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SET Operations in SQL

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SQL supports few Set operations which can be performed on the table data. These are used to get meaningful results from data stored in the table, under different special conditions.

In this tutorial, we will cover 4 different types of SET operations, along with example:

UNION
UNION ALL
INTERSECT
MINUS

UNION Operation

UNION is used to combine the results of two or more SELECT statements. However it will eliminate duplicate rows from its resultset. In case of union, number of columns and datatype must be same in both the tables, on which UNION operation is being applied.

Example of UNION

The First table,

ID	Name
1	abhi
2	adam

The Second table,

ID	Name
2	adam
3	Chester

Union SQL query will be,

SELECT * FROM First 
UNION
SELECT * FROM Second;

The resultset table will look like,

ID	NAME
1	abhi
2	adam
3	Chester

UNION ALL

This operation is similar to Union. But it also shows the duplicate rows.

Example of Union All

The First table,

ID	NAME
1	abhi
2	adam

The Second table,

ID	NAME
2	adam
3	Chester

Union All query will be like,

SELECT * FROM First 
UNION ALL
SELECT * FROM Second;

The resultset table will look like,

ID	NAME
1	abhi
2	adam
2	adam
3	Chester

INTERSECT

Intersect operation is used to combine two SELECT statements, but it only retuns the records which are common from both SELECT statements. In case of Intersect the number of columns and datatype must be same.

NOTE: MySQL does not support INTERSECT operator.

Example of Intersect

The First table,

ID	NAME
1	abhi
2	adam

The Second table,

ID	NAME
2	adam
3	Chester

Intersect query will be,

SELECT * FROM First 
INTERSECT
SELECT * FROM Second;

The resultset table will look like

ID	NAME
2	adam

MINUS

The Minus operation combines results of two SELECT statements and return only those in the final result, which belongs to the first set of the result.

Example of Minus

The First table,

ID	NAME
1	abhi
2	adam

The Second table,

ID	NAME
2	adam
3	Chester

Minus query will be,

SELECT * FROM First 
MINUS
SELECT * FROM Second;

The resultset table will look like,

ID	NAME
1	abhi

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SQL Alias – `AS` Keyword

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Alias is used to give an alias name to a table or a column, which can be a resultset table too. This is quite useful in case of large or complex queries. Alias is mainly used for giving a short alias name for a column or a table with complex names.

Syntax of Alias for table names,

SELECT column-name FROM table-name AS alias-name

Following is an SQL query using alias,

SELECT * FROM Employee_detail AS ed;

Syntax for defining alias for columns will be like,

SELECT column-name AS alias-name FROM table-name;

Example using alias for columns,

SELECT customer_id AS cid FROM Emp;

Example of Alias in SQL Query

Consider the following two tables,

The class table,

ID	Name
1	abhi
2	adam
3	alex
4	anu
5	ashish

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI
7	NOIDA
8	PANIPAT

Below is the Query to fetch data from both the tables using SQL Alias,

SELECT C.id, C.Name, Ci.Address from Class AS C, Class_info AS Ci where C.id = Ci.id;

and the resultset table will look like,

ID	Name	Address
1	abhi	DELHI
2	adam	MUMBAI
3	alex	CHENNAI

SQL Alias seems to be quite a simple feature of SQL, but it is highly useful when you are working with more than 3 tables and have to use JOIN on them.

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SQL JOIN

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SQL Join is used to fetch data from two or more tables, which is joined to appear as single set of data. It is used for combining column from two or more tables by using values common to both tables.

JOIN Keyword is used in SQL queries for joining two or more tables. Minimum required condition for joining table, is (n-1) where n, is number of tables. A table can also join to itself, which is known as, Self Join.

Types of JOIN

Following are the types of JOIN that we can use in SQL:

Inner
Outer
Left
Right

Cross JOIN or Cartesian Product

This type of JOIN returns the cartesian product of rows from the tables in Join. It will return a table which consists of records which combines each row from the first table with each row of the second table.

