Structured Query Language or SQL is a standard database language that is used to create, maintain, destroy, update, and retrieve data from relational databases like MySQL, Oracle, SQL Server, PostgreSQL, etc.
Entity Relationship Model (ER)
It is a conceptual framework used to describe the structure of data within a database. It was designed to represent real-world entities and the relationships between them in a more abstract way. It is similar to how Object Oriented programming is for programming language.
Entities: These are objects or “things” in the real world that have a distinct existence, such as a customer, product, or order.
Relationships: These define how entities are related to one another. For example, a “Customer” entity might have a relationship with an “Order” entity
Commands:
Create Database
create database <database_name>;
List Database
show databases;
Use Database
use <database_name>
Display structure of table
DESCRIBE table_name;
Sub-languages of SQL
Data Query Language (DQL):
Language used for performing queries on the data. This command is used to retrieve data out from the database.
Commands:
1) Select:
select * from table_name;
select column1,column2 from table_name;
select * from table_name where column1 = "value";
Data Definition Language (DDL):
Language used to define the database schema. This command is used to create,modify and delete database but not data.
Commands
1) Create:
create table table_name(
column_name data_type(size) constraint,
column_name data_type(size) constraint
column_name data_type(size) constraint
);
2) Drop:
This command removes the table/database completely.
drop table table_name;
drop database database_name;
3) Truncate:
This command removes the data only.
truncate table table_name;
4) Alter:
This command can add, delete or update columns of the table.
Add
alter table table_name
add column_name datatype;
Modify
alter table table_name
modify column column_name datatype;
--ALTER TABLE employees
--MODIFY COLUMN salary DECIMAL(10,2);
Drop
alter table table_name
drop column_name datatype;
Data Manipulation Language (DML):
Language used to manipulate the data present in the database.
1) Insert:
This command is used to insert only new values.
insert into table_name
values (val1,val2,val3,val4); //4 columns
2) Update:
update table_name set col1=val1, col2=val2 where
col3 = val3;
3) Delete:
delete from table_name where col1=val1;
Data Control Language (DCL):
GRANT: allow specified users to perform specified tasks.
REVOKE: cancel previously granted or denied permissions.
Transaction Control Language (TCL):
It is used manage transactions in a database. It manages the changes done by DML commands.
1) Commit
It is used to save all the changes made during the current transaction to the database
BEGIN TRANSACTION;
UPDATE employees
SET salary = salary * 1.1
WHERE department = 'Sales';
COMMIT;
2) Rollback
It is used to undo all the changes made during the current transaction
BEGIN TRANSACTION;
UPDATE employees
SET salary = salary * 1.1
WHERE department = 'Sales';
ROLLBACK;
3) Savepoint
begin transaction;
update customers
set first_name= 'one'
WHERE customer_id=4;
SAVEPOINT one;
update customers
set first_name= 'two'
WHERE customer_id=4;
ROLLBACK TO SAVEPOINT one;
COMMIT;
Having:
This command is used to filter results based on aggregate functions.” We cannot use aggregate functions in WHERE statement so we can use in this command”
Note: This can be used when we need to compare using made up column whereas WHERE command can be used to compare using existing column
select Department, sum(Salary) as Salary
from employee
group by department
having sum(Salary) >= 50000;
In
This command is used when they ask to exclude any two/more particular items
select * from table_name
where colname not in ('Germany', 'France', 'UK');
Distinct:
This command is used to retrieve only unique data based on the field chosen.
Select distinct field from table;
SELECT COUNT(DISTINCT salesman_id)
FROM orders;
Correlated Query
It is a subquery (a query nested inside another query) that references columns from the outer query
SELECT EmployeeName, Salary
FROM Employees e1
WHERE Salary > (
SELECT AVG(Salary)
FROM Employees e2
WHERE e1.DepartmentID = e2.DepartmentID
);
Normalization
Normalization is a database design technique used to organize tables in a way that reduces redundancy and improves data integrity. The primary goal of normalization is to divide a large table into smaller, more manageable pieces while preserving the relationships between the data
First Normal Form (1NF)
All the values in the columns are atomic (indivisible).
