2. Selects All Column records from the Specified table:

         SELECT * FROM table_name ;
          

1. Selects the specified Column records from the Specified

         SELECT First_Name ,Last_Name  FROM Customer;
          

OutPut

2. Selects All Column records from the Specified table:

         SELECT * FROM Customer ;
          

OutPut

This Will Return Only unique value of The Specified Column Of The Table

                SELECT DISTINCT column_name  FROM Table_name;
              

Exmaple

                SELECT DISTINCT  Country  FROM Customer;
              

Syntax

  
            SELECT column1, column2, ...
            FROM table_name
            WHERE condition;
          

Example

Consider a table named Customers with the following data:

To select customers from the USA, you can use the following SQL query:

            SELECT * FROM Customers
            WHERE Country = 'USA';
          

Output

Syntax

  
            SELECT column1, column2, ...
            FROM table_name
            ORDER BY column1 [ASC|DESC], column2 [ASC|DESC], ...;
          

Example

Consider a table named Customers with the following data:

To select all customers and order them by their last names in ascending order, you can use the following SQL query:

            SELECT * FROM Customers
            ORDER BY Last_Name ASC;
          

Output

Syntax

  
      SELECT column1, column2, ...
      FROM table_name
      WHERE condition1 AND condition2 AND ...;
    

Example

Consider a table named Customers with the following data:

To select customers from the USA who are over 25 years old, you can use the following SQL query:

      SELECT * FROM Customers
      WHERE Country = 'USA' AND Age > 25;
    

Output

Syntax

  
            SELECT column1, column2, ...
            FROM table_name
            WHERE condition1 OR condition2 OR ...;
          

Example

Consider a table named Customers with the following data:

To select customers from either the USA or Canada, you can use the following SQL query:

            SELECT * FROM Customers
            WHERE Country = 'USA' OR Country = 'Canada';
          

Output

Syntax

  
          INSERT INTO table_name (column1, column2, ...)
          VALUES (value1, value2, ...);
        

Example

Consider a table named Customers with the following structure:

To insert a new customer into the Customers table, you can use the following SQL query:

          INSERT INTO Customers (First_Name, Last_Name, Country, Age)
          VALUES ('Emily', 'Jones', 'USA', 28);
        

Output

After executing the above query, the Customers table will have the following data:

Syntax

  
          SELECT column1, column2, ...
          FROM table_name
          WHERE column_name IS NULL;
        

Example

Consider a table named Customers with the following data:

To select customers who do not have an email address, you can use the following SQL query:

          SELECT * FROM Customers
          WHERE Email IS NULL;
        

Output

Syntax

  
          SELECT column1, aggregate_function(column2)
          FROM table_name
          WHERE condition
          GROUP BY column1;
        

Example

Consider a table named Orders with the following data:

To calculate the total amount spent by each customer, you can use the following SQL query:

          SELECT Customer_ID, SUM(Amount) AS Total_Spent
          FROM Orders
          GROUP BY Customer_ID;
        

Output

Syntax

  
          SELECT column1, aggregate_function(column2)
          FROM table_name
          GROUP BY column1
          HAVING condition;
        

Example

Consider a table named Orders with the following data:

To find customers who have spent more than $200 in total, you can use the following SQL query:

          SELECT Customer_ID, SUM(Amount) AS Total_Spent
          FROM Orders
          GROUP BY Customer_ID
          HAVING SUM(Amount) > 200;
        

Output

Types of Joins

• INNER JOIN: Returns records that have matching values in both tables.
• LEFT JOIN (or LEFT OUTER JOIN): Returns all records from the left table and the matched records from the right table. If there is no match, NULL values are returned for columns from the right table.
• RIGHT JOIN (or RIGHT OUTER JOIN): Returns all records from the right table and the matched records from the left table. If there is no match, NULL values are returned for columns from the left table.
• FULL JOIN (or FULL OUTER JOIN): Returns all records when there is a match in either left or right table records. If there is no match, NULL values are returned for non-matching columns from both tables.

INNER JOIN Example

Consider two tables: Customers and Orders.

