000958762 aung pyae comp1639_dbe

Myanmar Computer Co., Ltd.

Course: COMP 1639

B.Sc. Top up Programme

Date: December 2016

A dissertation submitted in partial fulfilment of the requirements for the University of Greenwich’s Bachelor of Science Degree in Business Information Technology.

COMP1639

Word Count: 4122

Prepared by: AUNG PYAE

Student ID: 000958762

COMP1639 DATABASE ENGINEERING

2

COURSE : BSC (HONS) BUSINESS IT

MODULE TITLE : DATABASE ENGINEERING

ASSIGNMENT TITLE : SPORT INFORMATION SYSTEM (FOOTBALL)

EXAM CYCLE : DECEMBER 2016

CANDIDATE NAME : AUNG PYAE

CANDIDATE NO : 000958762

SUMMITED DATE : 21-11-2016

MARKAR’S COMMENT :

MODERATOR’S COMMENT :

MARKS: MODERATED MARKS: FINAL MARKS:


3

STATEMENT AND CONFIRMATION OF OWN WORK

All GREENWICH Education assessed assignments submitted by students must have this statement

as the cover page or it will not be accepted for marking. Please ensure that this statement is either

firmly attached to the cover of the assignment or electronically inserted into the front of the

assignment.

STUDENT DECLARATION

I have read and understood GREENWICH Education’s Policy on Academic Dishonesty and

Plagiarism.

I am confirmed the following details:

STUDENT ID/REGISTRATION NUMBER: 000958762

NAME : AUNG PYAE

CENTRE NAME : MCC TRAINING INSTITUTE (YATANARPON)

MODULE NAME : DATABASE ENGINEERING

MODULE LEADER : DAW THE SEINT AYE, DAW NEW NWE WIN

TITILE OF WORK : SPORT INFORMATION SYSTEM (FOOTBALL)

NUMBER OF WORDS : 4122

I confirm that this is my own work and that I have not plagiarized any part of it. I have also noted

the assessment criteria and pass mark for assignments.

DUE DATE : 21-11-2016

STUDENT SIGNATURE : AUNGPYAE

SUBBMITTED DATE : 21-11-2016


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CONTENTS CONTENTS ........................................................................................................................... 4

ACKNOWLEDGEMENT ........................................................................................................ 5

DATABASE DESIGN ............................................................................................................. 6

Assumptions about the database system and design .................................................................. 6

Enhanced Entity Relationship Diagram ................................................................................... 8

Relational schema for all entities.......................................................................................... 12

Normalization.................................................................................................................... 13

DATABASE SETUP ............................................................................................................. 20

Create commands of database and tables ............................................................................... 20

Population of database with data and values .......................................................................... 32

View, Trigger and Index ..................................................................................................... 35

SQL QUERIES ..................................................................................................................... 40

10 SQL queries that demonstrate for usefulness of database .................................................... 40

Future development report .................................................................................................. 50

Self-Assessment Sheet ........................................................................................................ 51

REFERENCES ..................................................................................................................... 52


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ACKNOWLEDGEMENT Knowledge is the most valuable prize of the world and the teachers who gives me knowledge are

valuable, thankful and grand persons. When I first arrived in MCC Institute, every learning courses

and texts are difficult for me but my teachers are very kind and help, teach and train me to the right

way with practical and technological skills to become the successful IT researcher student. So I great

thanks to my teachers with best wishes.

On designing and developing of this database management, I planned how to document the report

completely and help for teachers, professionals and researchers. I great thank to all teacher in our B.Sc.

programme for giving me great advices and logical thinking. I also thanks to our class tutor, Daw K

Zin Thant and mindful assistant lecturer, Daw Zin Thandar, give me strengths for my mind and teach

me to become well certified student.

Next I thanks to my friends who help me in solving the difficulties on finding the problems and

solutions of business cases. Finally, I great thank to MCC, NCC education, University of Greenwich

and all our education partners since they service me to get more ways for living and guide to become

a professional IT technician.

Aung Pyae


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DATABASE DESIGN

Assumptions about the database system and design I designed the relational database system for football management system and created with SQL

command queries (Data Query Language, Data Manipulation Language, Data Definition Language,

data Control Language) to use and manage the database.

There are 14 tables in football management database and all tables are connected with their

constraints. The judge team table recorded the judge team data to manage in match. The manager

table is used to record the managers with their profile information such as name, NRC, email, phone,

etc. The match table used to insert the matches with the related events. The match event table

recorded the events of whole match with their start date, end date and venues. Match player position

table is used to place for players to play which player plays in what position such as Goalkeeper,

Midfielder, Centre Forward. On match table is used to record goal records in match. Owner table and

Player table are uses to record information of owners and players as in the manager table. Player goal

table records the goals of players and position table has the values of football playing positions.

Round table record the match and teams with their playing positions. Team table records the

information of all teams with manger id, owner id and team score tables has the scores on each team.

Transfer table is used to record while transferring the player on match.

