Preamble
The Oracle/PLSQL MIN function returns the minimum value of the expression.
Oracle/PLSQL syntax of MIN function
SELECT MIN(aggregate_expression_id)
FROM tabs
[WHERE conds]
OR syntax for MIN function with results grouped in one or more columns:
SELECT expression1_id, expression2_id, ... expression_n_id,
MIN(aggregate_expression_id)
FROM tabs
[WHERE conds]
GROUP BY expression1_id, expression2_id, ... expression_n_id;
Parameters and arguments of the function
- expression1_id, expression2_id, …expression_n_id – expressions that are not encapsulated in the MIN function must be included in the GROUP BY operator at the end of the SQL sentence.
- aggregate_expression_id – is a column or expression from which the minimum value will be returned.
- tabs – tables from which you want to get records. At least one table must be specified in FROM operator.
- WHERE conds – optional. These are the conditions that must be met for the selected records.
MIN function in the following versions of Oracle/PLSQL
|
Oracle 12c, Oracle 11g, Oracle 10g, Oracle 9i, Oracle 8i
|
One Field Example
Let’s consider examples of the MIN function and learn how to use the MIN function in Oracle/PLSQL.
For example, you will want to know what is the minimum wage for all employees.
SELECT MIN(salary_id) AS "Lowest Salary"
FROM empls;
The query above will return the minimum wage for all employees from the employees table.
Example – Using GROUP BY
In some cases, you may need to use GROUP BY with MIN function.
For example, you might also want to use the MIN function to return the department and MIN(salary) to the department.
SELECT depart, MIN(salary_id) AS "Lowest salary".
FROM empls
GROUP BY depart;
Since your SELECT operator has one column that is not encapsulated in the MIN function, you must use GROUP BY. Therefore, the department field must be specified in the GROUP BY operator.
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
How Can Banks Prevent Database Bottlenecks in Real-Time Financial Transactions?
- 1 September 2026
- Database Performance Management
Banks can prevent database bottlenecks in banking by continuously monitoring SQL workloads, optimizing queries and indexes, detecting resource contention, analyzing transaction latency, and identifying anomalies before performance declines. Effective database performance monitoring for banks provides real-time workload visibility and faster root cause analysis. Enteros helps financial institutions identify database inefficiencies and maintain reliable, scalable transaction … Continue reading “How Can Banks Prevent Database Bottlenecks in Real-Time Financial Transactions?”
Why Is Database Observability Important for Modern Hospitals and Healthcare IT Teams?
Database observability in healthcare is important because hospitals depend on databases to power EHRs, patient portals, clinical applications, billing, analytics, and other essential systems. It gives healthcare IT teams deeper visibility into SQL workloads, resource usage, bottlenecks, and performance changes. Enteros supports this approach with database observability, AI-powered analysis, anomaly detection, and root cause analysis … Continue reading “Why Is Database Observability Important for Modern Hospitals and Healthcare IT Teams?”
How Can Healthcare Organizations Reduce Cloud Database Costs With AIOps and FinOps
Healthcare organizations can reduce cloud database costs by combining AIOps with FinOps to identify inefficient workloads, detect anomalies, rightsize resources, and connect database performance with infrastructure spending. Effective healthcare cloud database cost optimization focuses on eliminating waste without compromising reliability. Enteros supports this approach through database observability, AI-powered SQL analysis, root cause analysis, performance intelligence, … Continue reading “How Can Healthcare Organizations Reduce Cloud Database Costs With AIOps and FinOps”
What Database Performance Challenges Do Hospitals Face in Cloud-Based Healthcare Systems?
Hospitals face database performance challenges such as slow SQL queries, growing healthcare data, EHR performance issues, database bottlenecks, resource contention, cloud complexity, and rising costs. Cloud-based healthcare systems require continuous database monitoring, workload optimization, anomaly detection, and root-cause analysis. AI-powered AIOps can help hospitals improve database performance, reliability, scalability, and cloud cost efficiency while supporting … Continue reading “What Database Performance Challenges Do Hospitals Face in Cloud-Based Healthcare Systems?”