Each column contains only one type of data.
EmployeeID | EmployeeName | Department | PhoneNumbers
----------------------------------------------------
1 | Alice | HR | 123456, 789012
2 | Bob | IT | 345678
After 1NF:
EmployeeID | EmployeeName | Department | PhoneNumber
----------------------------------------------------
1 | Alice | HR | 123456
1 | Alice | HR | 789012
2 | Bob | IT | 345678
Second Normal Form (2NF)
It is in 1NF.
All non-key attributes are fully functionally dependent on the primary key (no partial dependencies).
EmployeeID | EmployeeName | DepartmentID | DepartmentName
---------------------------------------------------------
1 | Alice | 1 | HR
2 | Bob | 2 | IT
After 2NF:
EmployeeID | EmployeeName | DepartmentID
---------------------------------------
1 | Alice | 1
2 | Bob | 2
DepartmentID | DepartmentName
------------------------------
1 | HR
2 | IT
Third Normal Form (3NF)
It is in 2NF.
All the attributes are functionally dependent only on the primary key (no transitive dependencies).
EmployeeID | EmployeeN | DepartmentID | Department | DepartmentLocation
--------------------------------------------------------------------------
1 | Alice | 1 | HR | New York
2 | Bob | 2 | IT | Los Angeles
After 3NF:
EmployeeID | EmployeeN | DepartmentID
----------------------------------------
1 | Alice | 1
2 | Bob | 2
DepartmentID | DepartmentName | DepartmentLocation
-----------------------------------------------
1 | HR | New York
2 | IT | Los Angeles
Union:
This command is used to combine results of two or more SELECT statements
Select *
from table_name
WHERE (subject = 'Physics' AND year = 1970)
UNION
(SELECT * FROM nobel_win WHERE (subject = 'Economics' AND year = 1971));
Limit:
This command is used to limit the amount data retrieved from the query.
select Department, sum(Salary) as Salary
from employee
limit 2;
Offset:
This command is used to skip the number of rows before returning the result.
select Department, sum(Salary) as Salary
from employee
limit 2 offset 2;
Order By:
This command is used to sort the data based on the field in ascending or descending order.
Data:
create table employees (
id int primary key,
first_name varchar(50),
last_name varchar(50),
salary decimal(10, 2),
department varchar(50)
);
insert into employees (first_name, last_name, salary, department)
values
('John', 'Doe', 50000.00, 'Sales'),
('Jane', 'Smith', 60000.00, 'Marketing'),
('Jim', 'Brown', 60000.00, 'Sales'),
('Alice', 'Johnson', 70000.00, 'Marketing');
select * from employees order by department;
select * from employees order by salary desc
Null
This command is used to test for empty values
select * from tablename
where colname IS NULL;
Group By
This command is used to arrange similar data into groups using a function.
select department, avg(salary) AS avg_salary
from employees
group by department;
Like:
This command is used to search a particular pattern in a column.
SELECT *
FROM employees
WHERE first_name LIKE 'a%';
SELECT *
FROM salesman
WHERE name BETWEEN 'A' AND 'L';
Wildcard:
Characters used with the LIKE operator to perform pattern matching in string searches.
% – Percent
_ – Underscore
How to print Wildcard characters?
SELECT 'It's a beautiful day';
SELECT * FROM table_name WHERE column_name LIKE '%50!%%' ESCAPE '!';
Case
The CASE statement in SQL is used to add conditional logic to queries. It allows you to return different values based on different conditions.
