DBMS Concepts

DBMS Tutorial Components of DBMS. Applications of DBMS The difference between file system and DBMS. Types of DBMS DBMS Architecture DBMS Schema Three Schema Architecture. DBMS Languages.

DBMS ER Model

ER model: Entity Relationship Diagram (ERD) Components of ER Model. DBMS Generalization, Specialization and Aggregation.

DBMS Relational Model

Codd’s rule of DBMS Relational DBMS concepts Relational Integrity Constraints DBMS keys Convert ER model into Relational model Difference between DBMS and RDBMS Relational Algebra DBMS Joins

DBMS Normalization

Functional Dependency Inference Rules Multivalued Dependency Normalization in DBMS: 1NF, 2NF, 3NF, BCNF and 4NF

DBMS Transaction

What is Transaction? States of transaction ACID Properties in DBMS Concurrent execution and its problems DBMS schedule DBMS Serializability Conflict Serializability View Serializability Deadlock in DBMS Concurrency control Protocols

Difference

Difference between DFD and ERD

Misc

Advantages of DBMS Disadvantages of DBMS Data Models in DBMS Relational Algebra in DBMS Cardinality in DBMS Entity in DBMS Attributes in DBMS Data Independence in DBMS Primary Key in DBMS Foreign Key in DBMS Candidate Key in DBMS Super Key in DBMS Aggregation in DBMS Hashing in DBMS Generalization in DBMS Specialization in DBMS View in DBMS File Organization in DBMS What Is A Cloud Database What Is A Database Levels Of Locking In DBMS What is RDBMS Fragmentation in Distributed DBMS What is Advanced Database Management System Data Abstraction in DBMS Checkpoint In DBMS B Tree in DBMS BCNF in DBMS Advantages of Threaded Binary Tree in DBMS Advantages of Database Management System in DBMS Enforcing Integrity Constraints in DBMS B-Tree Insertion in DBMS B+ Tree in DBMS Advantages of B-Tree in DBMS Types of Data Abstraction in DBMS Levels of Abstraction in DBMS 3- Tier Architecture in DBMS Anomalies in Database Management System Atomicity in Database Management System Characteristics of DBMS DBMS Examples Difference between Relational and Non-Relational Databases Domain Constraints in DBMS Entity and Entity set in DBMS ER Diagram for Banking System in DBMS ER Diagram for Company Database in DBMS ER Diagram for School Management System in DBMS ER Diagram for Student Management System in DBMS ER Diagram for University Database in DBMS ER Diagram of Company Database in DBMS Er Diagram Symbols and Notations in DBMS How to draw ER-Diagram in DBMS Integrity Constraints in DBMS Red-Black Tree Deletion in DBMS Red-Black Tree Properties in DBMS Red-Black Tree Visualization in DBMS Redundancy in Database Management System Secondary Key in DBMS Structure of DBMS 2-Tier Architecture in DBMS Advantages and Disadvantages of Binary Search Tree Closure of Functional Dependency in DBMS Consistency in Database Management System Durability in Database Management System ER Diagram for Bank Management System in DBMS ER Diagram for College Management System in DBMS ER Diagram for Hotel Management System in DBMS ER Diagram for Online Shopping ER Diagram for Railway Reservation System ER Diagram for Student Management System in DBMS Isolation in DBMS Lossless Join and Dependency Preserving Decomposition in DBMS Non-Key Attributes in DBMS Data Security Requirements in DBMS DBMS functions and Components What is Homogeneous Database? DBMS Functions and Components Advantages and Disadvantages of Distributed Database

Aggregate Functions in DBMS

Aggregate Functions in DBMS: Aggregate functions are those functions in the DBMS which takes the values of multiple rows of a single column and then form a single value by using a query. These functions allow the user to summarizing the data. These functions ignore the NULL values except the count function.

In Database Management System, following are the five aggregate functions:

1. AVG

2. COUNT

3. SUM

4. MIN

5. MAX

AVG Function

This function takes the values from the given column and then returns the average of the values. This function works only on the datatypes, which are specified as numeric in the table.

Let's take an example, which describes to you how to use the AVG function in SQL. Suppose we want to calculate the average salary from the Employee_Details table, then we have to type the following query:

Select AVG(Employee_salary) from Employee_Details;

COUNT Function

This aggregate function returns the total number of values in the specified column. This function can work on any type of data, i.e., numeric as well as non-numeric. This function does not count the NULL values. If we want to count all the rows with NULL values, then we have to use the Count(*) function.

Let's take an example, which describes to us how to use the COUNT function in SQL. Suppose a user wants to count the number of employees in the Employee_Details table, then we have to type the following query:

Select Count(Employee_ID) from Employee_Details;

SUM Function

This aggregate function sums all the non-NULL values of the given column. Like the AVG function, this function also works only on the numeric data.

Let's take an example, which describes to you how to use the SUM function in SQL. Suppose a user wants to find the sum of salary from the Employee_Details table, then we have to type the following query:

Select SUM(Employee_salary) from Employee_Details;

MAX Function

This function returns the value, which is maximum from the specified column.

Let's take an example, which describes to you how to use the MAX function in SQL. Suppose we want to find the maximum price of the Cars_Price column from the Cars table, then we have to type the following query:

Select MAX(Cars_Price) from Cars;

MIN Function

This function returns the value, which is minimum from the specified column.

Let's take an example, which describes to you how to use the MIN function in SQL. Suppose we want to find the minimum price of the Bikes_Price column from the Bikes table, then we have to type the following query:

Select MIN(Bikes_Price) from Bikes;