3 Essential SQL Advanced Concepts: Stored Procedures, Sequences, and Window Functions Vaishnavi Tech Talks

SQL Advanced Concepts: Stored Procedures, Sequences, and Window Functions

In the time since the occurrence of the changes, SQL (Structured Query Language) has needed a lot of development, so that various tools could be created for data storage and analysis.
Aside from the basic SQL operations that are SELECT, INSERT, UPDATE, and DELETE which represent the foundation of Relational Database Management Systems (RDBMS), there are some SQL Advanced Concepts that are even more innovative and functional.
These SQL advanced concepts bring an extra level of efficiency, optimization, and flexibility to the database automation procedures, thus magnifying the developers’ proficiency.
The article will cover three vital SQL advanced concepts: SQL Stored Procedures, SQL Sequences, and Window Functions in SQL.
Each of these SQL advanced concepts is the fundamental methodology in crafting a clean, high-performance, and well-optimized SQL search algorithm.
Mastery of SQL Advanced Concepts is important not only for developers to enhance their skills, but also for them to create optimized solutions.
Learning the SQL Advanced Concepts will give you better understanding of how to manage databases and how to execute your queries optimally. Such SQL Advanced Concepts are those that developers use to construct systems that are powerful and work efficiently.
The SQL Advanced Concepts are comprehended with a level of high differentiation of data and the skill of using such SQL advanced concepts will change your capability to manage and handle data and this will make you a more productive programmer at the same time.

1. SQL Stored Procedures

A Stored Procedure in SQL is a precompiled group of one or many SQL statements that can be executed on the database.
Mainly, stored procedures reside in the database and may be utilized by the customer or application whenever they are in demand.
The dominant advantage of using stored procedures is that they are capable of modular programming.
In other words, they can access complex operations in a single command. They also further handle security, performance, and reusability.

Key Characteristics of Stored Procedures:

Precompiled: Stored procedures have already been compiled and are stored in the database, so SQL engine need not parse and compile them again when they are executed.
Efficiency: As they are precompiled, stored procedures can be faster than dynamic SQL queries. SQL engine does not have to re-parse the query during the repeated execution of the same procedure.
Modularity: The stored procedure provides developers an opportunity to encapsulate their complex logic into a single procedure. This modularity results in the development of a clear and easily maintainable code.
Security: By the help of stored procedures, users can be restricted to only performing predefined operations. This can prevent direct access to very sensitive database tables and, consequently, SQL injection hazards can be reduced.

How Stored Procedures Work

Stored procedures are originally created by means of the SQL statements that are compiled, which then are saved in the database.
If the client or the application needs to access it, they can do so using a stored procedure name.
The server is responsible for executing the procedure.

This is a brief summary of the stored procedures:

Step 1: Create the Procedure – The stored procedure is created and stored in the database using the SQL CREATE PROCEDURE statement.
Step 2: Execute the Procedure – The procedure, the application and database client, is called with the help of the EXECUTE or CALL command.
Step 3: Return Results – The procedure can either return a result set, output values, or just carry out the necessary operations without returning anything.

A stored procedure can receive input parameters (parameters given by the calling program), output parameters (parameters designed to convey results to the calling program), or both.

Syntax of a Stored Procedure:

The syntax of a stored procedure is usually different for each RDBMS.
We have the main one such as MySQL, PostgreSQL, or SQL Server.
On the other hand, it’s a basic one for SQL Server, i.e.:

CREATE PROCEDURE GetEmployeeDetails

@EmployeeID INT

BEGIN

SELECT EmployeeName, JobTitle, Department

FROM Employees

WHERE EmployeeID = @EmployeeID;

END;

Now, GetUserDetails is to get information about an employee by an EmployeeID that is entered to the procedure. The procedure is executed this way:

EXEC GetEmployeeDetails @EmployeeID=101;

Benefits of Using Stored Procedures:

Performance: Being compiled, stored procedures outperform query reformation via dynamic SQL when it comes to speed.
Code Reusability: Since a stored procedure can be reused many times without having to type the same SQL statements again and again, it endeavours the developers to stick with it and improves maintainability and reduces redundancy.
Security: Coders can manage who can access the tables and give permission only to run specific procedures instead of having to give full access to the database.

Example Use Case for Stored Procedures:

If a business needs to create monthly reports for different departments, it may be inspired by the following idea. The generation of a stored procedure will address the need to automate the whole process by querying multiple tables, performing calculations, and generating the report in one go. So that it allows for the automation of the process and the consistency is maintained in the execution of the reports.

2. SQL Sequences

A Sequence in SQL is a thing that makes different numbers in order, and it often gets used for creating primary keys or producing unique identifiers in a table.
Sequences are of prime importance in maintaining data consistency while it is added to a row in a table that needs a unique value for each record.

Key Characteristics of Sequences:

Uniqueness: Sequences are used to generate unique sequence numbers, which ensures that no two rows in a table will have the same identifier (e.g., a unique ID for each new employee in an Employee table).
Independent of Tables: Sequences are different from auto-increment columns in the fact that they are not associated with a table. They are database elements on their own and they can be linked to different tables.
Customization: Sequences can be configured to start at a specific number of your choice, they can increment by a specified number that you specify, also they can even be reused by cycling from the beginning when the maximum number has been reached.