SELECT first_name, last_name, salary,
CASE salary
WHEN 50000 THEN 'Low'
WHEN 60000 THEN 'Medium'
WHEN 70000 THEN 'High'
ELSE 'Unknown'
END AS salary_category
FROM employees;
Display Text
1) Print something
Select "message";
select ' For', ord_date, ',there are', COUNT(ord_no)
group by colname;
2) Print numbers in each column
Select 1,2,3;
3) Print some calculation
Select 6x2-1;
4) Print wildcard characters
select colname1,'%',colname2
from tablename;
5) Connect two colnames
select first_name || ' ' || last_name AS colname
from employees
6) Use the nth field
select *
from orders
group by colname
order by 2 desc;
Constraints
1) Not Null:
This constraint is used to tell the field that it cannot have null value in a column.
create table employees(
id int(6) not null
);
2) Unique:
This constraint is used to tell the field that it cannot have duplicate value. It can accept NULL values and multiple unique constraints are allowed per table.
create table employees (
id int primary key,
first_name varchar(50) unique
);
3) Primary Key:
This constraint is used to tell the field that uniquely identifies in the table. It cannot accept NULL values and it can have only one primary key per table.
create table employees (
id int primary key
);
4) Foreign Key:
This constraint is used to refer the unique row of another table.
create table employees (
id int primary key
foreign key (id) references owner(id)
);
5) Check:
This constraint is used to check a particular condition for data to be stored.
create table employees (
id int primary key,
age int check (age >= 18)
);
6) Default:
This constraint is used to provide default value for a field.
create table employees (
id int primary key,
age int default 28
);
Aggregate functions
1)Count:
select count(*) as members from employees;
2)Sum:
select sum(salary) as total_amount
FROM employees;
3)Average:
select avg(salary) as average_amount
FROM employees;
4)Maximum:
select max(salary) as highest_amount
FROM employees;
5)Minimum:
select min(salary) as lowest_amount
FROM employees;
6)Round:
select round(123.4567, -2) as rounded_value;
Date Functions
1) datediff
select a.id from weather a join weather b on datediff(a.recordDate,b.recordDate)=1 where a.temperature > b.temperature;
2) date_add
select date_add("2017-06-15", interval 10 day);
SECOND
MINUTE
HOUR
DAY
WEEK
MONTH
QUARTER
YEAR
3) date_sub
SELECT DATE_SUB("2017-06-15", INTERVAL 10 DAY);
Joins
Inner Join
This is used to combine two tables based on one common column.
It returns only the rows where there is a match between both tables.
Data
create table employees(
employee_id int(2) primary key,
first_name varchar(30),
last_name varchar(30),
department_id int(2)
);
create table department(
department_id int(2) primary key,
department_name varchar(30)
);
insert into employees values (1,"John","Dow",10);
insert into employees values (2,"Jane","Smith",20);
insert into employees values (3,"Jim","Brown",10);
insert into employees values (4,"Alice","Johnson",30);
insert into department values (10,"Sales");
insert into department values (20,"Marketing");
insert into department values (30,"IT");
select e.employee_id,e.first_name,e.last_name,d.department_name
from employees e
inner join department d
on e.department_id=d.department_id;
Left Join
This type of join returns all rows from the left table along with the matching rows from the right table. Note: If there are no matching rows in the right side, it return null.
select e.employee_id, e.first_name, e.last_name, d.department_name
from employees e
left join departments d
on e.department_id = d.department_id;
Right Join
This type of join returns all rows from the right table along with the matching rows from the left table. Note: If there are no matching rows in the left side, it returns null.
SELECT e.employee_id, e.first_name, e.last_name, d.department_name
FROM employees e
RIGHT JOIN departments d
ON e.department_id = d.department_id;
Self Join
This type of join is used to combine with itself especially for creation of new column of same data.
SELECT e.employee_id AS employee_id,
e.first_name AS employee_first_name,
e.last_name AS employee_last_name,
m.first_name AS manager_first_name,
m.last_name AS manager_last_name
FROM employees e
LEFT JOIN employees m ON e.manager_id = m.employee_id;
Full Join/ Full outer join
This type of join is used to combine the result of both left and right join.
SELECT e.employee_id, e.first_name, e.last_name, d.department_name
FROM employees e
FULL JOIN departments d
ON e.department_id = d.department_id;
Cross Join
This type of join is used to generate a Cartesian product of two tables.
