database architecture and features. For example, not understanding Oracle Database concurrency controls and multiversioning read consistency may make an application corrupt the integrity of the data, run slowly, and decrease scalability.
Oracle Database Concepts explains the basic relational data structures, transaction management, storage structures, and instance architecture of Oracle Database.
Knowledge of SQL and PL/SQL
Because of the existence of GUI-based tools, it is possible to create applications and administer a database without knowing SQL. However, it is impossible to tune applications or a database without knowing SQL.
Oracle Database Concepts includes an introduction to Oracle SQL and PL/SQL. You must also have a working knowledge of Oracle Database SQL Language Reference, Oracle Database PL/SQL Packages and Types Reference, and Oracle Database PL/SQL Packages and Types Reference.
Familiarity with database-provided SQL tuning tools
The database generates performance statistics, and provides SQL tuning tools that interpret these statistics.
Oracle Database 2 Day + Performance Tuning Guide provides an introduction to the principal SQL tuning tools.
After you have identified the goal for a tuning session, for example, reducing user response time from three minutes to less than a second, the problem becomes how to accomplish this goal.
The Oracle-recommended tuning methodology is covered in detail in "SQL Performance Methodology".
The specifics of a tuning session depend on many factors, including whether you tune proactively or reactively.
In proactive SQL tuning, you regularly use SQL Tuning Advisor to determine whether you can make SQL statements perform better. In reactive SQL tuning, you correct a SQL-related problem that a user has experienced.
Whether you tune proactively or reactively, a typical SQL tuning session involves all or most of the following tasks:
Identifying high-load SQL statements
Review past execution history to find the statements responsible for a large share of the application workload and system resources.
Gathering performance-related data
The optimizer statistics are crucial to SQL tuning. If these statistics do not exist or are no longer accurate, then the optimizer cannot generate the best plan. Other data relevant to SQL performance include the structure of tables and views that the statement accessed, and definitions of any indexes available to the statement.
Determining the causes of the problem
Typically, causes of SQL performance problems include:
Inefficiently designed SQL statements
If a SQL statement is written so that it performs unnecessary work, then the optimizer cannot do much to improve its performance. Examples of inefficient design include
Suboptimal execution plans
The query optimizer (also called the optimizer) is internal software that determines which execution plan is most efficient. Sometimes the optimizer chooses a plan with a suboptimal access path, which is the means by which the database retrieves data from the database. For example, the plan for a query predicate with low selectivity may use a full table scan on a large table instead of an index.
You can compare the execution plan of an optimally performing SQL statement to the plan of the statement when it performs suboptimally. This comparison, along with information such as changes in data volumes, can help identify causes of performance degradation.
Missing SQL access structures
Absence of SQL access structures, such as indexes and materialized views, is a typical reason for suboptimal SQL performance. The optimal set of access structures can improve SQL performance by orders of magnitude.
Stale optimizer statistics
Statistics gathered by
DBMS_STATS can become stale when the statistics maintenance operations, either automatic or manual, cannot keep up with the changes to the table data caused by DML. Because stale statistics on a table do not accurately reflect the table data, the optimizer can make decisions based on faulty information and generate suboptimal execution plans.
Suboptimal performance might be connected with memory, I/O, and CPU problems.
Defining the scope of the problem
The scope of the solution must match the scope of the problem. Consider a problem at the database level and a problem at the statement level. For example, the shared pool is too small, which causes cursors to age out quickly, which in turn causes many hard parses. Using an initialization parameter to increase the shared pool size fixes the problem at the database level and improves performance for all sessions. However, if a single SQL statement is not using a helpful index, then changing the optimizer initialization parameters for the entire database could harm overall performance. If a single SQL statement has a problem, then an appropriately scoped solution addresses just this problem with this statement.
Implementing corrective actions for suboptimally performing SQL statements
These actions vary depending on circumstances. For example, you might rewrite a SQL statement to be more efficient, avoiding unnecessary hard parsing by rewriting the statement to use bind variables. You might also use equijoins, remove functions from
WHERE clauses, and break a complex SQL statement into multiple simple statements.