Cross JOIN Syntax is,

SELECT column-name-list
FROM 
table-name1 CROSS JOIN table-name2;

Example of Cross JOIN

Following is the class table,

ID	NAME
1	abhi
2	adam
4	alex

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI

Cross JOIN query will be,

SELECT * FROM 
class CROSS JOIN class_info;

The resultset table will look like,

ID	NAME	ID	Address
1	abhi	1	DELHI
2	adam	1	DELHI
4	alex	1	DELHI
1	abhi	2	MUMBAI
2	adam	2	MUMBAI
4	alex	2	MUMBAI
1	abhi	3	CHENNAI
2	adam	3	CHENNAI
4	alex	3	CHENNAI

As you can see, this join returns the cross product of all the records present in both the tables.

INNER Join or EQUI Join

This is a simple JOIN in which the result is based on matched data as per the equality condition specified in the SQL query.

Inner Join Syntax is,

SELECT column-name-list FROM 
table-name1 INNER JOIN table-name2 
WHERE table-name1.column-name = table-name2.column-name;

Example of INNER JOIN

Consider a class table,

ID	NAME
1	abhi
2	adam
3	alex
4	anu

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI

Inner JOIN query will be,

SELECT * from class INNER JOIN class_info where class.id = class_info.id;

The resultset table will look like,

ID	NAME	ID	Address
1	abhi	1	DELHI
2	adam	2	MUMBAI
3	alex	3	CHENNAI

Natural JOIN

Natural Join is a type of Inner join which is based on column having same name and same datatype present in both the tables to be joined.

The syntax for Natural Join is,

SELECT * FROM 
table-name1 NATURAL JOIN table-name2;

Example of Natural JOIN

Here is the class table,

ID	NAME
1	abhi
2	adam
3	alex
4	anu

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI

Natural join query will be,

SELECT * from class NATURAL JOIN class_info;

The resultset table will look like,

ID	NAME	Address
1	abhi	DELHI
2	adam	MUMBAI
3	alex	CHENNAI

In the above example, both the tables being joined have ID column(same name and same datatype), hence the records for which value of ID matches in both the tables will be the result of Natural Join of these two tables.

OUTER JOIN

Outer Join is based on both matched and unmatched data. Outer Joins subdivide further into,

Left Outer Join
Right Outer Join
Full Outer Join

LEFT Outer Join

The left outer join returns a resultset table with the matched data from the two tables and then the remaining rows of the left table and null from the right table’s columns.

Syntax for Left Outer Join is,

SELECT column-name-list FROM 
table-name1 LEFT OUTER JOIN table-name2
ON table-name1.column-name = table-name2.column-name;

To specify a condition, we use the ON keyword with Outer Join.

Left outer Join Syntax for Oracle is,

SELECT column-name-list FROM 
table-name1, table-name2 on table-name1.column-name = table-name2.column-name(+);

Example of Left Outer Join

Here is the class table,

ID	NAME
1	abhi
2	adam
3	alex
4	anu
5	ashish

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI
7	NOIDA
8	PANIPAT

Left Outer Join query will be,

SELECT * FROM class LEFT OUTER JOIN class_info ON (class.id = class_info.id);

The resultset table will look like,

ID	NAME	ID	Address
1	abhi	1	DELHI
2	adam	2	MUMBAI
3	alex	3	CHENNAI
4	anu	null	null
5	ashish	null	null

RIGHT Outer Join

The right outer join returns a resultset table with the matched data from the two tables being joined, then the remaining rows of the right table and null for the remaining left table’s columns.

Syntax for Right Outer Join is,

SELECT column-name-list FROM 
table-name1 RIGHT OUTER JOIN table-name2 
ON table-name1.column-name = table-name2.column-name;

Right outer Join Syntax for Oracle is,

SELECT column-name-list FROM 
table-name1, table-name2 
ON table-name1.column-name(+) = table-name2.column-name;

Example of Right Outer Join

Once again the class table,

ID	NAME
1	abhi
2	adam
3	alex
4	anu
5	ashish

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI
7	NOIDA
8	PANIPAT

Right Outer Join query will be,

SELECT * FROM class RIGHT OUTER JOIN class_info ON (class.id = class_info.id);

The resultant table will look like,

ID	NAME	ID	Address
1	abhi	1	DELHI
2	adam	2	MUMBAI
3	alex	3	CHENNAI
null	null	7	NOIDA
null	null	8	PANIPAT

Full Outer Join

The full outer join returns a resultset table with the matched data of two table then remaining rows of both left table and then the right table.

