sql operators clauses

sql operators clauses

SQL (Structured Query Language) uses various clauses to refine, filter, and manipulate data stored in relational databases. These clauses act as directives to structure queries efficiently. Below are the key SQL clauses with syntax and examples.

1. SELECT Clause

The SELECT clause is fundamental in SQL, used to retrieve data from a database. It specifies the columns to be displayed in the output.

Syntax:

SELECT column1, column2, ...  
FROM table_name;

Example:

Retrieve the names and ages of all employees from the employees table.

SELECT name, age  
FROM employees;

2. FROM Clause

The FROM clause indicates the table from which data will be fetched. It follows the SELECT clause.

Syntax:

SELECT column1, column2  
FROM table_name;

Example:

Retrieve all records from the products table.

SELECT *  
FROM products;

3. WHERE Clause

The WHERE clause filters records based on specific conditions.

Syntax:

SELECT column1, column2  
FROM table_name  
WHERE condition;

Example:

Fetch employees older than 30.

SELECT name, age  
FROM employees  
WHERE age > 30;

4. ORDER BY Clause

The ORDER BY clause arranges results in ascending or descending order.

Syntax:

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

Example:

Sort employees by salary in descending order.

SELECT name, salary  
FROM employees  
ORDER BY salary DESC;

5. GROUP BY Clause

The GROUP BY clause groups rows with identical values in specified columns. It is often used with aggregate functions.

Syntax:

SELECT column_name, aggregate_function(column_name)  
FROM table_name  
GROUP BY column_name;

Example:

Find the total sales per product category.

SELECT category, SUM(sales)  
FROM products  
GROUP BY category;

6. HAVING Clause

The HAVING clause filters grouped results, unlike WHERE, which filters individual rows.

Syntax:

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

Example:

Show categories where total sales exceed 10,000.

SELECT category, SUM(sales)  
FROM products  
GROUP BY category  
HAVING SUM(sales) > 10000;

7. JOIN Clause

The JOIN clause combines records from multiple tables based on a related column.

Syntax:

SELECT table1.column1, table2.column2  
FROM table1  
JOIN table2  
ON table1.common_column = table2.common_column;

Example:

Retrieve customer orders by joining customers and orders.

SELECT customers.name, orders.order_date  
FROM customers  
JOIN orders  
ON customers.customer_id = orders.customer_id;

8. LIMIT Clause

The LIMIT clause restricts the number of records returned.

Syntax:

SELECT column1, column2  
FROM table_name  
LIMIT number;

Example:

Fetch the first five employees.

SELECT *  
FROM employees  
LIMIT 5;

9. DISTINCT Clause

The DISTINCT clause removes duplicate records from the result set.

Syntax:

SELECT DISTINCT column_name  
FROM table_name;

Example:

Retrieve unique job titles from the employees table.

SELECT DISTINCT job_title  
FROM employees;

10. UNION Clause

The UNION clause combines results from multiple queries, removing duplicates.

Syntax:

SELECT column1 FROM table1  
UNION  
SELECT column1 FROM table2;

Example:

Combine customer lists from two regions.

SELECT name FROM customers_region1  
UNION  
SELECT name FROM customers_region2;

Conclusion

SQL clauses optimize data queries by filtering, sorting, grouping, and merging datasets efficiently. Understanding these clauses enhances database management skills, allowing for precise data retrieval and manipulation.

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