Database

Tools

• mySQL

MySQL Datatypes

Ty p e	S i z e	D e s c r i p t i o n
CHAR[Length]	Length bytes	A fixed-length field from 0 to 255 characters long.
VARCHAR(Length)	String length + 1 bytes	A fixed-length field from 0 to 255 characters long.
TINYTEXT	String length + 1 bytes	A string with a maximum length of 255 characters.
TEXT	String length + 2 bytes	A string with a maximum length of 65,535 characters.
MEDIUMTEXT	String length + 3 bytes	A string with a maximum length of 16,777,215 characters.
LONGTEXT	String length + 4 bytes	A string with a maximum length of 4,294,967,295 characters.
TINYINT[Length]	1 byte	Range of -128 to 127 or 0 to 255 unsigned.
SMALLINT[Length]	2 bytes	Range of -32,768 to 32,767 or 0 to 65535 unsigned.
MEDIUMINT[Length]	3 bytes	Range of -8,388,608 to 8,388,607 or 0 to 16,777,215 unsigned.
INT[Length]	4 bytes	Range of -2,147,483,648 to 2,147,483,647 or 0 to 4,294,967,295 unsigned.
BIGINT[Length]	8 bytes	Range of -9,223,372,036,854,775,808 to 9,223,372,036,854,775,807 or 0 to 18,446,744,073,709,551,615 unsigned.
FLOAT	4 bytes	A small number with a floating decimal point.
DOUBLE[Length, Decimals]	8 bytes	A large number with a floating decimal point.
DECIMAL[Length, Decimals]	Length + 1 or Length + 2 bytes	A DOUBLE stored as a string, allowing for a fixed decimal point.
DATE	3 bytes	In the format of YYYY-MM-DD.
DATETIME	8 bytes	In the format of YYYY-MM-DD HH:MM:SS.
TIMESTAMP	4 bytes	In the format of YYYYMMDDHHMMSS; acceptable range ends inthe year 2037.
TIME	3 bytes	In the format of HH:MM:SS
ENUM	1 or 2 bytes	Short for enumeration, which means that each column can haveone of several possible values.
SET	1, 2, 3, 4, or 8 bytes	Like ENUM except that each column can have more than one ofseveral possible values.

SQL Client

• Part 1

mysql> show databases;

mysql> create database test_db;

mysql> show databases;

mysql> use test_db;

mysql> show tables;

mysql> create table users (
       user_id INT,
       name VARCHAR(50),
       dob DATE,
       mobile_number INT,
       ic_number INT
);

// show table fields design
mysql> describe users;

// add new column
mysql> alter table users add verify INT;

// delete column
mysql> alter table users drop column verify;

// modify field type
mysql> alter table users modify column verify varchar(100);

// insert record into table
mysql> insert into users (user_id, name, mobile_number)
       values (123, 'dixant', 9988222);

// dob in yyyy-mm-dd
mysql> insert into users (user_id, name, mobile_number, dob)
       values (123, 'dixant', 9988222, '1975-12-01');

// add multiple records
mysql> insert into users (user_id, name, mobile_number)
       values (125, 'john', 99882221), (126, 'harry', 99882223);

// view table records
mysql> select * FROM users

//update a record
mysql> update users set dob = '1976-01-01' where user_id = 123;

// delete record
mysql> delete from users where dob > '1976-01-01';

// create new database
mysql> create database ntuc;

mysql> use ntuc;

// create grocery table
mysql> create table grocery (
         tag INT,
         name VARCHAR(100),
         brand VARCHAR(100),
         price DECIMAL(10,2),
         quantity INT
);

// rename table
mysql> alter table grocery rename to store;

• Part 2

// open database
mysql> use ntuc;

// import script from .sql file
mysql> source C:\...\data.sql

mysql> show tables;

// queries filter order by ascending order
mysql> select * from customer where customer_wallet > 5000 order by customer_wallet order by asc;

// order by wallet then tolerance
mysql> select * from customer where customer_wallet > 5000 order by customer_wallet desc, customer_tolerance order by asc;

// only display name& email order by wallet then tolerance
mysql> select customer_name, customer_email from customer where customer_wallet > 5000 order by customer_wallet desc, customer_tolerance order by asc;


/// nested queries select within select
mysql> select customer_name from 
        (select * from customer where customer_wallet > 3000) as temp
        where customer_tolerance > 0.5;

// filter using IN clause
mysql> select * from customer where customer_tolerance IN (0.5, 0.6, 0.7);

mysql> select * from customer where custome tolerance 
        IN (select customer_tolerance where customer_tolerance < 0.8);

// ans for exercise
mysql> select * from transaction where customer_id
       in (select customer_id from customer where customer_tolerance < 0.7);        
///

• common functions
  • COUNT
  • SUM
  • AVG
  • MAX
  • MIN

// sum
mysql> select SUM(customer_wallet) from customer;

// average
mysql> select AVG(customer_wallet) from customer;

/// number of records
mysql> select COUNT(customer_wallet) from customer;