SELECT e.name, d.department_name
FROM Employees e
CROSS JOIN Departments d;
Nested Query
A nested query, also known as a subquery, is a query within another SQL query. The nested query is executed first, and its result is used by the outer query.
Subqueries can be used in various parts of a SQL statement, including the SELECT clause, FROM clause, WHERE clause, and HAVING clause.
1) Nested Query in SELECT Clause:
SELECT e.first_name, e.last_name,
(SELECT d.department_name
FROM departments d
WHERE d.id = e.department_id) AS department_name
FROM employees e;
2) Nested Query in WHERE Clause:
SELECT first_name, last_name, salary
FROM employees
WHERE salary > (SELECT AVG(salary) FROM employees);
SELECT pro_name, pro_price
FROM item_mast
WHERE pro_price = (SELECT MIN(pro_price) FROM item_mast);
3) Nested Query in FROM Clause:
SELECT department_id, AVG(salary) AS avg_salary
FROM employees
GROUP BY department_id;
4) Nested Query with EXISTS:
SELECT customer_name
FROM customers c
WHERE EXISTS (
SELECT 1
FROM orders o
WHERE o.customer_id = c.customer_id
);
Exists
This command is used to test the existence of a particular record. Note: When using EXISTS query, actual data returned by subquery does not matter.
SELECT customer_name
FROM customers c
WHERE EXISTS (
SELECT 1
FROM orders o
WHERE o.customer_id = c.customer_id
);
SELECT customer_name
FROM customers c
WHERE NOT EXISTS (
SELECT 1
FROM orders o
WHERE o.customer_id = c.customer_id
);
COALESCE
The COALESCE function in SQL is used to return the first non-null expression among its arguments. It is particularly useful for handling NULL values and providing default values when dealing with potentially missing or undefined data.
CREATE TABLE employees (
first_name VARCHAR(50),
middle_name VARCHAR(50),
last_name VARCHAR(50)
);
INSERT INTO employees (first_name, middle_name, last_name) VALUES
('John', NULL, 'Doe'),
('Jane', 'Marie', 'Smith'),
('Emily', NULL, 'Johnson');
SELECT
first_name,
COALESCE(middle_name, 'No Middle Name') AS middle_name,
last_name
FROM
employees;
PL/SQL(Procedural Language/Structured Query Language)
It is Oracle’s procedural extension to SQL. If multiple SELECT statements are issued, the network traffic increases significantly very fast. For example, four SELECT statements cause eight network trips. If these statements are part of the PL/SQL block, they are sent to the server as a single unit.
Blocks
They are the fundamental units of execution and organization.
1) Named block
Named blocks are used when creating subroutines. These subroutines are procedures, functions, and packages. The subroutines can be stored in the database and referenced by their names later on.
Ex.
CREATE OR REPLACE PROCEDURE procedure_name (param1 IN datatype, param2 OUT datatype) AS
BEGIN
-- Executable statements
END procedure_name;
2) Anonymous
They are blocks do not have names. As a result, they cannot be stored in the database and referenced later.
DECLARE
-- Declarations (optional)
BEGIN
-- Executable statements
EXCEPTION
-- Exception handling (optional)
END;
Declaration
It contains identifiers such as variables, constants, cursors etc
Ex.
declare
v_first_name varchar2(35) ;
v_last_name varchar2(35) ;
v_counter number := 0 ;
v_lname students.lname%TYPE; // takes field datatype from column
Rowtype
DECLARE
v_student students%rowtype;
BEGIN
select * into v_student
from students
where sid='123456';
DBMS_OUTPUT.PUT_LINE(v_student.lname);
DBMS_OUTPUT.PUT_LINE(v_student.major);
DBMS_OUTPUT.PUT_LINE(v_student.gpa);
END;
Execution
It contains executable statements that allow you to manipulate the variables.