To start the match, there need to create and event in event table with other information. And match

table is needed to insert the match information with judge team and event. After inserting in match

table, two participating teams are need to record to round table by selecting LEFT or RIGHT positions.

Two rows need to insert and trigger will run for player placing in match player position table for each

row.

If a player wins a goals on playing the match, there will insert one row in on match table and if one

row is inserted, the trigger will run to insert on player goal and team score for goaled team and player.

All team score can be view from final result VIEW.

The whole database system uses MySQL relational database management system (RDBMS), which is

the most commercial database type in Structured Query Language (SQL).


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RDBMS is the best and common choice for storage of information in database with related primary

and foreign relations. So the football management database system uses RDBMS to keep record and

retrieve information.

SINCE ALL SQL KEYWORDS ARE FIXED AND ALL OTHER STUDENTS USE SAME

COMMAND LINES, I CANNOT AVOID PLAGARISM CHECKING WHICH HAS BEEN

COUNTED FOR THOSE KEYWORDS.


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Enhanced Entity Relationship Diagram

ap_manager

manager_nationali

ty

manager_address

manager_email

manager_name

manager_salary

ap_owner

owner_name owner_idowner_nrc

owner_phone

owner_personal_blo

g

ap_team

manage

ap_player_goal

ap_position

ap_player ap_match_player_position

manager_id

manager_phone

manager_nrc

manager_birthday

owns

owner_address

owner_email

owner_nationali ty

owner_birthday

goal participate

place

place

has

position_id

position_type

player_id

match_id

player_goal

team_id player_reg_date

player_id player_salary

player_name

player_nationality

player_birthday

player_number

player_nrc

player_email

player_phone player_w

eight_kg

player_height_ft

player_blood

ap_transfer

transfer

substitute

participate

dap_round

place for

ap_match

transfer place

divide

plays

plays

has

ap_on_match

ap_team_score

goal

get from

play

ap_match_event ap_judge_teamschedule control

match_id

player_id

trans fer_type

manager_blog

team_headquarter

team_name

team_country

manager_id

owner_id team_email

team_est_year

team_id

match_id

player_id

team_id

position_id

team_id

match_id

position

match_id on_match_goal

on_match_time team_id

team_score

team_id

match_id

event_id

match_date

judge_team_id

match_id

event_naneevent_id

event_start_date

event_end_date

event_venue

judge_team_contac

t

judge_team_id

judge_team_name

judge_team_memb

ers

Enhanced Entity Relationship Diagram for football management database system showing all entities,

attributes, relationships and multi sub classes connected with related notation signs using Chen’s

Database Notation method.


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Regular entity

ap_player

team_id player_reg_date

player_id player_salary

player_name

player_nationality

player_birthday

player_number

player_nrc

player_email

player_phone player_w

eight_kg

player_height_ft

player_blood

Player entity with attributes

ap_team

team_headquarter

team_name

team_country

manager_id

owner_id team_email

team_est_year

team_id

Team entity with attributes

There are 14 entities in the database and each linked with their related relationships.


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One to one entity

ap_manager

manager_nationali

ty

manager_address

manager_email

manager_name

manager_salary

ap_team

manage

manager_id

manager_phone

manager_nrc

manager_birthday

manager_blog

team_headquarter

team_name

team_country

manager_id

owner_id team_email

team_est_year

team_id

One to one entity relationship between manager and team. The relationship shows that one manager

manages only one team and one team only be controlled by one manager.

Relational schema for one to one entity

Manager_id

Manager_name

Manager_nrc

Manager_email

Manager_phone

Manager_birthday

Manager_national

ity

Manager_address

Manager_salary

Manager_blog

Team_id Owner_id

Manager_id*

Team_name

Team_email

Team_Est_year

Team_headquarte

rTeam_

ap_manager

ap_team


11

Multi sub class entity

ap_match_player_position

ap_transfer

substitute

participate

dap_round

place for

match_id

player_id

transfer_type

match_id

player_id

team_id

position_id

team_id

match_id

position

This multi sub class entity shows the relationship of round and players. If selecting for match,

participate payers are inserted in match player position for player placing and substitute are used for

player transfer on match.

Mapping result for multi sub class entity

Match_id* Team_id Player_id Position_id

Match_id* Player_id Transfer_type

Match_id* Team_id position


ap_transfer

ap_round


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Relational schema for all entities

Owner_id

Owner_name

Owner_nrc

Ower_email

Owner_phone

Owner_birthday

Owner_nationality

Owner_adddress

Owner_Personal_

blog

Manager_id

Manager_name

Manager_nrc

Manager_email

Manager_phone

Manager_birthday

Manager_national

ity

Manager_address

Manager_salary

Manager_blog

Judge_team_id name Total_me

mbers contact

Position_id

Position_type

Event_id Event_name

Event_Start_date

Event_End_date

Event_venue

Match_id Event_id Judge_team_id

Match_date

Match_id Team_id Player_id Position_id

Player_id Match_id Player_goal

Team_id Match_id Team_score

Team_id Owner_id

Manager_id

Team_name

Team_email

Team_Est_year

Team_headquarte

rTeam_

Match_id Player_id Transfer_type

Match_id Team_id On_match_goal

On_match_time

Match_id Team_id position

Player_id Team_id Player_name

Player_number

Player_nrc

Player_email

Player_phone

Player_Height_ft

Player_Weight_k

g

Player_birthday

Player_nationality

Player_salary

Player_Reg_date

Player_blood


ap_on_match

ap_judge_team

ap_player_goal

ap_position

ap_transfer

ap_team_score

ap_round

ap_player

ap_team

ap_manager

ap_owner

ap_match_event

ap_match

Relational schema diagram clearly showing all tables in database with all relations