• Others functions

  • CURRENT_DATE
  • Complete List

• Group By Clause

// group and sum by type..
mysql> select customer_type, sum(customer_wallet) from customer group by customer_type;

// exclude type 2
mysql> select customer_type, sum(customer_wallet) from customer 
    where customer_type <> 2
    group by customer_type;

• LIMIT Clause
  • limit the number of record to return

// show onlt first 5 records
mysql> select * from customer limit 5;

• LIKE Clause
  • pattern match
  • wildcard
    • % : substitute any number of character
    • _ : substitute only one character

// show name start with Z
mysql> select * from customer where customer_name LIKE 'Z%';

• UNION Clause
  • combine data from different table
  • performance optimisation

mysql> select customer_id from customer
        UNION
        select transaction_id from transaction;

mysql> select seller_name as name from seller 
    UNION select product_name from product;

// in comparison with OR, UNION is better performance
mysql> select customer_name from customer where customer_wallet = 6000 UNION
      select customer_name from customer where customer_wallet = 8000;

• INNER JOIN clause
  • aggregates data from different tables

// join [transaction] and [customer] table
mysql> SELECT transaction.transaction_id, transaction.transaction_datetime, customer.customer_name 
       FROM transaction
       INNER JOIN customer 
       ON customer.customer_id = transaction.customer_id;

// alias AS to simplify
mysql> SELECT t.transaction_id, t.transaction_datetime, c.customer_name 
       FROM transaction AS t 
       INNER JOIN customer AS c 
       ON c.customer_id = t.customer_id;

• LEFT JOIN clause
  • return data from first table

// alias AS to simplify
mysql> SELECT t.transaction_id, t.transaction_datetime, c.customer_name 
       FROM transaction AS t 
       LEFT JOIN customer AS c 
       ON c.customer_id = t.customer_id
       GROUP BY c.customer_id;

mysql> SELECT c.customer_name, t.transaction_id, t.transaction_datetime
       FROM customer AS c 
       LEFT JOIN transaction AS t 
       ON c.customer_id = t.customer_id
       GROUP BY c.customer_id;

• RIGHT JOIN clause
  • return data from first table

mysql> SELECT t.transaction_id, t.transaction_datetime, c.customer_name 
       FROM transaction AS t 
       RIGHT JOIN customer AS c 
       ON c.customer_id = t.customer_id;

• OUTER JOIN clause

  • 3 types
    • LEFT OUTER JOIN
    • RIGHT OUTER JOIN
    • FULL OUTER JOIN

• INDEX clause

  • speed up search queries

mysql> CREATE INDEX 
       ON ;

• PRIMARY KEY clause
  • constraint to force unique values

mysql> CREATE TABLE table1( 
       COL1 INT
       COL2 INT)
       PRIMARY KEY (COL1);

//
mysql> ALTER TABLE Persons
ADD PRIMARY KEY (ID);       

• FOREIGN KEY clause *

mysql> ALTER TABLE table2
       ADD FOREIGN KEY (COL2) REFERENCE table1(COL2);

Practical Exercise #4

Trial Result

// Q1
mysql> SELECT t.transaction_id, t.transaction_datetime, c.customer_name 
       FROM transaction AS t 
       INNER JOIN customer AS c 
       ON c.customer_id = t.customer_id;

// Q2
mysql> select customer_id, max(transaction_datetime) from transaction group by customer_id;

// Q3
mysql> select seller_id, avg(transaction_amount) from transaction group by seller_id;

mysql> select s.seller_id, s.seller_name, avg(t.transaction_amount) FROM seller AS s
        RIGHT JOIN transaction AS t
        ON s.seller_id = t.seller_id
        GROUP BY s.seller_id;

Model Answers

// Q1
mysql> select c.customer_name, t.transaction_datetime from customer as c left join transaction as t on c.customer_id = t.customer_id;


// Q2
mysql> select c.customer_name, max(t.transaction_datetime) from customer as c left join transaction as t on c.customer_id = t.customer_id group by c.customer_id;


// Q3
mysql> select s.seller_name, avg(t.transaction_amount) from seller as s left join transaction as t on s.seller_id = t.seller_id group by s.seller_id;

Data mock tools

• mockaroo
• generatedata

Using MySQL Shell

1. Switch to SQL mode

MySQL JS> \sql

// connect data
MySQL JS> \connect root@localhost:3306

// proceed with normal sql command
MySQL localhost:3306 ssl SQL> show databases;

// open ntuc db
MySQL localhost:3306 ssl SQL> use ntuc;

// show tables in ntuc
MySQL localhost:3306 ssl SQL> show tables;

// show store_test table description
MySQL localhost:3306 ssl SQL> describe store_test;

// display table records
MySQL localhost:3306 ssl SQL> select * from store_test;

Generate sql Dump data

1. Windows command prompt. Execute below command

// change to MySQL binary folder
C:\> "C:\Program Files\MySQL\MySQL Server 8.0\bin\mysqldump.exe" -u root -p nusbank > d:/nusbank.sql

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