declare
v_regno number;
v_variable number:=0;
begin
select regno into v_regno from student where regno=1;
dbms_output.put_line(v_regno || ' '|| v_variable);
end
Input of text
DECLARE
v_inv_value number(8,2);
v_price number(8,2);
v_quantity number(8,0) := 400;
BEGIN
v_price := :p_price;
v_inv_value := v_price * v_quantity;
dbms_output.put_line(v_inv_value);
END;
If-else loop
IF rating > 7 THEN
v_message := 'You are great';
ELSIF rating >= 5 THEN
v_message := 'Not bad';
ELSE
v_message := 'Pretty bad';
END IF;
Loops
Simple Loop
declare
begin
for i in 1..5 loop
dbms_output.put_line('Value of i: ' || i);
end loop;
end;
While Loop
declare
counter number := 1;
begin
while counter <= 5 LOOP
dbms_output.put_line('Value of counter: ' || counter);
counter := counter + 1;
end loop;
end;
Loop with Exit
declare
counter number := 1;
begin
loop
exit when counter > 5;
dbms_output.put_line('Value of counter: ' || counter);
counter := counter + 1;
end loop;
end;
Procedure
A series of statements accepting and/or returning
zero variables.
--creating a procedure
create or replace procedure proc (var in number) as
begin
dbms_output.put_line(var);
end
--calling of procedure
begin
proc(3);
end
Function
A series of statements accepting zero or more variables that returns one value.
create or replace function func(var in number)
return number
is res number;
begin
select regno into res from student where regno=var;
return res;
end
--function calling
declare
var number;
begin
var :=func(1);
dbms_output.put_line(var);
end
All types of I/O
p_name IN VARCHAR2
p_lname OUT VARCHAR2
p_salary IN OUT NUMBER
Triggers
DML (Data Manipulation Language) triggers are fired in response to INSERT, UPDATE, or DELETE operations on a table or view.
BEFORE Triggers:
Execute before the DML operation is performed.
AFTER Triggers:
Execute after the DML operation is performed.
INSTEAD OF Triggers:
Execute in place of the DML operation, typically used for views.
Note: :new represents the cid of the new row in the orders table that was just inserted.
create or replace trigger t_name
after update on student
for each row
begin
dbms_output.put_line(:NEW.regno);
end
--after updation
update student
set name='name'
where regno=1;
Window function
SELECT
id,name,gender,
ROW_NUMBER() OVER(
PARTITION BY name
order by gender
) AS row_number
FROM student;
SELECT
employee_id,
department_id,
salary,
RANK() OVER(
PARTITION BY department_id
ORDER BY salary DESC
) AS salary_rank
FROM employees;
ACID Properties:
Atomicity:
All operations within a transaction are treated as a single unit.
Ex. Consider a bank transfer where money is being transferred from one account to another. Atomicity ensures that if the debit from one account succeeds, the credit to the other account will also succeed. If either operation fails, the entire transaction is rolled back to maintain consistency.
Consistency:
Consistency ensures that the database remains in a consistent state before and after the transaction.
Ex. If a transfer transaction reduces the balance of one account, it should also increase the balance of the receiving account. This maintains the overall balance of the system.
Isolation:
Isolation ensures that the concurrent execution of transactions results in a system state that would be obtained if transactions were executed serially, i.e., one after the other.
Ex. Consider two transactions T1 and T2. If T1 transfers money from account A to account B, and T2 checks the balance of account A, isolation ensures that T2 will either see the balance of account A before the transfer (if T1 has not committed yet) or after the transfer (if T1 has committed), but not an intermediate state.
Durability:
Durability guarantees that once a transaction is committed, its effects are permanent and survive system failures. Even if the system crashes or restarts, the changes made by the transaction are not lost.
Data Types
1) Numeric Datatype
int
decimal(p,q) – p is size, q is precision
2) String Datatype
char(value) – max(8000) && immutable
varchar(value) – max(8000)
text – largest size
3) Date Datatype
date
time
datetime
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