Range function in SQL

Introduction

Imagine that you have a list of employees in your company’s sales department and you have to assign the best salespeople. Again, since there are thousands of transactions and numerous factors to consider, the task of sorting and classifying the data through simple traditional methods is hectic. It brings together SQL sorting functions that are smart methods to classify the content of your database conveniently. Moreover, the functions provided can not only help you simplify the sorting operation when making decisions but also help you gain useful insights for your business. Now, let’s proceed to the analysis of what sorting is in SQL, how it works, when it can be used, and why.

Learning outcomes

• Understand the concept of sorting in SQL and its importance.
• Learn about the different sorting functions available in SQL.
• Discover practical examples of how to use sorting functions.
• Explore the advantages and potential drawbacks of using sorting functions in SQL.
• Learn best practices for effectively using sort functions in SQL.

Understanding Sorting in SQL

Ranking in SQL is a technique to assign a rank to each row in the result set based on a selected column. This is especially useful for sorted data such as ranking seller performance, ranking by score, or ranking products based on demand. There are several ranking functions built into SQL: RANK(), DENSE_RANK(), ROW_NUMBER(), and NTILE().

Sorting Functions in SQL

Let's now explore sorting functions in SQL:

RANGE()

• Assigns a unique rank number to each distinct row within a partition.
• Rows with equal values ​​are given the same rank, with gaps in the sorting sequence.
• Example: If two rows share the same rank of 1, the next assigned rank will be 3.

DENSE RANGE()

• Similar to RANK()but without gaps in the sorting sequence.
• Rows with equal values ​​are given the same rank, but the next rank follows immediately.
• Example: If two rows share the same rank of 1, the next assigned rank will be 2.

ROW NUMBER()

• Assigns a unique sequential integer to each row within a partition.
• Each row is given a different rank, regardless of the column values.
• Useful for generating unique row IDs.

NTILE()

• Distributes rows into a specified number of groups of approximately equal size.
• Each row is assigned a group number from 1 to the specified number of groups.
• Useful for dividing data into quartiles or percentiles.

Practical examples

Below we will discuss some practical examples of the range function.

Data set

CREATE TABLE Employees (
    EmployeeID INT,
    Name VARCHAR(50),
    Department VARCHAR(50),
    Salary DECIMAL(10, 2)
);

INSERT INTO Employees (EmployeeID, Name, Department, Salary) VALUES
(1, 'John Doe', 'HR', 50000),
(2, 'Jane Smith', 'Finance', 60000),
(3, 'Sam Brown', 'Finance', 55000),
(4, 'Emily Davis', 'HR', 52000),
(5, 'Michael Johnson', 'IT', 75000),
(6, 'Sarah Wilson', 'IT', 72000);

Using RANK() to Rank Sales Reps

This function assigns a rank to each row within a partition of the result set. Rows with equal values ​​are ranked the same, with gaps in the rank numbers if there are ties.

SELECT 
    EmployeeID,
    Name,
    Department,
    Salary,
    RANK() OVER (ORDER BY Salary DESC) AS Rank
FROM Employees;

Production:

Using DENSE_RANK() to rank students based on their test scores

Similar to RANK()but with no spaces in the rank numbers. Rows with equal values ​​are given the same rank, and subsequent ranks are consecutive integers.

SELECT 
    EmployeeID,
    Name,
    Department,
    Salary,
    DENSE_RANK() OVER (ORDER BY Salary DESC) AS DenseRank
FROM Employees;

Production:

Using ROW_NUMBER() to assign unique identifiers

Assigns a unique sequential integer to the rows, starting from 1. There are no gaps, even if there are ties.

SELECT 
    EmployeeID,
    Name,
    Department,
    Salary,
    ROW_NUMBER() OVER (ORDER BY Salary DESC) AS RowNumber
FROM Employees;

Production:

Using NTILE() to divide employees into quartiles

Wearing NTILE() It is useful for statistical analysis and reporting when you need to segment data into quantifiable parts, making it easier to analyze and interpret distributions and trends.

SELECT 
    EmployeeID,
    Name,
    Department,
    Salary,
    NTILE(3) OVER (ORDER BY Salary DESC) AS Quartile
FROM Employees;

Production:

This splits the result set into 3 roughly equal parts based on the Salary in descending order. Each employee is assigned a Quartile Number that indicates your position within the salary distribution.

Advantages of sorting functions

• Simplifies complex classification and sorting tasks.
• Improves the ability to generate meaningful information from organized data.
• Reduces the need for manual sorting and sorting of data.
• Facilitates data segmentation and grouping.

Potential dangers

• Performance issues with large data sets due to sorting and partitioning.
• Misunderstanding the differences between RANK(), DENSE_RANK()and ROW_NUMBER() It may lead to incorrect results.
• Overhead associated with calculating ranges in real-time queries.

Better practices

• Use appropriate sorting functions based on the specific requirements of your query.
• Consider indexing columns used in sort functions to improve performance.
• Test and optimize queries with ranking functions on large data sets to ensure efficiency.

Conclusion

Ranking functions in SQL are a set of crucial tools that are applied to handle sorted data. No matter if you are sorting sales reps, test scores, or want to split data into quartiles, these functions help and provide more insights in an easier way. So, if you learn the differences between RANK(), DENSE_RANK(), ROW_NUMBER(), and NTILE() and apply the best practices, you will gain more control over ranking functions and be able to further boost your data and information analysis.

Read also: Top 10 SQL Projects for Data Analytics

Frequent questions