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Query Optimization in Oracle



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Query optimization is a complex and creative process that lacks a definitive formula. While it relies on fundamental principles, there is often no one-size-fits-all solution. Therefore, evaluating the necessity of query optimization before diving into the task is crucial. Otherwise, the time invested may outweigh the minimal impact of optimization. The primary focus should be on optimizing slow queries that are executed frequently, particularly during periods of high database workload. Doing so reduces the overall load on the system, resulting in improved performance.

Query optimization in Oracle is the process of improving the efficiency and performance of database queries. When you execute a query in a database management system (DBMS), the DBMS determines the most efficient way to retrieve and manipulate the data based on the query’s requirements. Query optimization minimizes query execution time and resource consumption while delivering the desired result set.

The query optimization process involves several steps, including:

  1. Parsing and Semantic Analysis: The DBMS parses the query and performs semantic analysis to ensure the query is syntactically correct and refers to valid database objects.
  2. Cost Estimation: The optimizer estimates the cost of executing various execution plans for the query. The cost estimation considers factors such as the number of I/O operations, CPU usage, and network communication.
  3. Plan Generation: The optimizer explores different execution plans and generates a set of potential plans based on cost estimations. These plans represent different ways the query can be executed.
  4. Plan Selection: The optimizer compares the estimated costs of the generated plans and selects the plan with the lowest cost. The selected plan is the one expected to execute the query most efficiently.
  5. Plan Execution: The DBMS executes the chosen execution plan to retrieve and process the data required by the query.

Query optimization techniques can vary depending on the specific DBMS. Common optimization techniques include:

  1. Index Utilization: The optimizer determines the most effective use of indexes to reduce the number of disk reads and improve data retrieval performance.
  2. Join Optimization: The optimizer decides the optimal join order and joins methods (e.g., nested loops join, hash join, merge join) to minimize the computational cost of joining multiple tables.
  3. Predicate Pushdown: The optimizer pushes filtering conditions as close to the data source as possible, reducing the amount of data that needs to be processed.
  4. Parallel Execution: In some cases, the optimizer may choose to execute parts of a query in parallel, utilizing multiple CPU cores or distributed processing to speed up the query execution.
  5. Statistics Collection: The optimizer relies on accurate statistical information about the data to make informed decisions. Regularly updating and maintaining statistics can help improve query optimization.

Effective query optimization can significantly enhance the performance of database systems, especially for complex queries or large datasets. It requires a deep understanding of the database schema, data distribution, and query patterns.

How to Optimize SQL Query in Oracle?

Optimizing SQL queries in Oracle involves a combination of understanding the query execution plan, analyzing query performance, and applying appropriate optimization techniques. Here are some steps you can follow to optimize SQL queries in Oracle:

  1. Analyse the Query Execution Plan: The first step is understanding how Oracle executes the query. Use the EXPLAIN PLAN statement or the SQL Developer tool to obtain the query execution plan. The execution plan shows how Oracle accesses the tables, joins them, applies filters, and performs other operations. Analyze the plan to identify potential bottlenecks or areas for improvement.
  2. Ensure Indexes are Optimized: Indexes play a crucial role in query performance. Ensure the appropriate indexes are created on the columns used in the query’s WHERE, JOIN, and ORDER BY clauses. Consider using composite indexes for multiple columns and analyze index usage using the INDEX_STATS view. If necessary, create or modify indexes to match the query access patterns.
  3. Use Bind Variables and Avoid Literal Values: Using bind variables in SQL queries helps improve performance by enabling query plan reuse. Bind variables allow Oracle to parse and execute queries more efficiently. Avoid using literal values in queries, especially when executing them multiple times, as it can lead to inefficient, hard parsing and suboptimal execution plans.
  4. Optimize Join Operations: For queries involving multiple tables, optimize join operations by ensuring appropriate join methods are used. Evaluate whether nested loop joins, hash joins, or merge joins are most suitable for the query. You can use hints (e.g., /*+ USE_HASH */) to influence the join method selection if necessary.
  5. Use Proper Index Access Methods: Oracle offers various index access methods, such as full index scans, unique scans, and range scans. Ensure that the appropriate index access methods are employed based on the query requirements and data distribution. Review the query execution plan and consider using hints to guide Oracle in choosing the most efficient index access method.
  6. Optimize Subqueries: Subqueries can impact query performance. If possible, rewrite subqueries as joins or use inline views to enhance performance. Ensure that subqueries are correlated efficiently and evaluate the need for materializing subquery results if they are reused multiple times within the query.
  7. Collect and Refresh Statistics: Accurate statistics are crucial for query optimization. Regularly gather statistics using the DBMS_STATS package or the ANALYZE command to ensure that the optimizer has up-to-date information about table and index cardinality. Consider using histograms for skewed data distributions.