In some cases, you improve SQL performance not by rewriting the statement, but by restructuring schema objects. For example, you might index a new access path, or reorder columns in a concatenated index. You might also partition a table, introduce derived values, or even change the database design.
Preventing SQL performance regressions
To ensure optimal SQL performance, verify that execution plans continue to provide optimal performance, and choose better plans if they come available. You can achieve these goals using optimizer statistics, SQL profiles, and SQL plan baselines.
SQL tuning tools are either automated or manual.
In this context, a tool is automated if the database itself can provide diagnosis, advice, or corrective actions. A manual tool requires you to perform all of these operations.
All tuning tools depend on the basic tools of the dynamic performance views, statistics, and metrics that the database instance collects. The database itself contains the data and metadata required to tune SQL statements.
Oracle Database provides several advisors relevant for SQL tuning.
Additionally, SQL plan management is a mechanism that can prevent performance regressions and also help you to improve SQL performance.
All of the automated SQL tuning tools can use SQL tuning sets as input. A SQL tuning set (STS) is a database object that includes one or more SQL statements along with their execution statistics and execution context.
ADDM is self-diagnostic software built into Oracle Database.
ADDM can automatically locate the root causes of performance problems, provide recommendations for correction, and quantify the expected benefits. ADDM also identifies areas where no action is necessary.
ADDM and other advisors use Automatic Workload Repository (AWR), which is an infrastructure that provides services to database components to collect, maintain, and use statistics. ADDM examines and analyzes statistics in AWR to determine possible performance problems, including high-load SQL.
For example, you can configure ADDM to run nightly. In the morning, you can examine the latest ADDM report to see what might have caused a problem and if there is a recommended fix. The report might show that a particular
SELECT statement consumed a huge amount of CPU, and recommend that you run SQL Tuning Advisor.
SQL Tuning Advisor is internal diagnostic software that identifies problematic SQL statements and recommends how to improve statement performance.
When run during database maintenance windows as an automated maintenance task, SQL Tuning Advisor is known as Automatic SQL Tuning Advisor.
SQL Tuning Advisor takes one or more SQL statements as an input and invokes the Automatic Tuning Optimizer to perform SQL tuning on the statements. The advisor performs the following types of analysis:
Checks for missing or stale statistics
Builds SQL profiles
A SQL profile is a set of auxiliary information specific to a SQL statement. A SQL profile contains corrections for suboptimal optimizer estimates discovered during Automatic SQL Tuning. This information can improve optimizer estimates for cardinality, which is the number of rows that is estimated to be or actually is returned by an operation in an execution plan, and selectivity. These improved estimates lead the optimizer to select better plans.
Explores whether a different access path can significantly improve performance
Identifies SQL statements that lend themselves to suboptimal plans
The output is in the form of advice or recommendations, along with a rationale for each recommendation and its expected benefit. The recommendation relates to a collection of statistics on objects, creation of new indexes, restructuring of the SQL statement, or creation of a SQL profile. You can choose to accept the recommendations to complete the tuning of the SQL statements.
SQL Access Advisor is internal diagnostic software that recommends which materialized views, indexes, and materialized view logs to create, drop, or retain.
SQL Access Advisor takes an actual workload as input, or the advisor can derive a hypothetical workload from the schema. SQL Access Advisor considers the trade-offs between space usage and query performance, and recommends the most cost-effective configuration of new and existing materialized views and indexes. The advisor also makes recommendations about partitioning.
SQL plan management is a preventative mechanism that enables the optimizer to automatically manage execution plans, ensuring that the database uses only known or verified plans.
This mechanism can build a SQL plan baseline, which contains one or more accepted plans for each SQL statement. By using baselines, SQL plan management can prevent plan regressions from environmental changes, while permitting the optimizer to discover and use better plans.
SQL Performance Analyzer determines the effect of a change on a SQL workload by identifying performance divergence for each SQL statement.
System changes such as upgrading a database or adding an index may cause changes to execution plans, affecting SQL performance. By using SQL Performance Analyzer, you can accurately forecast the effect of system changes on SQL performance. Using this information, you can tune the database when SQL performance regresses, or validate and measure the gain when SQL performance improves.
