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DELETE Query in SQL

DELETE Query in SQL
Adnene Mabrouk
Technical writer
SQL
29.05.2024
Reading time: 6 min

The DELETE SQL query is a fundamental command used to remove records from a database table. Proper use of DELETE ensures that unnecessary or outdated data is efficiently removed while maintaining the integrity and performance of the database.

Creating a database and its tables

First, let's create a small database named Company and a few tables to work with: departments, employees, customers, and orders.

-- Create the database Company
CREATE DATABASE Company;
USE Company;

DROP TABLE IF EXISTS orders;
DROP TABLE IF EXISTS customers;
DROP TABLE IF EXISTS employees;
DROP TABLE IF EXISTS departments;

-- Create the departments table
CREATE TABLE departments (
    department_id INTEGER PRIMARY KEY,
    department_name TEXT NOT NULL
);

-- Create the employees table
CREATE TABLE employees (
    employee_id INTEGER PRIMARY KEY,
    first_name TEXT NOT NULL,
    last_name TEXT NOT NULL,
    department_id INTEGER,
    hire_date DATE,
    FOREIGN KEY (department_id) REFERENCES departments(department_id)
);

-- Create the customers table
CREATE TABLE customers (
    customer_id INTEGER PRIMARY KEY,
    customer_name TEXT NOT NULL
);

-- Create the orders table
CREATE TABLE orders (
    order_id INTEGER PRIMARY KEY,
    order_date DATE NOT NULL,
    customer_id INTEGER,
    employee_id INTEGER,
    FOREIGN KEY (employee_id) REFERENCES employees(employee_id)
);

-- Insert data into departments
INSERT INTO departments (department_id, department_name) VALUES
(1, 'Sales'),
(2, 'Engineering'),
(3, 'HR'),
(4, 'Obsolete');

-- Insert data into employees
INSERT INTO employees (employee_id, first_name, last_name, department_id, hire_date) VALUES
(101, 'John', 'Doe', 1, '2019-06-15'),
(102, 'Jane', 'Smith', 2, '2020-01-20'),
(103, 'Emily', 'Jones', 1, '2018-11-03'),
(104, 'Michael', 'Brown', 4, '2017-05-12');

-- Insert data into customers
INSERT INTO customers (customer_id, customer_name) VALUES
(1, 'Alice Johnson'),
(2, 'Bob Davis');

-- Insert data into orders
INSERT INTO orders (order_id, order_date, customer_id, employee_id) VALUES
(1001, '2023-01-10', 1, 101),
(1002, '2023-02-15', 2, 102),
(1003, '2023-03-20', 1, 103);

After creating and populating the tables, the data is as follows:

Departments:

Image1

Employees:

Image3

Customers:

Image2

Orders:

Image5

The examples below always start with these tables with their original data. 

Syntax of the DELETE Query

The DELETE query syntax is straightforward. The basic structure is:

DELETE FROM <table_name>
WHERE <condition>;
  • table_name: Specifies the table from which the records are to be deleted.

  • condition: Defines which records should be erased. If no condition is provided, all records from the table will be deleted (use with caution).

Deleting Data from a Single Table

  • Delete all records from customers

DELETE FROM customers;

Result :

Image4

  • Delete a specific record from employees

DELETE FROM employees WHERE employee_id = 101;

Result:

Image7

  •  Delete based on multiple conditions

DELETE FROM employees WHERE department_id = 2 AND hire_date < '2020-01-01';

Result:

Image6

Deleting Data from Multiple Tables

  •  Deleting using JOIN

DELETE e, d
FROM employees e
JOIN departments d ON e.department_id = d.department_id
WHERE d.department_name = 'Obsolete';

Result:

Image9

Cascading Deletes

Cascading deletes automatically remove related records in other tables. This is typically defined through foreign key constraints.

  • Setting up cascading deletes

ALTER TABLE orders
ADD CONSTRAINT fk_employee
FOREIGN KEY (employee_id) REFERENCES employees(employee_id)
ON DELETE CASCADE;

Now, if we delete an employee, their associated orders will also be deleted.