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Normalization (1): Judge team table

Judge_team_id Judge_team_name Judge_team_members Judge_contact

In this judge team table, there are no multivalued attributes and the values of each attribute (column)

such as (JUDGE_TEAM_ID, JUDGE_TEAM_NAME, etc.) are atomic. Therefore, the table is in 1st

Normal form.

This table is in 1NF and the value of each non-key attribute such as (JUDGE_TEAM_NAME,

JUDGE_TEAM_MEMBERS, etc.) is fully functionally dependent on the primary key

(JUDGE_TEAM_ID) in the table. Therefore, it’s in 2nd Normal Form.

This table is in 2NF and there are no functional dependencies between non-keys attribute in the judge

table and the JUDGE_TEAM_ID is primary key and other attributes are non-key attributes. Therefore,

it’s in 3rd Normal Form.

(2): Manager table

Mana

ger_i

d

Manag

er_nam

e

Mana

ger_nr

c

Manag

er_ema

il

Manage

r_phon

e

Manager

_birthda

y

Manager_

nationalit

y

Manage

r_addres

s

Manage

r_salary

Manag

er_blo

g

In this manager table, there are no multivalued attributes and the values of each attribute (column)

such as (MANAGER_ID, MANAGER_NAME, MANAGER_NRC, etc.) are atomic. Therefore, the

table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (MANAGER_NAME,

MANAGER_NRC, etc.) is fully functionally dependent on the primary key (MANAER_ID) in the

table. Therefore, it’s in 2nd Normal Form.

This table is in 2NF and there are no functional dependencies between non-keys attribute in the table

and the MANAGER_ID is primary key and other attributes are non-key attributes. Therefore, it’s in

3rd Normal Form.

(3): Match table


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Match_id Event_id Judge_team_id Match_date

In this match table, there are no multivalued attributes and the values of each attribute (column) such

as (MATCH_ID, EVENT_ID, JUDGE_TEAM_ID, etc.) are atomic. Therefore, the table is in 1st

Normal form.

This table is in 1NF and the value of each non-key attribute such as (EVENT_ID, MATCH_DATE,

etc.) is fully functionally dependent on the primary key (MATCH_ID) in the table. Therefore, it’s in

2nd Normal Form.


and the MATCH_ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(4): Match event table

Event_id Event_name Event_start_date Event_end_date Event_venue

In this match event table, there are no multivalued attributes and the values of each attribute (column)

such as (EVENT_ID, EVENT_NAME, etc.) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (EVENT_NAME,

EVETN_START_DATE, EVENT_END_DATE, etc.) is fully functionally dependent on the primary

key (EVENT_ID) in the table. Therefore, it’s in 2nd Normal Form.


and the EVENT_ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(5): Match player position table

Match_id Team_id Player_id Position_id

In this match player position table, there are no multivalued attributes and the values of each attribute

(column) such as (MATCH_ID, TEAM_ID, PLAYER_ID, POSITION_ID) are atomic. Therefore, the

table is in 1st Normal form.


15

This table is in 1NF and the value of each non-key attribute such as (TEAM_ID, PLAYER_ID,

POSITION_ID) is fully functionally dependent on the primary key (MATCH_ID) in the table.

Therefore, it’s in 2nd Normal Form.



Normal Form.

(6): On match table

Match_id Team_id On_match_goal On_match_time

In this on match table, there are no multivalued attributes and the values of each attribute (column)

such as (MATCH_ID, TEAM_ID) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (TEAM_ID,

ON_MATCH_GOAL, ON_MATCH_TIME) is fully functionally dependent on the primary key

(MATCH_ID) in the table. Therefore, it’s in 2nd Normal Form.



Normal Form.

(7): Owner table

Owne

r_id

Owner_

name

Owner

_nrc

Owner_

email

Owner_

phone

Owner_bi

rthday

Owner_nat

ionality

Owner_a

ddress

Owner_perso

nal_blog

In this owner table, there are no multivalued attributes and the values of each attribute (column) such

as (OWNER_ID, OWNER_NAME, etc.) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (OWNER_NAME,

OWNER_NRC, OWNER_EMAIL, etc.) is fully functionally dependent on the primary key

(OWNER_ID) in the table. Therefore, it’s in 2nd Normal Form.