Syntax of Full Outer Join is,

SELECT column-name-list FROM 
table-name1 FULL OUTER JOIN table-name2
ON table-name1.column-name = table-name2.column-name;

Example of Full outer join is,

The class table,

ID	NAME
1	abhi
2	adam
3	alex
4	anu
5	ashish

and the class_info table,

ID	Address
1	DELHI
2	MUMBAI
3	CHENNAI
7	NOIDA
8	PANIPAT

Full Outer Join query will be like,

SELECT * FROM class FULL OUTER JOIN class_info ON (class.id = class_info.id);

The resultset table will look like,

ID	NAME	ID	Address
1	abhi	1	DELHI
2	adam	2	MUMBAI
3	alex	3	CHENNAI
4	anu	null	null
5	ashish	null	null
null	null	7	NOIDA
null	null	8	PANIPAT

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SQL Constraints

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SQL Constraints are rules used to limit the type of data that can go into a table, to maintain the accuracy and integrity of the data inside table.

Constraints can be divided into the following two types,

Column level constraints: Limits only column data.
Table level constraints: Limits whole table data.

Constraints are used to make sure that the integrity of data is maintained in the database. Following are the most used constraints that can be applied to a table.

NOT NULL
UNIQUE
PRIMARY KEY
FOREIGN KEY
CHECK
DEFAULT

`NOT NULL` Constraint

NOT NULL constraint restricts a column from having a NULL value. Once NOT NULL constraint is applied to a column, you cannot pass a null value to that column. It enforces a column to contain a proper value.

One important point to note about this constraint is that it cannot be defined at table level.

Example using `NOT NULL` constraint

CREATE TABLE Student(s_id int NOT NULL, Name varchar(60), Age int);

The above query will declare that the s_id field of Student table will not take NULL value.

`UNIQUE` Constraint

UNIQUE constraint ensures that a field or column will only have unique values. A UNIQUE constraint field will not have duplicate data. This constraint can be applied at column level or table level.

Using `UNIQUE` constraint when creating a Table (Table Level)

Here we have a simple CREATE query to create a table, which will have a column s_id with unique values.

CREATE TABLE Student(s_id int NOT NULL UNIQUE, Name varchar(60), Age int);

The above query will declare that the s_id field of Student table will only have unique values and wont take NULL value.

Using `UNIQUE` constraint after Table is created (Column Level)

ALTER TABLE Student ADD UNIQUE(s_id);

The above query specifies that s_id field of Student table will only have unique value.

Primary Key Constraint

Primary key constraint uniquely identifies each record in a database. A Primary Key must contain unique value and it must not contain null value. Usually Primary Key is used to index the data inside the table.

Using PRIMARY KEY constraint at Table Level

CREATE table Student (s_id int PRIMARY KEY, Name varchar(60) NOT NULL, Age int);

The above command will creates a PRIMARY KEY on the s_id.

Using PRIMARY KEY constraint at Column Level

ALTER table Student ADD PRIMARY KEY (s_id);

The above command will creates a PRIMARY KEY on the s_id.

Foreign Key Constraint

FOREIGN KEY is used to relate two tables. FOREIGN KEY constraint is also used to restrict actions that would destroy links between tables. To understand FOREIGN KEY, let’s see its use, with help of the below tables:

Customer_Detail Table

c_id	Customer_Name	address
101	Adam	Noida
102	Alex	Delhi
103	Stuart	Rohtak

Order_Detail Table

Order_id	Order_Name	c_id
10	Order1	101
11	Order2	103
12	Order3	102

In Customer_Detail table, c_id is the primary key which is set as foreign key in Order_Detail table. The value that is entered in c_id which is set as foreign key in Order_Detail table must be present in Customer_Detail table where it is set as primary key. This prevents invalid data to be inserted into c_id column of Order_Detail table.