To select all customers along with their orders, you can use the following SQL query with an INNER JOIN:

            SELECT Customers.First_Name, Customers.Last_Name, Orders.Product
            FROM Customers
            INNER JOIN Orders ON Customers.Customer_ID = Orders.Customer_ID;
          

Output

LEFT JOIN Example

To select all customers and their orders, including customers without orders, you can use the following SQL query with a LEFT JOIN:

            SELECT Customers.First_Name, Customers.Last_Name, Orders.Product
            FROM Customers
            LEFT JOIN Orders ON Customers.Customer_ID = Orders.Customer_ID;
          

Output

RIGHT JOIN Example

To select all orders and their corresponding customers, including orders without customers, you can use the following SQL query with a RIGHT JOIN:

          SELECT Customers.First_Name, Customers.Last_Name, Orders.Product
          FROM Customers
          RIGHT JOIN Orders ON Customers.Customer_ID = Orders.Customer_ID;
        

Output

FULL OUTER JOIN Example

To select all customers and all orders, including customers without orders and orders without customers, you can use the following SQL query with a FULL OUTER JOIN:

          SELECT Customers.First_Name, Customers.Last_Name, Orders.Product
          FROM Customers
          FULL OUTER JOIN Orders ON Customers.Customer_ID = Orders.Customer_ID;
        

Output

Common Aggregate Functions

• COUNT: Returns the number of rows that match a specified criterion.
• SUM: Returns the total sum of a numeric column.
• AVG: Returns the average value of a numeric column.
• MAX: Returns the maximum value in a set.
• MIN: Returns the minimum value in a set.

Example

Consider a table named Sales with the following data:

To find the total sales amount and the average quantity sold, you can use the following SQL query:

          SELECT SUM(Amount) AS Total_Sales, AVG(Quantity) AS Average_Quantity
          FROM Sales;
        

Output

In this example, the total sales amount is calculated as $550, and the average quantity sold is 1.75.

Syntax

              -- Aggregate Function Example
              SELECT AGGREGATE_FUNCTION(column_name)
              FROM table_name
              WHERE condition;
  
              -- Scalar Function Example
              SELECT SCALAR_FUNCTION(column_name)
              FROM table_name;
          

Example

Consider a table named Sales with the following data:

To calculate the total sales amount and the average quantity sold, you can use the following SQL query:

              SELECT SUM(Amount) AS Total_Sales, AVG(Quantity) AS Average_Quantity
              FROM Sales;
          

Output

In this example, the total sales amount is calculated as $550, and the average quantity sold is 1.75.

Syntax

            CREATE INDEX index_name
            ON table_name (column1, column2, ...);
        

Example

Consider a table named Employees with the following data:

To create an index on the Last Name column of the Employees table, you can use the following SQL query:

            CREATE INDEX idx_last_name
            ON Employees (Last_Name);
        

Output

After executing the above query, an index named idx_last_name will be created on the Last Name column, which can improve the performance of queries that filter or sort by this column.

Syntax

            CREATE TABLE table_name (
                column1 datatype constraint,
                column2 datatype constraint,
                ...
                CONSTRAINT constraint_name PRIMARY KEY (column_name),
                CONSTRAINT constraint_name FOREIGN KEY (column_name) REFERENCES other_table (column_name)
            );
        

Example

Consider a table named Orders that references a Customers table:

To create the Orders table with constraints, you can use the following SQL query:

            CREATE TABLE Orders (
                Order_ID INT PRIMARY KEY,
                Customer_ID INT,
                Order_Date DATE,
                Amount DECIMAL(10, 2),
                CONSTRAINT fk_customer
                FOREIGN KEY (Customer_ID) REFERENCES Customers(Customer_ID)
                ON DELETE CASCADE
            );
        

Output

In this example, the Order_ID is defined as the PRIMARY KEY, ensuring that each order is uniquely identifiable. The Customer_ID column is defined as a FOREIGN KEY, establishing a relationship with the Customers table. The ON DELETE CASCADE option ensures that if a customer is deleted, all their associated orders will also be deleted automatically.

Syntax

            BEGIN TRANSACTION;

            -- SQL operations (INSERT, UPDATE, DELETE)
            -- Example:
            INSERT INTO table_name (column1, column2) VALUES (value1, value2);

            COMMIT;  -- Save changes
            -- or
            ROLLBACK;  -- Undo changes if an error occurs
        

Example

Consider a banking application where you want to transfer funds from one account to another:

To transfer $200 from John Doe's account to Jane Smith's account, you can use the following SQL transaction:

            BEGIN TRANSACTION;

            UPDATE Accounts
            SET Balance = Balance - 200
            WHERE Account_ID = 1;

            UPDATE Accounts
            SET Balance = Balance + 200
            WHERE Account_ID = 2;

            COMMIT;  -- Save changes
        

Output

In this example, the transaction ensures that both updates (debit from John Doe's account and credit to Jane Smith's account) are executed together. If either update fails, you can issue a ROLLBACK command to undo any changes made during the transaction, keeping the account balances consistent.