How to Optimize Queries for Better Performance in Oracle

March 26, 2025

Efficient query optimization is crucial for maintaining high performance in Oracle databases. Poorly optimized queries can lead to slow response times, increased CPU usage, and overall system inefficiencies. In this blog, we’ll explore key strategies to optimize queries in Oracle for better performance.

1. Use Indexing Wisely

Indexes help speed up query execution by allowing the database to quickly locate rows. However, excessive indexing can increase the overhead of DML (INSERT, UPDATE, DELETE) operations.

Best Practices:

Use B-Tree Indexes for highly selective columns.
Use Bitmap Indexes for low-cardinality columns.
Use Function-Based Indexes when filtering data using expressions.
Avoid indexing frequently updated columns to reduce overhead.

2. Optimize SQL Execution Plans

Oracle generates an execution plan to determine the most efficient way to execute a query.

Steps to Analyze Execution Plans:

Use EXPLAIN PLAN to check the query execution path:

EXPLAIN PLAN FOR SELECT * FROM employees WHERE department_id = 10;
SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY);

Use Autotrace to get execution statistics:

SET AUTOTRACE ON;
SELECT * FROM employees WHERE department_id = 10;

Use AWR (Automatic Workload Repository) Reports for long-term performance analysis.

3. Avoid Full Table Scans

A full table scan can slow down queries if an index can be used instead.

How to Avoid:

Ensure WHERE clause filters use indexed columns.

Use ROWNUM or FETCH FIRST to limit results:

SELECT * FROM employees WHERE department_id = 10 FETCH FIRST 10 ROWS ONLY;

Partition large tables to improve query efficiency.

4. Optimize Joins and Subqueries

Joins and subqueries can impact performance significantly.

Best Practices:

Use INNER JOIN instead of subqueries where possible.
Optimize JOIN conditions by indexing the join columns.
Use HASH JOIN for large datasets instead of NESTED LOOP JOIN.
Avoid unnecessary Cartesian Joins (joining without conditions).

Example:

SELECT e.employee_id, e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.department_id;

5. Use Bind Variables

Bind variables improve query performance by reducing parsing time and optimizing execution plans.

Example:

SELECT * FROM employees WHERE department_id = :dept_id;

6. Gather Statistics Regularly

Oracle uses statistics to generate optimal execution plans. Outdated statistics can lead to inefficient queries.

How to Gather Stats:

EXEC DBMS_STATS.GATHER_TABLE_STATS('HR', 'EMPLOYEES');

7. Optimize Sorting and Aggregation

Sorting and aggregation operations (e.g., ORDER BY, GROUP BY, DISTINCT) can be resource-intensive.

Best Practices:

Use indexes on ORDER BY columns.
Use HASH AGGREGATION instead of SORT AGGREGATION where possible.
Minimize the use of DISTINCT if not required.

Example:

SELECT department_id, COUNT(*) FROM employees GROUP BY department_id;

8. Tune Temporary Tables and Materialized Views

Temporary tables and Materialized Views improve performance for complex queries.

Example Materialized View:

CREATE MATERIALIZED VIEW emp_dept_mv AS
SELECT e.employee_id, e.name, d.department_name
FROM employees e
JOIN departments d ON e.department_id = d.department_id;

9. Optimize Parallel Query Execution

For large datasets, enabling parallel query execution can improve performance.

Example:

ALTER SESSION ENABLE PARALLEL DML;
SELECT /*+ PARALLEL(8) */ * FROM employees;

10. Monitor and Tune with Performance Tools

AWR Reports (@?/rdbms/admin/awrrpt.sql)
ASH (Active Session History)
SQL Tuning Advisor (DBMS_SQLTUNE)

Conclusion

Optimizing queries in Oracle requires a combination of indexing, execution plan analysis, and proper SQL structuring. By applying these best practices, you can significantly improve query performance, reduce CPU usage, and enhance database efficiency.

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