If you try to insert any incorrect data, DBMS will return error and will not allow you to insert the data.

Using FOREIGN KEY constraint at Table Level

CREATE table Order_Detail(
    order_id int PRIMARY KEY, 
    order_name varchar(60) NOT NULL,
    c_id int FOREIGN KEY REFERENCES Customer_Detail(c_id)
);

In this query, c_id in table Order_Detail is made as foriegn key, which is a reference of c_id column in Customer_Detail table.

Using FOREIGN KEY constraint at Column Level

ALTER table Order_Detail ADD FOREIGN KEY (c_id) REFERENCES Customer_Detail(c_id);

Behaviour of Foriegn Key Column on Delete

There are two ways to maintin the integrity of data in Child table, when a particular record is deleted in the main table. When two tables are connected with Foriegn key, and certain data in the main table is deleted, for which a record exits in the child table, then we must have some mechanism to save the integrity of data in the child table.

foriegn key behaviour on delete - cascade and Null

On Delete Cascade : This will remove the record from child table, if that value of foriegn key is deleted from the main table.
On Delete Null : This will set all the values in that record of child table as NULL, for which the value of foriegn key is deleted from the main table.
If we don’t use any of the above, then we cannot delete data from the main table for which data in child table exists. We will get an error if we try to do so.

`CHECK` Constraint

CHECK constraint is used to restrict the value of a column between a range. It performs check on the values, before storing them into the database. Its like condition checking before saving data into a column.

Using `CHECK` constraint at Table Level

CREATE table Student(
    s_id int NOT NULL CHECK(s_id > 0),
    Name varchar(60) NOT NULL,
    Age int
);

The above query will restrict the s_id value to be greater than zero.

Using `CHECK` constraint at Column Level

ALTER table Student ADD CHECK(s_id > 0);

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`DISTINCT` keyword

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The distinct keyword is used with SELECT statement to retrieve unique values from the table. Distinct removes all the duplicate records while retrieving records from any table in the database.

Syntax for `DISTINCT` Keyword

SELECT DISTINCT column-name FROM table-name;

Example using `DISTINCT` Keyword

Consider the following Emp table. As you can see in the table below, there is employee name, along with employee salary and age.

In the table below, multiple employees have the same salary, so we will be using DISTINCT keyword to list down distinct salary amount, that is currently being paid to the employees.

eid	name	age	salary
401	Anu	22	5000
402	Shane	29	8000
403	Rohan	34	10000
404	Scott	44	10000
405	Tiger	35	8000

SELECT DISTINCT salary FROM Emp;

The above query will return only the unique salary from Emp table.

salary
5000
8000
10000

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SQL `HAVING` Clause

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Having clause is used with SQL Queries to give more precise condition for a statement. It is used to mention condition in Group by based SQL queries, just like WHERE clause is used with SELECT query.

Syntax for HAVING clause is,

SELECT column_name, function(column_name)
FROM table_name
WHERE column_name condition
GROUP BY column_name
HAVING function(column_name) condition

Example of SQL Statement using `HAVING`

Consider the following Sale table.

oid	order_name	previous_balance	customer
11	ord1	2000	Alex
12	ord2	1000	Adam
13	ord3	2000	Abhi
14	ord4	1000	Adam
15	ord5	2000	Alex

Suppose we want to find the customer whose previous_balance sum is more than 3000.

We will use the below SQL query,

SELECT *
FROM sale GROUP BY customer
HAVING sum(previous_balance) > 3000

Result will be,

oid	order_name	previous_balance	customer
11	ord1	2000	Alex

The main objective of the above SQL query was to find out the name of the customer who has had a previous_balance more than 3000, based on all the previous sales made to the customer, hence we get the first row in the table for customer Alex.

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SQL `Group By` Clause

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Group by clause is used to group the results of a SELECT query based on one or more columns. It is also used with SQL functions to group the result from one or more tables.

Syntax for using Group by in a statement.