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and the OWNER_ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(8): Player table

Pla

yer

_id

Te

am

_i

d

Play

er_n

ame

Play

er_n

umb

er

Pla

yer

_nr

c

Play

er_e

mail

Play

er

Play

er_p

hone

Play

er_b

lood

Playe

r_hei

ght_ft

Player

_weig

ht_kg

Playe

r_birt

hday

Player

_natio

nality

Play

er_s

alar

y

Playe

r_reg

_date

In this player table, there are no multivalued attributes and the values of each attribute (column) such

as (PLAYER_ID, PLAYER_NAME, etc.) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (PLAYER_NAME,

PLAYER_NUMBER, etc.) is fully functionally dependent on the primary key (PLAYER_ID) in the

table. Therefore, it’s in 2nd Normal Form.


and the PLAYER_ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(9): Player goal table

Player_id Match_id Player_goal

In this player goal table, there are no multivalued attributes and the values of each attribute (column)

such as (PLAYER_ID, MATCH_ID, PLAYER_GOAL) are atomic. Therefore, the table is in 1st

Normal form.

This table is in 1NF and the value of each non-key attribute such as (MATCH_ID, LAYER_GOAL)

is fully functionally dependent on the primary key (PLAYER_ID) in the table. Therefore, it’s in 2nd

Normal Form.


17


and the PLAYER_ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(10): Position table

Position_id Position_type

In this position table, there are no multivalued attributes and the values of each attribute (column)

such as (POSITION_ID, POSITION_TYPE) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (POSITION_TYPE) is fully

functionally dependent on the primary key (POSITION _ID) in the table. Therefore, it’s in 2nd Normal

Form.


and the POSITION _ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(11): Round table

Match_id Team_id position

In this round table, there are no multivalued attributes and the values of each attribute (column) such

as (MATCH_ID, TEAM_ID, POSITION) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (TEAM_ID, POSITION) is fully

functionally dependent on the primary key (MATCH _ID) in the table. Therefore, it’s in 2nd Normal

Form.


and the MATCH _ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(12): Team table


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Team_

id

Owner_

id

Manager

_id

Team_na

me

Team_em

ail

Team_est_y

ear

Team_headqua

rter

Team_coun

try

In this team table, there are no multivalued attributes and the values of each attribute (column) such as

(TEAM_ID, OWNER_ID, MANAGER_ID, etc) are atomic. Therefore, the table is in 1st Normal form.

This table is in 1NF and the value of each non-key attribute such as (OWNER_ID, MANAGR_ID,

TEAM_NAME, TEAM_EMAIL, etc.) is fully functionally dependent on the primary key (TEAM

_ID) in the table. Therefore, it’s in 2nd Normal Form.


and the TEAM _ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(13): Team score table

Team_id Match_id Team_score

In this team score table, there are no multivalued attributes and the values of each attribute (column)

such as (TEAM_ID, MATCH_ID, TEAM_SCORE) are atomic. Therefore, the table is in 1st Normal

form.

This table is in 1NF and the value of each non-key attribute such as (MATCH_ID, TEAM_SCORE) is

fully functionally dependent on the primary key (TEAM _ID) in the table. Therefore, it’s in 2nd

Normal Form.


and the TEAM _ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.

(14): Transfer table

Match_id Player_id Transfer_type


19

In this transfer table, there are no multivalued attributes and the values of each attribute (column) such

as (MATCH_ID, PLAYER_ID, TRANSFER_TYPE) are atomic. Therefore, the table is in 1st Normal

form.

This table is in 1NF and the value of each non-key attribute such as (PLAYER_ID,

TRANSFER_TYPE) is fully functionally dependent on the primary key (MATCH _ID) in the table.

Therefore, it’s in 2nd Normal Form.


and the MATCH _ID is primary key and other attributes are non-key attributes. Therefore, it’s in 3rd

Normal Form.


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DATABASE SETUP

Create commands of database and tables (1): Create database

(2): Create query for judge team table

Result

(3): Create query for manager table

CREATE àung_pyae_dbe_football`;

USE àung_pyae_dbe_football`;

CREATE TABLE àp_judge_team` (

`judge_team_id` varchar(50) NOT NULL,

`judge_team_name` varchar(50) NOT NULL,

`judge_team_members` int(11) NOT NULL,

`judge_contact` varchar(50) NOT NULL,

PRIMARY KEY (`judge_team_id`)

);


21

Result

CREATE TABLE àp_manager` (

`manager_id` varchar(50) NOT NULL,

`manager_name` varchar(50) NOT NULL,

`manager_nrc` varchar(50) NOT NULL,

`manager_email` varchar(50) NOT NULL,

`manager_phone` int(11) NOT NULL,

`manager_birthday` date NOT NULL,

`manager_nationality` varchar(50) NOT NULL,

`manager_address` text NOT NULL,

`manager_salary` double NOT NULL,

`manager_blog` varchar(50) NOT NULL,

PRIMARY KEY (`manager_id`)

);