DELETE FROM employees WHERE employee_id = 101;

Result:

Image8

Best Practices for Deleting Data

  • Always Back Up Data: Before performing delete operations, ensure you have a recent backup.

  • Use Transactions: Encapsulate delete operations in transactions to allow rollback in case of errors.

  • Limit Deletes: Use conditions to limit the scope of deletion and avoid deleting unintended data.

  • Log Deletions: Maintain a log of deleted records for auditing and recovery purposes.

  • Test Queries: Test delete queries on a small dataset or development environment before executing on production.

Transaction Management

Transactions ensure that a series of SQL statements are executed as a single unit. If any part of the transaction fails, the entire transaction can be rolled back.

Using Transactions

START TRANSACTION;
DELETE FROM employees WHERE employee_id = 101;
DELETE FROM orders WHERE employee_idd = 101;
COMMIT;

If any delete operation fails, the transaction can be rolled back to maintain data integrity.

Error Handling

Handling errors effectively ensures database integrity and application stability.

Common Errors:

  • Foreign Key Constraint Violations: Occurs when trying to delete a record referenced by another table without cascading deletes.

  • Syntax Errors: Incorrect SQL syntax can cause the DELETE query to fail.

  • Permission Issues: Lack of appropriate permissions can prevent deletions.

Handling Errors in SQL queries

-- Start a transaction
START TRANSACTION;

-- Declare a handler for any errors
DECLARE EXIT HANDLER FOR SQLEXCEPTION
BEGIN
    -- Rollback the transaction if an error occurs
    ROLLBACK;
    -- Optionally, you can log the error or take other actions here
    SELECT 'An error occurred, transaction rolled back' AS error_message;
END;

-- Perform delete operations
DELETE FROM employees WHERE employee_id = 101;

-- Introduce an error deliberately, e.g., by deleting from a non-existent table
DELETE FROM non_existent_table WHERE id = 1;

-- If no errors occur, commit the transaction
COMMIT;

-- If errors occur, the ROLLBACK in the handler will be executed

When you execute the above script, the transaction will be rolled back due to the deliberate error, and the output will indicate that an error occurred and the transaction was rolled back. This ensures the database remains in a consistent state, and no partial changes are committed. Here is the status of the employees table:

Image3

This approach provides a robust way to handle errors during transactions, ensuring data integrity and allowing you to take appropriate actions when an error occurs.

Conclusion

The DELETE SQL query is a powerful tool for managing data within a database. Proper understanding and careful use of DELETE, along with best practices and transaction management, ensure data integrity and optimal database performance. Always perform deletions with caution and consider the implications of removing data from your database.

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SQL
29.05.2024
Reading time: 6 min

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SQL Constraints

When working with SQL tables, you'll often need to set constraints on the data types stored in a specific table. For instance, if you have a table with employee data, it's logical that some fields should not contain null values. You can apply such a constraint to the SQL values with a simple command. You can also require that entered values be unique or that data be checked against certain conditions. In this article, we'll look at how to do this and cover all possible types of constraints, but first, let's start with some terminology. What Are SQL Constraints? An SQL constraint is a rule that we apply to fields in SQL, determining which values are allowed and which are not. After adding a constraint, the program will check whether it's possible to insert, update, or delete data in the table based on the user-defined constraints. If not, the operation will not be executed, and the program will return an error. 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13 December 2024 · 6 min to read
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How to Select Data in SQL