SELECT column_name, function(column_name)
FROM table_name 
WHERE condition 
GROUP BY column_name

Example of `Group by` in a Statement

Consider the following Emp table.

eid	name	age	salary
401	Anu	22	9000
402	Shane	29	8000
403	Rohan	34	6000
404	Scott	44	9000
405	Tiger	35	8000

Here we want to find name and age of employees grouped by their salaries or in other words, we will be grouping employees based on their salaries, hence, as a result, we will get a data set, with unique salaries listed, along side the first employee’s name and age to have that salary. Hope you are getting the point here!

group by is used to group different row of data together based on any one column.

SQL query for the above requirement will be,

SELECT name, age 
FROM Emp GROUP BY salary

Result will be,

name	age
Rohan	34
Shane	29
Anu	22

Example of `Group by` in a Statement with `WHERE` clause

Consider the following Emp table

eid	name	age	salary
401	Anu	22	9000
402	Shane	29	8000
403	Rohan	34	6000
404	Scott	44	9000
405	Tiger	35	8000

SQL query will be,

SELECT name, salary 
FROM Emp 
WHERE age > 25
GROUP BY salary

Result will be.

name	salary
Rohan	6000
Shane	8000
Scott	9000

You must remember that Group By clause will always come at the end of the SQL query, just like the Order by clause.

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SQL `ORDER BY` Clause

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Order by clause is used with SELECT statement for arranging retrieved data in sorted order. The Order by clause by default sorts the retrieved data in ascending order. To sort the data in descending order DESC keyword is used with Order by clause.

Syntax of `Order By`

SELECT column-list|* FROM table-name ORDER BY ASC | DESC;

Using default `Order by`

Consider the following Emp table,

eid	name	age	salary
401	Anu	22	9000
402	Shane	29	8000
403	Rohan	34	6000
404	Scott	44	10000
405	Tiger	35	8000

SELECT * FROM Emp ORDER BY salary;

The above query will return the resultant data in ascending order of the salary.

eid	name	age	salary
403	Rohan	34	6000
402	Shane	29	8000
405	Tiger	35	8000
401	Anu	22	9000
404	Scott	44	10000

Using Order by `DESC`

Consider the Emp table described above,

SELECT * FROM Emp ORDER BY salary DESC;

The above query will return the resultant data in descending order of the salary.

eid	name	age	salary
404	Scott	44	10000
401	Anu	22	9000
405	Tiger	35	8000
402	Shane	29	8000
403	Rohan	34	6000

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SQL `LIKE` clause

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LIKE clause is used in the condition in SQL query with the WHERE clause. LIKE clause compares data with an expression using wildcard operators to match pattern given in the condition.

Wildcard operators

There are two wildcard operators that are used in LIKE clause.

Percent sign %: represents zero, one or more than one character.
Underscore sign _: represents only a single character.

Example of `LIKE` clause

Consider the following Student table.

s_id	s_Name	age
101	Adam	15
102	Alex	18
103	Abhi	17

SELECT * FROM Student WHERE s_name LIKE 'A%';

The above query will return all records where s_name starts with character ‘A’.

s_id	s_Name	age
101	Adam	15
102	Alex	18
103	Abhi	17

Using `_` and `%`

SELECT * FROM Student WHERE s_name LIKE '_d%';

The above query will return all records from Student table where s_name contain ‘d’ as second character.

s_id	s_Name	age
101	Adam	15

Using `%` only

SELECT * FROM Student WHERE s_name LIKE '%x';

The above query will return all records from Student table where s_name contain ‘x’ as last character.

s_id	s_Name	age
102	Alex	18

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Using the `WHERE` SQL clause

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WHERE clause is used to specify/apply any condition while retrieving, updating or deleting data from a table. This clause is used mostly with SELECT, UPDATE and DELETEquery.

When we specify a condition using the WHERE clause then the query executes only for those records for which the condition specified by the WHERE clause is true.

Syntax for `WHERE` clause

Here is how you can use the WHERE clause with a DELETE statement, or any other statement,

DELETE FROM table_name WHERE [condition];

The WHERE clause is used at the end of any SQL query, to specify a condition for execution.

Time for an Example

Consider a table student,

s_id	name	age	address
101	Adam	15	Chennai
102	Alex	18	Delhi
103	Abhi	17	Banglore
104	Ankit	22	Mumbai

Now we will use the SELECT statement to display data of the table, based on a condition, which we will add to our SELECT query using WHERE clause.