22

(4): Create query for match table

Result

(5): Create query for match event table

Result

CREATE TABLE àp_match` (

`match_id` varchar(50) NOT NULL,

èvent_id` varchar(50) NOT NULL,

`judge_team_id` varchar(50) NOT NULL,

`match_date` date NOT NULL,

PRIMARY KEY (`match_id`),

KEY èvent_id` (èvent_id`),

KEY `judge_team_id` (`judge_team_id`),

CONSTRAINT àp_match_ibfk_1` FOREIGN KEY (èvent_id`) REFERENCES àp_match_event` (èvent_id`),

CONSTRAINT àp_match_ibfk_3` FOREIGN KEY (`judge_team_id`) REFERENCES àp_judge_team` (`judge_team_id`)

);

CREATE TABLE àp_match_event` (

èvent_id` varchar(50) NOT NULL,

èvent_name` text NOT NULL,

èvent_start_date` date NOT NULL,

èvent_end_date` date NOT NULL,

èvent_venue` text NOT NULL,

PRIMARY KEY (èvent_id`)

);


23

(6): Create query for match player position (player placing) table

Result

(7): Create query for on match (matching) table

CREATE TABLE àp_match_player_position` (


`team_id` varchar(50) DEFAULT NULL,

`player_id` varchar(50) NOT NULL,

`position_id` varchar(50) NOT NULL,

KEY `match_id` (`match_id`),

KEY `player_id` (`player_id`),

KEY `position_id` (`position_id`),

KEY `team_id` (`team_id`),

CONSTRAINT àp_match_player_position_ibfk_1` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`),

CONSTRAINT àp_match_player_position_ibfk_2` FOREIGN KEY (`player_id`) REFERENCES àp_player` (`player_id`),

CONSTRAINT àp_match_player_position_ibfk_3` FOREIGN KEY (`position_id`) REFERENCES àp_position` (`position_id`),

CONSTRAINT àp_match_player_position_ibfk_4` FOREIGN KEY (`team_id`) REFERENCES àp_team` (`team_id`)

);


24

Result

(8): Create query for owner table

CREATE TABLE àp_on_match` (


`team_id` varchar(50) NOT NULL,

òn_match_goal` int(11) NOT NULL,

òn_match_time` varchar(50) NOT NULL,


KEY `player_id` (`team_id`),

CONSTRAINT àp_on_match_ibfk_1` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`),

CONSTRAINT àp_on_match_ibfk_2` FOREIGN KEY (`team_id`) REFERENCES àp_team` (`team_id`)

);

CREATE TABLE àp_owner` (

òwner_id` varchar(50) NOT NULL,

òwner_name` varchar(50) NOT NULL,

òwner_nrc` varchar(50) NOT NULL,

òwner_email` varchar(50) NOT NULL,

òwner_phone` int(11) NOT NULL,

òwner_birthday` date NOT NULL,

òwner_nationality` varchar(50) NOT NULL,

òwner_address` text NOT NULL,

òwner_personal_blog` varchar(50) NOT NULL,

PRIMARY KEY (òwner_id`)

);


25

Result

(9): Create query for player table


26

Result

CREATE TABLE àp_player` (



`player_name` varchar(50) NOT NULL,

`player_number` int(11) NOT NULL,

`player_nrc` varchar(50) NOT NULL,

`player_email` varchar(50) NOT NULL,

`player_phone` int(11) NOT NULL,

`player_blood` varchar(10) NOT NULL,

`player_height_ft` double NOT NULL,

`player_weight_kg` double NOT NULL,

`player_birthday` date NOT NULL,

`player_nationality` varchar(50) NOT NULL,

`player_salary` double NOT NULL,

`player_reg_date` date NOT NULL,

PRIMARY KEY (`player_id`),


KEY `player` (`player_id`),

CONSTRAINT àp_player_ibfk_1` FOREIGN KEY (`team_id`) REFERENCES àp_team` (`team_id`)

);


27

(10): Create query for player goal table

Result

(11): Create query for position table

Result

(12): Create query for round table

CREATE TABLE àp_player_goal` (



`player_goal` int(11) NOT NULL,



CONSTRAINT àp_player_goal_ibfk_1` FOREIGN KEY (`player_id`) REFERENCES àp_player` (`player_id`),

CONSTRAINT àp_player_goal_ibfk_2` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`)

);

CREATE TABLE àp_position` (

`position_id` varchar(50) NOT NULL,

`position_type` varchar(100) NOT NULL,

PRIMARY KEY (`position_id`)

);


28

Result

(13): Create query for team table

CREATE TABLE àp_round` (



`position` enum('LEFT','RIGHT') NOT NULL,



CONSTRAINT àp_round_ibfk_1` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`),

CONSTRAINT àp_round_ibfk_2` FOREIGN KEY (`team_id`) REFERENCES àp_team` (`team_id`)

);