In the modern world, where information is becoming an increasingly valuable resource, databases (DBs) remain an integral part of any information system, and the ability to retrieve data from them with maximum efficiency becomes a decisive factor in successfully working with these systems. SQL (Structured Query Language) is a specialized programming language for managing records stored in relational databases. Within SQL, there are many operators and methods that allow developers to retrieve the required information from a DB. This article is a practical guide for those who want to learn how to select data from an SQL table. In this guide, we will explore the syntax of the SELECT statement, learn how to filter data using WHERE, and examine how to aggregate data using GROUP BY and HAVING. Basics of the SELECT Statement SQL, being an incredibly flexible language for managing data, offers many tools for working with information stored in databases. 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Conditions defined in HAVING apply to already formed data groups, allowing for more detailed analysis. The GROUP BY and HAVING operators are essential tools for data aggregation in SQL.  Their use provides extensive data analysis capabilities, allowing statistical data collection and the identification of patterns, trends, and relationships within the data. Using JOIN to Combine Tables Often, developers need to select data from two SQL tables. To accomplish this, the JOIN operator is used, allowing data from two or more sources to be combined based on matching values in specific columns. Tables in a database usually have linking columns that correlate with keys in other tables, thus enabling the linking of data. This allows for automatic synchronization of changes across related tables, which is an invaluable advantage when working with large databases where information is split across multiple tables. The structure of a query using JOIN looks like this: SELECT dataField(s)FROM tableAJOIN tableBON tableA.dataField = tableB.dataField; In this case, JOIN is used to combine two tables (tableA and tableB). The join is performed based on a common column (dataField). Additionally, the query includes the selection of specific columns (dataField(s)) that the developer wants to display in the final result. It is important to note that in SQL, there are different types of table joins, including: INNER JOIN: This allows us to retrieve only those rows that have matching records in both tables, meaning where the join condition is met: SELECT Purchases.PurchaseID, Clients.ClientNameFROM PurchasesINNER JOIN ClientsON Purchases.ClientID = Clients.ClientID; LEFT (OUTER) JOIN: This is used when we need to retrieve all rows from the left table (the one specified first in the query), and the matching rows from the right table. If there are no matching rows in the right table, the results for those rows will contain NULL values: SELECT Clients.ClientName, Purchases.PurchaseIDFROM ClientsLEFT JOIN PurchasesON Clients.ClientID = Purchases.ClientID; RIGHT (OUTER) JOIN: This works similarly to the LEFT JOIN, but in reverse. Here, we get all the records from the right table, supplemented with matching data from the left table. If no matches are found for records from the right table, NULL will be placed in the columns for the left table: SELECT Clients.ClientName, Purchases.PurchaseIDFROM ClientsRIGHT JOIN PurchasesON Clients.ClientID = Purchases.ClientID; FULL (OUTER) JOIN: This type of join gives us all rows from both tables that have corresponding records. In other words, it combines the LEFT and RIGHT JOINs. If there are rows in the first table with no matching rows in the second table, the columns from the second table will contain NULL for those rows. Similarly, if records from the second table do not have matches in the first table, the columns from the first table will contain NULL for those rows: SELECT Clients.ClientName, Purchases.PurchaseIDFROM ClientsFULL OUTER JOIN PurchasesON Clients.ClientID = Purchases.ClientID; It is worth noting that although the FULL (OUTER) JOIN is a standard SQL feature, not all SQL systems support it. For example, MySQL does not have built-in support for FULL (OUTER) JOIN, but you can emulate it using a combination of LEFT JOIN and UNION: SELECT Clients.ClientName, Purchases.PurchaseID FROM Clients LEFT JOIN Purchases ON Clients.ClientID = Purchases.ClientID UNION SELECT Clients.ClientName, Purchases.PurchaseID FROM Purchases LEFT JOIN Clients ON Clients.ClientID = Purchases.ClientID WHERE Clients.ClientID IS NULL; This query first performs a left outer join, attaching records from the Purchases table to the Clients table. Then, it joins records from Clients to Purchases that were not selected in the first query (i.e., those where ClientID is NULL). Finally, it combines the results of these two queries. In this section, we discussed different types of JOIN in SQL. Each of these joins provides flexibility in managing which data from related tables we want to see in the result set. Conclusion In this guide, we explored the use of SQL operators such as SELECT, WHERE, ORDER BY, JOIN, GROUP BY, and HAVING through practical examples. These operators offer users extensive capabilities for processing information, enabling complex analytical queries and extracting maximum value from stored data. We hope that you now have a clear understanding of how to use SQL to extract data from a database!
13 December 2024 · 12 min to read
SQL