In some situations, you may want to run manual tools in addition to the automated tools. Alternatively, you may not have access to the automated tools.
Execution plans are the principal diagnostic tool in manual SQL tuning. For example, you can view plans to determine whether the optimizer selects the plan you expect, or identify the effect of creating an index on a table.
You can display execution plans in multiple ways. The following tools are the most commonly used:
This SQL statement enables you to view the execution plan that the optimizer would use to execute a SQL statement without actually executing the statement. See Oracle Database SQL Language Reference.
AUTOTRACE command in SQL*Plus generates the execution plan and statistics about the performance of a query. This command provides statistics such as disk reads and memory reads. See SQL*Plus User's Guide and Reference.
V$SQL_PLAN and related views
These views contain information about executed SQL statements, and their execution plans, that are still in the shared pool. See Oracle Database Reference.
You can use the
DBMS_XPLAN package methods to display the execution plan generated by the
EXPLAIN PLAN command and query of
The Real-Time SQL Monitoring feature of Oracle Database enables you to monitor the performance of SQL statements while they are executing. By default, SQL monitoring starts automatically when a statement runs in parallel, or when it has consumed at least 5 seconds of CPU or I/O time in a single execution.
A database operation is a set of database tasks defined by end users or application code, for example, a batch job or Extraction, Transformation, and Loading (ETL) processing. You can define, monitor, and report on database operations. Real-Time Database Operations provides the ability to monitor composite operations automatically. The database automatically monitors parallel queries, DML, and DDL statements as soon as execution begins.
Oracle Enterprise Manager Cloud Control (Cloud Control) provides easy-to-use SQL monitoring pages. Alternatively, you can monitor SQL-related statistics using the
V$SQL_PLAN_MONITOR views. You can use these views with the following views to get more information about executions that you are monitoring:
A SQL trace file provides performance information on individual SQL statements: parse counts, physical and logical reads, misses on the library cache, and so on. You can use this information to diagnose SQL performance problems.
You can enable and disable SQL tracing for a specific session using the
DBMS_SESSION packages. Oracle Database implements tracing by generating a trace file for each server process when you enable the tracing mechanism.
Oracle Database provides the following command-line tools for analyzing trace files:
This utility accepts as input a trace file produced by the SQL Trace facility, and then produces a formatted output file.
This utility consolidates trace output from multiple trace files based on criteria such as session ID, client ID, and service ID. After
trcsess merges the trace information into a single output file, you can format the output file with
trcsess is useful for consolidating the tracing of a particular session for performance or debugging purposes.
End-to-End Application Tracing simplifies the process of diagnosing performance problems in multitier environments. In these environments, the middle tier routes a request from an end client to different database sessions, making it difficult to track a client across database sessions. End-to-End application tracing uses a client ID to uniquely trace a specific end-client through all tiers to the database.
Oracle Database PL/SQL Packages and Types Reference to learn more about
A hint is an instruction passed to the optimizer through comments in a SQL statement. Hints enable you to make decisions normally made automatically by the optimizer.
In a test or development environment, hints are useful for testing the performance of a specific access path. For example, you may know that a specific index is more selective for certain queries. In this case, you may use hints to instruct the optimizer to use a better execution plan, as in the following example:
SELECT /*+ INDEX (employees emp_department_ix) */ employee_id, department_id FROM employees WHERE department_id > 50;
Cloud Control is a system management tool that provides centralized management of a database environment. Cloud Control provides access to most tuning tools.
By combining a graphical console, Oracle Management Servers, Oracle Intelligent Agents, common services, and administrative tools, Cloud Control provides a comprehensive system management platform.
You can also access all SQL tuning tools using a command-line interface. For example, the
DBMS_ADVISOR package is the command-line interface for SQL Tuning Advisor.
Oracle recommends Cloud Control as the best interface for database administration and tuning. In cases where the command-line interface better illustrates a particular concept or task, this manual uses command-line examples. However, in these cases the tuning tasks include a reference to the principal Cloud Control page associated with the task.