29

Result

(14): Create query for team score table

CREATE TABLE àp_team` (


òwner_id` varchar(50) NOT NULL,

`manager_id` varchar(50) NOT NULL,

`team_name` varchar(50) NOT NULL,

`team_email` varchar(50) NOT NULL,

`team_est_year` int(11) NOT NULL,

`team_headquarter` text NOT NULL,

`team_country` varchar(50) NOT NULL,

PRIMARY KEY (`team_id`),

KEY òwner_id` (òwner_id`),

KEY `manager_id` (`manager_id`),

CONSTRAINT àp_team_ibfk_1` FOREIGN KEY (òwner_id`) REFERENCES àp_owner` (òwner_id`),

CONSTRAINT àp_team_ibfk_2` FOREIGN KEY (`manager_id`) REFERENCES àp_manager` (`manager_id`)

);


30

Result

(15): Create query for transfer (player transfer on match) table

Result

CREATE TABLE àp_team_score` (



`team_score` double NOT NULL,



CONSTRAINT àp_team_score_ibfk_1` FOREIGN KEY (`team_id`) REFERENCES àp_team` (`team_id`),

CONSTRAINT àp_team_score_ibfk_2` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`)

);

CREATE TABLE àp_transfer` (



`transfer_type` enum('OLD','NEW') NOT NULL,



CONSTRAINT àp_transfer_ibfk_3` FOREIGN KEY (`match_id`) REFERENCES àp_match` (`match_id`),

CONSTRAINT àp_transfer_ibfk_5` FOREIGN KEY (`player_id`) REFERENCES àp_player` (`player_id`)

);


31


32

Population of database with data and values (16): Insert data to manager table

insert into àp_manager`(`manager_id`,`manager_name`,`manager_nrc`,`manager_email`,`manager_phone`,`manager_birthday`,`manager_nationality`,`manager_address`,`manager_salary`,`manager_blog`) values ('MG01','Yuri','9/M(N)789456','[email protected]',9789654,'1994-11-28','JAPAN','No.22, Tera street, NW township',78965.12,'www.yuri.weebly.com'),

('MG02','Minnie','1/M(N)765744','[email protected]',9784521,'1994-06-22','MYANMAR','MCC institute compound, Mandalay',41258.56,'N/A'),

('MG03','Thiha Myat','2/W(N)452151','[email protected]',9785632,'1990-02-06','SOUTH KOREA','Block A, Tower 4D, MD trade center',82885.45,'N/A'),

('MG04','Hein Zarni','3/W(N)722226','[email protected]',9874125,'1989-02-07','USA','No.44, Judgernet street',98564.21,'N/A'),

('MG05','Michi Torea','9/M(N)111112','[email protected]',9853145,'1994-06-07','UK','No22, Arial street, near KZ bank',62457.45,'N/A'),

('MG06','Shiina Yosuke','9/D(N)564544','[email protected]',9875655,'1994-06-28','UK','No.65, Nano street\r\n',69855.36,'www.shiina.flip.jp'),

('MG07','Pudge','9/M(N)123445','[email protected]',9787878,'1989-01-03','THAILAND','No.23, George commerical center',85657.22,'www.pudge.flip.jp'),

('MG08','Lwin Moe Aung','9/M(N)456666','[email protected]',2555444,'1994-12-08','SINGAPORE','Room 1, Floor 4,Capital trade center',98556.24,'www.lwin.weebly.com'),

('MG09','Mario','2/M(N)734544','[email protected]',9875566,'1989-01-28','ITALY','No.44B, Huge square township',85647.21,'N/A'),

('MG10','Jerry','1/M(N)733333','[email protected]',9874366,'1994-06-28','FRENCH','Compound 4, Block A, Room 5, national tower',75652.24,'N/A'),

('MG11','Jack','7/T(N)754555','[email protected]',2564444,'1989-06-28','BRAZIL','Floor 65, Room 2, Capital tower',87214.13,'www.jack.wordpress.org'),

('MG12','Ben Gates','9/G(N)784444','[email protected]',2136977,'1989-02-28','USA','Room 3, Floor 55, Empire state building',56884.26,'www.bengates.blogspot.com');


33

(17): Insert data to judge team table

(18): Insert data to position table

insert into àp_judge_team`(`judge_team_id`,`judge_team_name`,`judge_team_members`,`judge_contact`) values

('J1','PANDA SPORT JUDGE TEAM',13,'[email protected]'),

('J2','WHITE MATCH SPORT JUDGE',11,'National sport center, US'),

('J3','NATIONAL FOOTBALL JUDGE TEAM',13,'965521'),

('J4','YOSUKE JUDGE TEAM',15,'[email protected]'),

('J5','YOUKU JUDGE TEAM',14,'www.youku.wordpress.org');


34

insert into àp_position`(`position_id`,`position_type`) values ('CF','CENTRE FORWARD'),

('CHB','CENTRE HALF-BACK'),

('CHF','CENTRE HALF-FORWARD'),

('FB','FULL-BACK'),

('GK','GOALKEEPER'),

('LB','LEFT CORNER-BACK'),

('LCF','LEFT CORNER-FORWARD'),

('LHB','LEFT HALF-BACK'),

('LHF','LEFT HALF-FORWARD'),

('M','MIDFILEDER'),

('RB','RIGHT CORNER-BACK'),

('RCF','RIGHT CORNER-FORWARD'),

('RHB','RIGHT HALF-BACK'),

('RHF','RIGHT HALF-FORWARD');