How to Insert Data into SQL Databases

The data insertion operation in relational databases is one of the most essential tasks. In this article, we will explain how to perform this operation using relational database management systems (DBMS) that work with the SQL language. We will use MySQL, the most popular SQL-based DBMS. As an example, we will consider two tables: one for leading European football clubs (including their national affiliation, year of establishment, number of national championships won, domestic cups, and European trophies), and another for some leading countries worldwide (with their capitals and population in millions). Initially, the tables (let's call them Clubs and Countries) will be empty, containing only column names. Our task is to populate them using various SQL commands so that they appear as follows: Club Country Year Champs Cups Eurocups Real Madrid Spain 1902 35 19 21 Barcelona Spain 1899 26 31 18 Milan Italy 1899 19 5 14 Juventus Italy 1897 36 14 8 Bavaria Germany 1900 32 20 10 The Countries table: Country Capital Population Russia Moscow 147 USA Washington 336 China Beijing 1427 India Delhi 1435 Brazil Brasilia 218 So, first, we need to create a database and two tables.  Connect to the MySQL server (replace xxx.xxx.xxx.xxx with the appropriate IP address): mysql -u root -h xxx.xxx.xxx.xxx -p Then enter the following command: CREATE DATABASE TestDB; To verify that the new database has been successfully created, use the command: SHOW DATABASES; Our database, TestDB, should appear in the list. Next, we need to grant users access to this database. For example, if we already have a user test_user, we can grant them access using the command: GRANT ALL PRIVILEGES ON TestDB.* TO 'test_user'@'%' WITH GRANT OPTION; Now, we can proceed to create the tables. Let’s start with the table for clubs: CREATE TABLE Clubs ( Club VARCHAR(64) NOT NULL, Country VARCHAR(32), Year INT, Champs INT, Cups INT, Eurocups INT ); This means that for the first two columns, we specified string values, with the length of the data in each cell not exceeding 64 and 32 characters, respectively. Additionally, cells in the Club column cannot be empty when adding data (NOT NULL). For the remaining four columns, we designated integer values (INT). Now, following the same pattern, we create the second table: CREATE TABLE Countries ( Country VARCHAR(32) NOT NULL, Capital VARCHAR(32), Population INT ); That’s it! Our tables are created and ready to be populated. The INSERT INTO Statement The INSERT INTO statement allows you to insert data into an SQL table. However, the data is inserted in the column order, so you must know the exact sequence of columns in the table. Let’s insert data into the first rows of our tables: INSERT INTO Clubs VALUES("Real Madrid", "Spain", 1902, 35, 19, 21); INSERT INTO Countries VALUES("Russia", "Moscow", 147); Note that we must specify values for all columns. For instance, the following entries would result in errors or misaligned values (e.g., we omitted the club’s founding year and the country’s capital): INSERT INTO Clubs VALUES("Real Madrid", "Spain", 35, 19, 21); INSERT INTO Countries VALUES("Russia", 147); The INSERT INTO Statement with Column List This method is more reliable as it prevents errors when skipping columns. However, you must specify the column names explicitly: INSERT INTO Clubs(Club, Country, Champs, Cups, Eurocups) VALUES("Barcelona", "Spain", 26, 31, 18); INSERT INTO Countries(Country, Capital) VALUES("USA", "Washington"); In these examples, we skipped the club's founding year (the Year column) in the first case and the population (the Population column) in the second. No errors occur because these fields simply remain empty and can be filled later. The INSERT INTO Statement for Bulk Insertion Adding data row by row is not always convenient. Therefore, let’s look at how to insert data into multiple rows simultaneously. We can do it with the following command: INSERT INTO Clubs(Club, Country, Eurocups) VALUES ("Real Madrid", "Spain", 21), ("Barcelona", "Spain", 18), ("Milan", "Italy", 14), ("Juventus", "Italy", 8), ("Bavaria", "Germany", 10); INSERT INTO Countries(Country, Population) VALUES ("Russia", 147), ("USA", 336), ("China", 1427), ("India", 1435), ("Brazil", 218); In the first table, we populated the columns with the names of the clubs, their national affiliation, and the number of European trophies won, leaving the remaining columns empty. In the second table, we omitted the countries' capitals.  