Remember, query optimization is not a one-size-fits-all process. The effectiveness of optimization techniques can vary depending on factors like data volumes, query complexity, and the specific database environment. Understanding the underlying principles and continuously monitoring and adjusting queries can help maintain optimal performance.

How to Optimize SQL query using dbForge Studio for Oracle

DbForge Studio for Oracle provides several features that can help optimize SQL queries. Here are some ways you can leverage the tool to optimize your queries:

Query Profiler

DbForge Studio for Oracle includes a query profiler that allows you to analyze the performance of your SQL queries. You can run a query with the profiler enabled, and it will provide detailed information about the query execution, including execution time, resource usage, and the query execution plan. The query execution plan can help identify bottlenecks and areas for optimization. You can identify potential performance issues, such as suboptimal join methods, full table scans, or missing indexes. You can also compare different execution plans and assess the impact of various query optimization techniques.

For demonstration, I have imported a few tables of the SQL Server database named Stackoverflow2010 to the Oracle database named EltechIndia. I have used dbForge Studio’s Import external data utility.

EltechIndia contains a table named USERS which holds the data of the users who use the Stackoverflow database. Now, let me execute a simple SELECT statement to view the details of users.


SELECT u.”Id”, u.”AboutMe”, u.”Age”, u.”CreationDate”, u.”DisplayName”, u.”EmailHash”, u.”LastAccessDate”, u.”Reputation”, u.”Views”, u.”WebsiteUrl”, u.”AccountId”


Enable the profiler mode from the top menu and execute the query.

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Screenshot of profiler:

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As you can see in the above screenshot, the profiler populates the following information:

  1. Query Profiler Session: The query profiler session section has details of the query execution plan and session statistics. It also contains the history of any query execution, which can be used to compare multiple execution plans of queries.
  2. Query execution plan: The query profiler shows the query execution plan in a tabular format with the details of operations performed while generating the result set. It shows the execution steps, access methods, and estimated costs for each part of the query.

The generated execution plan can be used to identify the resource utilization and IO bottleneck, and other parameters which might contribute to performance degradation. Suppose the query profiler shows the performance issue can be resolved by adding a missing index or making changes to the existing index. In that case, we can use the Index Manager feature of dbForge studio.

Index Management

Efficient indexing is essential for query optimization. dbForge Studio for Oracle provides tools for managing indexes, such as creating, editing, and dropping indexes. You can review the existing indexes on your tables and ensure they are appropriately configured. You can also use the tool to create new indexes or modify existing indexes based on the query access patterns.

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The dbForge Studio provides a feature that can be used to create/edit/drop any index on a table. The changes in indexes can be made from the object manager of dbForge studio. To do that, right-click on the USER table and select Edit Table.


Another tab opens with the details of the USERS table. Here you can make changes in existing tables, like adding/modifying/deleting any index, constraints, and columns. Also, you can add or change the other configuration parameters like storage, temporal validity, etc.


Now, to add/modify the index, click on the Indexes tab. A window with index details opens, which looks like the following image:

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As you can see in the above screenshot, the Index manager is divided into three sections.

  1. List of existing indexes: Here, you can see the details (Index Name and Key Columns) of the indexes that are already created on a table.
  2. New Index: Here, you can specify the index properties, like the name of the index, type of index, and key columns of the index.
  3. Create Index Statement: In this section, you can view the CREATE statement for
  4. The table on which we are adding an index.
  5. Existing indexes.
  6. New Index.

The entire script can be used to re-create the object on another schema or table.

SQL Debugging

The SQL debugging feature in dbForge Studio for Oracle enables you to step through your SQL code, set breakpoints, and inspect variables during query execution. This feature does not add much value compared to the Index Manager and query profiler. Still, sometimes it can be helpful to identify which query within a stored procedure is causing performance issues. By debugging the query, we can pinpoint areas that need optimization and make necessary adjustments.

Note that while using dbForge Studio for Oracle, it’s important to have a good understanding of SQL query optimization techniques and best practices. The tool provides valuable insights and features to help optimize queries. Still, it’s crucial to interpret the results correctly and apply the appropriate optimizations based on your specific database and query requirements.


Database Performance Tuning is one of the most important jobs for any database administrator, and choosing the best database monitoring tool to administrate and monitor the database server’s performance is also an important aspect. In this article, we learned about the basics of performance tuning and how dbForge Studio for Oracle can help us improve database performance.

Jean-Pierre is a polyglot communication specialist, freelance journalist, and writer for with over two decades of experience in media and public relations. He creates engaging content, manages communication campaigns, and attends conferences to stay up-to-date with the latest trends. He brings his wealth of experience and expertise to provide insightful analysis and engaging content for's audience.

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