35

View, Trigger and Index (19): Create view for final result

CREATE

ALGORITHM = UNDEFINED

DEFINER = `root`@`localhost`

SQL SECURITY DEFINER

VIEW àung_pyae_dbe_football`.`final_result` AS

SELECT

`ts`.`team_id` AS `team_id`,

`t`.`team_name` AS `team_name`,

SUM(`ts`.`team_score`) AS `team_score`

FROM

(àung_pyae_dbe_football`.àp_team_score` `ts`

JOIN àung_pyae_dbe_football`.àp_team` `t`)

WHERE

(`ts`.`team_id` = `t`.`team_id`)

GROUP BY `ts`.`team_id`;


36

(20): Create view for player view

CREATE




VIEW àung_pyae_dbe_football`.`player_view` AS

select àp_player`.`player_name` AS `player_name`,sum(àp_player_goal`.`player_goal`) AS `player_goal` from (àp_player_goal` join àp_player`) where (àp_player_goal`.`player_id` = àp_player`.`player_id`) group by àp_player`.`player_id`CREATE VIEW player_view AS

SELECT

àp_player`.`player_name` AS `player_name`,

SUM(àp_player_goal`.`player_goal`) AS `player_score`

FROM

(àp_player_goal`

JOIN àp_player`)

WHERE

(àp_player_goal`.`player_id` = àp_player`.`player_id`)

GROUP BY àp_player`.`player_id`;


37

(21): Create view for team players

CREATE




VIEW àung_pyae_dbe_football`.`team_players` AS

SELECT

àung_pyae_dbe_football`.àp_player`.`team_id` AS `team_id`,

COUNT(0) AS `team_players`

FROM

àung_pyae_dbe_football`.àp_player`

GROUP BY àung_pyae_dbe_football`.àp_player`.`team_id`;


38

(22): Create trigger for player and team score calculation

CREATE DEFINER=`root`@`localhost` TRIGGER àp_on_match_after_insert` AFTER INSERT ON àp_on_match` FOR EACH ROW BEGIN

declare player varchar(50);

INSERT INTO ap_team_score VALUES (new.team_id,new.match_id,'3');

SELECT player_id FROM ap_match_player_position WHERE match_id=new.match_id AND team_id=new.team_id ORDER BY RAND() LIMIT 1 into player;

INSERT INTO ap_player_goal VALUES (player,new.match_id,'1');

END


39

(23): Create trigger for player placing

(24): Create index on ap_player

CREATE DEFINER=`root`@`localhost` TRIGGER àp_player_placing` AFTER INSERT ON àp_round` FOR EACH ROW BEGIN

declare player_one varchar(50);

declare duplicate_player varchar(50);

declare total int;

declare p_position varchar(50);

myLoop: LOOP

select COUNT(player_id) from ap_match_player_position where match_id=new.match_id AND team_id=new.team_id into total;

SELECT `player_id` FROM ap_player WHERE `team_id`=new.team_id ORDER BY RAND() LIMIT 1 INTO player_one;

select position_id from ap_position ORDER BY RAND() LIMIT 1 INTO p_position;

INSERT INTO àp_match_player_position` VALUES (new.match_id,new.team_id,player_one,p_position);

IF total=10 THEN

LEAVE myLoop;

END IF;

END LOOP myLoop;

END

CREATE INDEX player ON ap_player(player_id);


40

SQL QUERIES

10 SQL queries that demonstrate for usefulness of database (1): a query that uses ORDER BY

Aim Used to know about teams with their related manager, owner and ordered with

established year descending. The age of team is calculated by YEAR function which is

counted from current date.

Query

Result Showing the result

SELECT

o.owner_name,

m.manager_name,

t.team_name,

t.team_est_year,

(YEAR(CURDATE()) - t.team_est_year) AS established

FROM

(ap_team t

JOIN ap_owner o, ap_manager m)

WHERE

t.owner_id = o.owner_id

AND t.manager_id = m.manager_id

ORDER BY established DESC;


41

(2): a query that uses INNER JOINS

Aim Used to know players who plays with their national team.

Query

Result

(3): a query that uses aggregate functions

Aim Used to know what team has how many players to know which team is has the high

power of players.

SELECT

player_name,

player_nationality,

ap_team.team_name,

ap_team.team_country

FROM

ap_player

INNER JOIN

ap_team ON ap_player.player_nationality = ap_team.team_country

ORDER BY player_nationality;


42

Query

Result

(4): a query that uses GROUP BY and HAVING clauses

Aim Counted with team players to in each team which are less than total of 14. This can be

used to show the teams which are few of total players.

SELECT

t.team_name, COUNT(p.team_id) AS total_players

FROM

ap_player p,

ap_team t

WHERE

p.team_id = t.team_id

GROUP BY t.team_name;


43

Query

Result

(5): a query that uses a sub-query as a relation

Aim Used to show which players played in what position at what match. Players play in

match and they have their playing positions, and this query can show their positions with

related match.