As we can see, there are some syntax differences, and the commands are split across multiple lines. The SET Statement In combination with INSERT INTO, the SET statement allows you to insert a single record into a table: INSERT INTO Clubs SET Club="Milan", Country="Italy", Year=1899, Champs=19, Cups=5, Eurocups=14; INSERT INTO Countries SET Country="China", Capital="Beijing", Population=1427; However, this is also its drawback, as it does not allow us to insert multiple records into an SQL table at once. For that purpose, the previous method is more suitable. How to Insert Data from Another SQL Table Suppose we have other tables with the same columns, and we want to add their data to our tables. This can be done using the SELECT statement in combination with the familiar INSERT: INSERT INTO Clubs(Club, Country, Year, Champs, Cups, Eurocups) SELECT Club, Country, Year, Champs, Cups, Eurocups FROM Clubs2; INSERT INTO Countries(Country, Capital, Population) SELECT Country, Capital, Population FROM Countries2; The IGNORE Clause for Avoiding Errors We can use the IGNORE clause to prevent MySQL from halting when trying to insert invalid values. For example, if we set a uniqueness constraint on the Club column to ensure that each club name is unique, the clause helps avoid interruptions. In MySQL, the first value in a table is always treated as unique, so manually adding such a constraint may not be necessary. For instance, if we already have a row like this: Real Madrid Spain 1902 35 19 21 This command will result in an error: INSERT INTO Clubs VALUES("Real Madrid", "Spain", 1902, 35, 19, 21); We already have a row with the value Real Madrid in the first column. However, duplicates are likely to occur when copying data from multiple tables. To ensure the program ignores these duplicates without generating errors, we use the IGNORE clause: INSERT IGNORE Clubs(Club, Country, Year, Champs, Cups, Eurocups) VALUES("Real Madrid", "Spain", 1902, 35, 19, 21); The same is true for the second example. We already have the line:  Russia Moscow 147 Running this query: INSERT INTO Countries VALUES("Russia", "Moscow", 147); — will result in an error. That’s why we should use IGNORE: INSERT IGNORE Countries(Country, Capital, Population) VALUES("Russia", "Moscow", 147); The program will simply ignore the duplicate row and continue execution without throwing an error. The LOAD DATA Statement for Importing from a Text File Suppose we have an empty Clubs table with the appropriate columns, and we need to populate it with information from a text file. The LOAD DATA statement allows us to do this. However, you first need to prepare the text file with the data. Open your file (let's say Clubs.txt) in a text editor and format the data as follows, separating values with a tab character: 'Real Madrid' 'Spain' '1902' '35' '19' '21' 'Barcelona' 'Spain' '1899' '26' '31' '18' 'Milan' 'Italy' '1899' '19' '5' '14' 'Juventus' 'Italy' '1897' '36' '14' '8' 'Bavaria' 'Germany' '1900' '32' '20' '10' This SQL query will insert data in the table, placing them in the right columns. But what if we don’t have values for specific columns? Suppose we don’t know when the clubs were established. The record will look like this: 'Real Madrid' 'Spain' '\N' '35' '19' '21' 'Barcelona' 'Spain' '\N' '26' '31' '18' 'Milan' 'Italy' '\N' '19' '5' '14' 'Juventus' 'Italy' '\N' '36' '14' '8' 'Bavaria' 'Germany' '\N' '32' '20' '10' \N means that the cell in the table will remain empty. Now, we just need to load the data into SQL, but first, let's enable working with local files like this: set global local_infile=true; exit mysql --local_infile=1 -u test_user -h xxx.xxx.xxx.xxx -p The Linux command to load data is: LOAD DATA LOCAL INFILE '/your_directory/Clubs.txt' INTO TABLE Clubs; And in Windows, it is done like this: LOAD DATA LOCAL INFILE '/your_directory/Clubs.txt'' INTO TABLE Clubs LINES TERMINATED BY '\r\n'; However, sometimes the system might not respond to these instructions. In that case, you will need to enable working with local files in MySQL, which is explained in detail in the official documentation. To summarize, the value of unsigned int in the MYSQL_OPT_LOCAL_INFILE option, related to the mysql_options() settings, must be non-zero. That’s all for now! Now you know how to insert data into SQL databases using various statements. Just choose the most appropriate statement for the specific case, and you’ll avoid issues when copying data.
12 December 2024 · 8 min to read

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