Let’s write a simple SQL query to display the record for student with s_id as 101.

SELECT s_id, 
    name, 
    age, 
    address 
    FROM student WHERE s_id = 101;

Following will be the result of the above query.

s_id	name	age	address
101	Adam	15	Noida

Applying condition on Text Fields

In the above example we have applied a condition to an integer value field, but what if we want to apply the condition on name field. In that case we must enclose the value in single quote ' '. Some databases even accept double quotes, but single quotes is accepted by all.

SELECT s_id, 
    name, 
    age, 
    address 
    FROM student WHERE name = 'Adam';

Following will be the result of the above query.

s_id	name	age	address
101	Adam	15	Noida

Operators for `WHERE` clause condition

Following is a list of operators that can be used while specifying the WHERE clause condition.

Operator	Description
`=`	Equal to
`!=`	Not Equal to
`<`	Less than
`>`	Greater than
`<=`	Less than or Equal to
`>=`	Greate than or Equal to
`BETWEEN`	Between a specified range of values
`LIKE`	This is used to search for a pattern in value.
`IN`	In a given set of values

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Database Concept

DBMS ER Model

DBMS Relational model

DBMS Normalization

DBMS Basic SQL

DBMS DML Command

DBMS DCL Command

Advanced SQL

UNION Operation

Example of UNION

UNION ALL

Example of Union All

INTERSECT

Example of Intersect

MINUS

Example of Minus

Database Concept

DBMS ER Model

DBMS Relational model

DBMS Normalization

DBMS Basic SQL

DBMS DML Command

DBMS DCL Command

Advanced SQL

Example of Alias in SQL Query

Database Concept

DBMS ER Model

DBMS Relational model

DBMS Normalization

DBMS Basic SQL

DBMS DML Command

DBMS DCL Command

Advanced SQL

Types of JOIN

Cross JOIN or Cartesian Product

Example of Cross JOIN

INNER Join or EQUI Join

Example of INNER JOIN

Natural JOIN

Example of Natural JOIN

OUTER JOIN

LEFT Outer Join

Example of Left Outer Join

RIGHT Outer Join

Example of Right Outer Join

Full Outer Join

Example of Full outer join is,

Database Concept

DBMS ER Model

DBMS Relational model

DBMS Normalization

DBMS Basic SQL

DBMS DML Command

DBMS DCL Command

Advanced SQL

NOT NULL Constraint

Example using NOT NULL constraint

UNIQUE Constraint

Using UNIQUE constraint when creating a Table (Table Level)

Using UNIQUE constraint after Table is created (Column Level)

Primary Key Constraint

Using PRIMARY KEY constraint at Table Level

Using PRIMARY KEY constraint at Column Level

Foreign Key Constraint

Using FOREIGN KEY constraint at Table Level

Using FOREIGN KEY constraint at Column Level

Behaviour of Foriegn Key Column on Delete

CHECK Constraint

Using CHECK constraint at Table Level

Using CHECK constraint at Column Level

Database Concept

DBMS ER Model

DBMS Relational model

DBMS Normalization

DBMS Basic SQL

DBMS DML Command

DBMS DCL Command

Advanced SQL

Syntax for DISTINCT Keyword

Example using DISTINCT Keyword

`NOT NULL` Constraint

Example using `NOT NULL` constraint

`UNIQUE` Constraint

Using `UNIQUE` constraint when creating a Table (Table Level)

Using `UNIQUE` constraint after Table is created (Column Level)

`CHECK` Constraint

Using `CHECK` constraint at Table Level

Using `CHECK` constraint at Column Level

Syntax for `DISTINCT` Keyword

Example using `DISTINCT` Keyword

Example of SQL Statement using `HAVING`

Example of `Group by` in a Statement

Example of `Group by` in a Statement with `WHERE` clause

Syntax of `Order By`

Using default `Order by`

Using Order by `DESC`

Example of `LIKE` clause

Using `_` and `%`

Using `%` only

Syntax for `WHERE` clause

Operators for `WHERE` clause condition