Query

SELECT

t.team_name, COUNT(p.team_id) AS total_players

FROM

ap_player p,

ap_team t

WHERE

p.team_id = t.team_id

GROUP BY t.team_name

HAVING COUNT(p.team_id) < 14;

SELECT

p.player_id, p.player_name, mp.match_id, mp.position_id

FROM

(SELECT

*

FROM

ap_match_player_position) AS mp,

ap_player p

WHERE

p.player_id = mp.player_id;


44

Result

(6): a query that uses a sub-query in the WHERE clause

Aim Select the players who have not been played in match as they are used for extra or spare

to use for transfer player in match and query is executed with sub-query.

Query

SELECT

p.player_id, p.player_name, p.player_nrc, p.team_id

FROM

ap_player p

WHERE

p.player_id NOT IN (SELECT

player_id

FROM


GROUP BY team_id);


45

Result

(7): a query stored as a VIEW

Aim Create a view to know the result score of each team which they have from the match.

Query

CREATE OR REPLACE VIEW final_result AS

SELECT

ts.team_id, t.team_name, SUM(ts.team_score) AS team_score

FROM

(ap_team_score ts

JOIN ap_team t)

WHERE

(ts.team_id = t.team_id)

GROUP BY ts.team_id;


46

Result

(8): a query that uses a VIEW as a relation

Aim Used to calculate the skill percentage of each team calculated with each team score from

VIEW. The team on the top row of table has the highest score and skill percentage.


47

Query

Result

(9): a query that uses partial matching in the WHERE clause

SELECT

a1.team_name,

a1.team_score,

CONCAT(a1.team_score * 100 / (SELECT

SUM(team_score)

FROM

final_result),

'%') AS skill_percentage

FROM

final_result a1,

final_result a2

WHERE

a1.team_score <= a2.team_score

OR (a1.team_score = a2.team_score

AND a1.team_id = a2.team_id)

GROUP BY a1.team_id , a1.team_score

ORDER BY a1.team_score DESC , a1.team_name DESC;


48

Aim Used to show the result of player who has played in match witch match information,

player position and has the name keyword of lich, and two tables are connected to view

the result.

Query

Result

(10): a query that uses a SELF-JOIN

Aim Used self-join method to view the players who has the standard weight more than 60 Kg,

and has standard height. The player height is recorded with feet (ft.) in player table, but

this value is converted to international height unit, centimetre (cm) in query result.

SELECT

p.player_id,

p.player_name,

p.player_number,

pp.match_id,

pp.position_id

FROM

ap_player p,

ap_match_player_position pp

WHERE

p.player_id = pp.player_id

AND p.player_name LIKE '%lich%';


49

Query

Result

SELECT DISTINCT

a.team_id,

a.player_name,

a.player_weight_kg,

CONCAT((a.player_height_ft * 30.48), ' cm') AS player_height

FROM

ap_player a,

ap_player b

WHERE

a.player_height_ft > b.player_height_ft

AND a.player_weight_kg > 60

ORDER BY player_height DESC;


50

Future development report In this database system, I designed and developed for football management database system by using

RDBMS with one to one, multi sub class, and other common relationships. I used common special

database queries with functions and also trigger have looping for player placings. Views have

counting functions and also have the special timing functions of SQL are used to retrieve data.

If I will do this football management again, I want to design and develop the database system more

perfectly. The database design and tables will further be used for all web program and PC programs.

And some tables are need to complete for additional information such as logs and activities. Venues

will need to consider as single table and some other weak points on database such as player placing

and rounds need to reconsider or redesign more perfectly.


51

Self-Assessment Sheet

%

No

Attempt

to Very

Poor

Poor Fair Good Very

Good Excellent

Conceptual

Database

design (EER)

20

Relational

Schema 10

Database

Implementation 20

Views and

Queries 20

Report 15

Data Used 5

Self-

assessment 5

Demonstration

Quality 5

Totals 100


52

REFERENCES BOOKS AND JOURNALS

SQL Tutorial (2016) Available at: http://www.tutorialspoint.com/sql/ (Accessed: 20 November 2016).

In-line Citation:(SQL Tutorial, 2016)

WEBSITES

Relational database (2016) in Wikipedia. Available at:

https://en.wikipedia.org/wiki/Relational_database (Accessed: 20 November 2016). In-line

Citation:(Relational database, 2016)

keydata, 1 (2016) SQL - calculate percent to total. Available at: http://www.1keydata.com/sql/sql-

percent-to-total.html (Accessed: 20 November 2016). In-line Citation: (keydata, 2016)

SQL (structured query language) in one page: SQL.SU (no date) Available at: http://www.cheat-

sheets.org/sites/sql.su/ (Accessed: 20 November 2016). In-line Citation:(SQL (structured query

language) in one page: SQL.SU, no date)

● END OF COURSEWORK ●