How Does an SQL Sequence Work?

An SQL Sequence is a feature of the Structured Query Language that is used for the generation of a sequence of numerical values.
Through functions such as NEXTVAL, CURRVAL, etc., the sequence of these numbers can be used to insert new data in various tables of databases.
Moreover, these numbers are arranged by running some of such coded sections which collect the new numbers using statements like UPDATE, INSERT INTO…SELECT WHERE NOT EXISTS, and so on further allowing for the same sequence to be assigned to all such data that are being entered.

Here’s how SQL sequences work step-by-step:

A sequence is made with unique characteristics, like the starting value, step used and whether it wraps around when it reaches the end or not.
The sequence starts counting from the given initial number, and the interval will separate by the numbers selected (e.g., 1, 10, etc.).
The sequence number is retrieved through the use of the NEXTVAL operation, which gives back the next number that is not already taken.
The sequence can also provide the last generated value using CURRVAL after NEXTVAL has been called.

Creating a Sequence:

How a sequence is created can differ between RDBMS, according to the syntax used the following example is the way of creating a proper sequence in PostgreSQL:

CREATE SEQUENCE employee_seq

START 1

INCREMENT BY 1;

This sequence begins with 1 and every new value gets its number by 1. You can get a value from the sequence in this way:

SELECT nextval(’employee_seq’);

Key Parameters:

sequence_name: The name of the sequence.
START WITH: The initial value to start making the sequence (e.g., 1).
INCREMENT BY: The value by which the sequence will be incremented each time (e.g., 1, 10, etc.).
MINVALUE: The lowest the sequence can go to (optional).
MAXVALUE: The highest the sequence can ever go to (optional).
CACHE: The number of sequence values to pre-allocate for faster access (optional).
CYCLE: Decides if the sequence should go back and start again after the maximum value is reached.

Benefits of Using Sequences:

Centralized Number Generation: The major point of using sequences is that the numbers are unique and they are always obtained in the exact same idea and place.
Flexibility: Sequences adapt to be able to meet the order which this issue of numbers might demand by creating more than one table that uses them, whereas Auto-Increment columns are not advisable on this front because of their static input value.
Concurrency: Sequences are dynamic and capable of handling parallel transactions. Besides, if they follow a particular format, they will output a unique figure that is not shared among users or applications.

Example Use Case for Sequences:

So, for instance, you have multiple systems that rely on the same central database, and you want a sequence to be used to ensure that a unique customer ID is generated on each separate system. Each new customer will have a unique identifier, regardless of which device processes the data.

3. Window Functions in SQL

Window Functions are a useful technique in SQL that permits users to find the results for specific rows or navigating rows that are related according to the specific one.
These functions are often used for analytical queries and operations that require the computation of a value based on a “window” or subset of rows.
Window functions are used together with the OVER() clause, which identifies the “window” of rows over which the function will perform.
In contrast to aggregate functions (like SUM() or AVG()), which combine rows into a single output, window functions act on each row separately but still include a set of rows in the calculation.

Key Types of Window Functions:

Ranking Functions: These functions give a rank to each row according to a specified order.ROW_NUMBER(): Assigns a unique number to each row, starting at 1.RANK(): Assigns ranks with intervals. If two rows have the same rank, the next row will have a rank that is incremented by the number of tied rows.DENSE_RANK(): Like RANK(), but no empty spaces between the ranks.
ROW_NUMBER(): Assigns a unique number to each row, from 1 to 1.
RANK(): Assigns ranks with gaps. If two rows share the same rank, the next row will have a rank that is increased by the number of tied rows.
DENSE_RANK(): Similar to RANK(), but without gaps in the ranks.
Aggregate functions: They aggregate the data from separate rows of a window and compute the result.SUM(), AVG(), MIN(), MAX(), COUNT().
Value Functions: These show values from other rows within the window.LEAD(): Holds the value of the next row.LAG(): Holds the value of the previous row.
LEAD(): Holds the value of the next row.
LAG(): Holds the value of the previous row.

Syntax for Window Functions:

Here is an example illustrating the concept of ROW_NUMBER() which is used to store a rank to these employees depending on the salaries in the table:

SELECT

EmployeeName,

Salary,

ROW_NUMBER() OVER (ORDER BY Salary DESC) AS Rank

FROM Employees;

Now, let’s take for instance the case of employees who are paid according to theirearned salaries according to which a track of their ranks is dedicated.

Benefits of Using Window Functions:

Enhanced Query Performance: Window functions enable queries to be processed more effectively compared to using subqueries or joins to execute analogous tasks.
Complicated Computations: The availability for them to do difficult calculations like cumulative amounts, rolling averages, and ranking all at once and without the need for multiple queries is one of their main advantages.
Analytical Power: Window functions are particularly efficient in business intelligence activities, analytics, and reporting scenarios, as they allow for the performance of quick calculations on large databases.

Example Use Case for Window Functions:

Suppose a company needs to calculate the total sales in a certain period of time, for it they want to run some subcontracts. Through the window function, the running total is calculated without the necessity of subquery formation: