7. SQL.pptx

1
ISTE 230 - INTRODUCTION TO DATABASE & DATA
MODELING
 Lifecycle Example with a Single Entity (con’t)
 SQL Introduction
 What is SQL?
 Types of Statements (So Far)
 Data Definition Language
 CREATE
 DROP
 Data Manipulation Language
 INSERT
 SELECT
 MySQL Introduction
 Viewing Metadata
 SHOW DATABASES|TABLES|CREATE TABLE
 DESCRIBE, EXPLAIN
 CREATE|DROP DATABASE
 USE
 Simple CREATE|DROP TABLE
 Data Types
 Character
 CHAR
 VARCHAR
 Numeric
 Integer
 INTEGER|INT
 Date/Time
 DATE
 PRIMARY KEY constraint
 Scripts versus Command-Line Entry
 INSERT
 SELECT Statement Introduction
 Required Clauses: SELECT and FROM
 Column Alias
 Optional Clause: WHERE
 Logical Operators (NOT, AND, OR)
 NULL values
 Finding
 Inserting
 Common Mistakes

2
Lifecycle Example: CONMAN
Is the CONTACT_INFO relation in 1NF?
 Rows contain data about tuples or instances of the relation
 Cells of the relation hold a single value (no arrays)
 Columns are attributes of the relation
 All entries in a column are of the same domain (physical and logical)
 Each column has a unique name
 The order of the attributes is unimportant
 The order of the tuples is unimportant
 No two tuples may be identical (Must have a primary key)
 No repeating groups – more than one attribute from the same physical and logical domain
(ex. author1, author2, etc)
CONTACT_INFO(contactID, firstName, middleInitial, lastName, birthday, email, url, notes)
RECAP - Step #3: Normalize Relation(s)

3
Expanded Database Development
Lifecycle
 Summary of Steps
1. Create a Data Model from gathered requirements.
 Entity-Relationship Model
2. Transpose Data Model into Relation(s)
3. Normalize Relations
4. Create the Relational Schema within Database Management System. (Metadata)
 Create the database
 Create the table(s)
5. Define forms, queries, reports, menus, if supported within DBMS or external application
programs. (Application Metadata)
 Will not be covered in this course
6. Populate with User Data
 The process and who is responsible (you or system users) depends on situation
7. Maintenance
 Change happens…expect it…plan for it as best you can!
 User Needs, DBMSs, Hardware

4
DBMS - INDEPENDENT
DBMS - SPECIFIC
UoD
HIGH-LEVEL or conceptual level
(e.g., E-R diagram)
LOW-LEVEL or physical level
(e.g., file layouts/structures,
indexing, OS access strategies)
DBMS
REPRESENTATIONAL level
which (to access the data), uses
the ...
DBMS software
(Relational Model)

5
Step #4: Create Relational Schema
within DBMS
 Use a data access language within the DBMS to create metadata
 In the late 70s and early 80s, each manufacturer used their own language
 In 1986, American National Standards Institute (ANSI) embraced IBM’s Structured English
Query Language (SEQUEL) and transformed it into what is now Structured Query
Language (SQL)
 Since then, ANSI has released the following standards:
 SQL-89
 SQL-92
 SQL:1999
 SQL:2003
 SQL:2006
 SQL:2008
 SQL:2011
 SQL:2016

6
SQL Statement Categories (So Far…)
 Data Definition Language (DDL)
 Deals primarily with metadata
 CREATE…
 DROP…
 Data Manipulation Language (DML)
 Deals primarily with user data
 INSERT
 SELECT
 Transaction Control Language (TCL)
 Also referred to as Data Control Language
 Commit
 Rollback

7
SQL
 Today, SQL is used by many commercial DBMS
products:
DB2 Oracle Informix
Sybase SQLServer Access
 Each manufacturer adds additional “features” to
differentiate their product (danger!)

8
The DBMS for this course: MySQL
 MySQL is the most popular Open Source database
 Developed by MySQL AB and now Oracle
 Commonly found in web applications
 Could also be used as a departmental database server
 Does not have all the features of a corporate database like
Oracle
 You will be expected to use only the command-line
interface for all work in this course.

9
Commands to View Metadata
SHOW DATABASES;
 Shows the databases on the system
SHOW TABLES;
 Shows the tables in the current database
DESCRIBE tableName;
 Shows some of the metadata maintained for the
specified table
 DESC tableName;
 EXPLAIN tableName;
 SHOW COLUMNS
FROM tableName;
SHOW CREATE TABLE tableName;
Shows the create table statement for the specified table

10
Lifecycle
7. Maintenance

11
DDL: CREATE|DROP DATABASE
 To create a database:
 General Syntax Format: CREATE DATABASE databaseName;
 Example: CREATE DATABASE test;
 To remove a database:
 General Syntax Format: DROP DATABASE databaseName;
 Example: DROP DATABASE test;
 Can add IF EXISTS to prevent the DROP DATABASE from executing if the
database does not exist.
 Example: DROP DATABASE IF EXISTS test;

12
USE command
 Once a MySQL database is created, it isn’t automatically opened
for access within the session
 “Open” a database through USE command
 General Syntax Format: USE databaseName;
 Example: USE test;
 Only one MySQL database can be opened at a time in a session
 To open a different database in the session, execute a USE
command

13
 CREATE DATABASE conman;
 What command can be entered to verify that the conman
database has been created?
 USE conman;
 What command can be entered to see if the system created any
tables in the database by default?
Step #4a: Create the Database
You have now created the database and it will remain on the computer until it
is deleted.

14
Lifecycle
7. Maintenance

15
Attribute Data Types (So Far…)
Character
CHAR(size) –fixed-length string
VARCHAR(size) –variable-length string
Numeric
Integer
INT or INTEGER
Date/Time
DATE
YYYY-MM-DD

16
What is a constraint?
A constraint is a rule limiting the values
allowed for an attribute
A PRIMARY KEY is one example
Each value must be unique
A value must be specified; NULL values are not
allowed
There are other constraints that protect
data integrity
Constraints are specified in the CREATE
TABLE statement

17
DDL: CREATE|DROP TABLE
 To create a table within the current database (based on USE command)
 Syntax Format (so far):
CREATE TABLE tableName(
attribute1 DATATYPE,
attribute2 DATATYPE,
…,
CONSTRAINT tableName_pk PRIMARY KEY (primary_key_attribute(s))
) ENGINE=InnoDB DEFAULT CHARSET=utf8;
 Example:
CREATE TABLE employee(
employeeID CHAR(11) COMMENT “employeeID will be constrained to be the primary key”,
ssn CHAR(11),
name VARCHAR(35),
dob DATE,
CONSTRAINT employee_pk PRIMARY KEY(employeeID) <-without a primary key constraint
) ENGINE=InnoDB DEFAULT CHARSET=utf8; duplicate records could occur
What command(s) can be executed to view the table’s metadata? To view the CREATE TABLE statement?
 To remove a table within the current database
 DROP TABLE tableName;

18
MySQL Scripts
 MySQL allows you to specify more than one SQL statement at a time
 Always use a semi-colon at the end of the statement
 MySQL also allows you to run SQL statements that are contained in a text
file (also known as a script file)
 Executing a script file has advantages over typing statements at the
command line
 Typos are easily corrected
 Scripts can be saved and reused
 Commenting can be included
 -- single line comment (space MUST be included after --)
 # single line comment
 /* block comment (can span multiple lines) */
 COMMENT “Comment within an attribute specification”
 See COMMENT for employeeID on previous slide

19
MySQL Scripts
mysql>. c:230somestuff.sql
command Full File Path
space
No semi-colon
mysql>SOURCE c:230somestuff.sql
Or

20
 Execute a CREATE TABLE STATEMENT
 Script: createCONTACT_INFO.sql
 MyCourses, Content
 What command can be entered to verify that the contactInfo
table has been created?
 What command can be entered to view the metadata of the
contactInfo table?
Step #4b: Create the Tables

21
Lifecycle
7. Maintenance

22
DML: INSERT
 Adds user data to a table
 The INSERT statement typically adds one record at a time
 Most DBMS packages also have a bulk insert capability (e.g., Oracle has
SQLLoader)
 General Syntax Format:
INSERT INTO tableName
(fieldlist) VALUES (valuelist);
 tableName is the name of the table we’re adding to
 fieldlist is a comma-separated list of attribute names
 Provides a template so that the DBMS engine know which attributes you are
specifying values for and what attribute order the values will be given in
 valuelist is a comma-separated list of values to be added for the
attribututes listed in the fieldlist

23
INSERT Shortcut
INSERT INTO employee
(employeeID, ssn, name, dob)
VALUES('11111111111',
'121-21-2121', 'Jason Jones',
'1990-10-31');
VALUES( '22222222222',
'342-56-2454',
'Lisa Kellog',
'1984-01-15');
You may specify only the
values if you know
the correct order of the
attributes in the table AND
will be specifying a value for
each attribute.

24
INSERT Shortcut
WRONG!
CORRECT
When using the shortcut and attributes are NOT specified,
ALL values must be specified in the CORRECT ORDER.
VALUES('12345678901','254-67-4563');
INSERT INTO employee (employeeID,
ssn) VALUES('12345678901',
'254-67-4563');

25
 Shows user data in a table
 Basic Syntax:
SELECT *| attributes_to_include
FROM tableName;
 Examples:
SELECT *
FROM employee;
SELECT name
FROM employee;
SELECT NAME, DoB, employeeID
FROM employee;
SELECT Name, dob AS "Date of Birth"
FROM employee;
DML: SELECT
Column Alias

26
 Execute INSERT statements
 Script: insertCONTACT_INFO.sql
 MyCourses, Content
 What statement can be executed to view the user data in the
contactInfo table?
Step #6: Populate database with User Data

27
SELECT: WHERE clause
 Allows the limitation of records that appear in the result set based
on condition(s) specified
 Basic Syntax:
FROM tableName
WHERE condition(s);
 Example: Please show the all the data from employee for the
employee with an ID of 12345678901.
SELECT employeeID, ssn, name, dob
FROM employee
WHERE employeeID='12345678901';

28
Logical Operators
 NOT – reverses the result
 Example: Please show the all the data from employee for every employee, except for the
employee with an ID of 12345678901.
SELECT employeeID, ssn, name, dob
FROM employee
WHERE NOT employeeID= '12345678901';
 AND – Conditions on both sides must evaluate to true to be in result set
 Example: Please show name of the employee with an ID of 11111111111 and a date of birth of
1984-01-05.
SELECT name
FROM employee
WHERE employeeID='11111111111' AND dob='1984-01-05';
 OR – One or both conditions must evaluate to true to be in result set
 Example: Please show name of employees with an ID of 11111111111 or a date of birth of 1984-
01-05.
SELECT name
FROM employee
WHERE employeeID='11111111111' OR dob='1984-01-05';

29
NULL values
 Means unknown or nothing
 Does NOT mean and empty string('') or a string of a space (' ')
 Example: How to find NULL values
SELECT employeeID
FROM employee
WHERE name IS NULL;

30
Inserting NULL values
 To see if NULLs are allowed for an attribute, DESCRIBE the table it
is in
 Can be used with or without field list
 Examples:
INSERT INTO employee (employeeID, ssn, name)
VALUES('33333333333', '098-76-5432', NULL);
INSERT INTO employee VALUES('44444444444',
'555-44-3333', NULL, null);

31
Common Mistakes with NULL
 INSERT INTO employee VALUES('77777777777',
'656-56-5656','', NULL);
'444-99-1111',' ', NULL);
'777-55-0909','NULL', NULL);
 SELECT * FROM employee WHERE name ='';
 SELECT * FROM employee WHERE name = ' ';
 SELECT * FROM employee WHERE name = 'NULL';

32
Constraints (So far…)
 PRIMARY KEY – constrains the attribute(s) to be the primary key
(unique, not null)
 Can be attribute or table level
 NOT NULL – a value is required to be entered
 Attribute level only
 CHECK – proposed value must meet specified conditions
 Can be attribute or table level
 DEFAULT – a value to be entered when a value is not specified
 Attribute level only

33
Data Integrity Checks
Two main types of data integrity checks:
 “atomic” checks that look at the proposed field value
 NOT NULL
 CHECK (if validation only refers to itself)
 “relative” checks that compare the proposed field value to other data
 UNIQUE
 CHECK (if validation refers to other attribute(s))
We say “proposed field value” because the data
check happens before the value goes into the
database

34
Naming Constraints
Other than field names and data types, everything
we’ve discussed is called a “constraint”
Each table-level constraint can be given a name
This allows us to refer to the constraint later
For Primary Key constraint: tablename_pk

35
Example
CREATE TABLE film (
filmID INT,
title VARCHAR(255) NOT NULL,
description varchar(1000),
releaseYear SMALLINT,
length SMALLINT UNSIGNED,
replacementCost DECIMAL(5,2) NOT NULL DEFAULT 19.99,
rating VARCHAR(5) NOT NULL,
CONSTRAINT film_pk PRIMARY KEY (filmID),
CONSTRAINT film_replacementCost_ck CHECK (replacementCost > 9.99)
) ENGINE=InnoDB DEFAULT CHARSET=utf8;

36
SELECT Statement - Review
 Shows user data in a table
 Basic Syntax (Required clauses):
FROM tableName;
 Basic Syntax (with optional clauses discussed so far):
FROM tableName
WHERE condition(s);

37
WHERE Clause
Relational Operators
 > Greater Than
 >= Greater Than or Equal To
 < Less Than
 <= Less Than or Equal To
 = Equal To
 <> Not Equal To
 != Not Equal To
 IN (list) Contained in comma-separated list
 LIKE string Matches string pattern

38
Logical Operators
Review:
 NOT – reverses the result
 AND – Conditions on both sides must evaluate to true to be in
result set
OR – One or both conditions must evaluate to true to
be in result set
BETWEEN – will include values that are greater than, or
equal to, the minimum value and less than, or equal to,
the maximum value specified
SELECT *|attribute(s)
FROM table
WHERE attribute BETWEEN min_value AND max_value;

39
LIKE: Pattern Matching
 To specify our pattern we use characters and wildcards
 Characters must be present
 Wildcards are placeholders for characters
 _ means exactly 1 character
 % means 0 or more characters

40
Calculations
 Calculations can be performed in the SELECT clause of a SELECT
statement
 Example:
 Show the title of each film, the total length in minutes, as well as in hours and
minutes.
SELECT title, length, TRUNCATE(length/60, 0), length MOD 60
FROM film;
SELECT title, length AS ‘Total Minutes’, TRUNCATE(length/60,0) AS “Hours”,
length MOD 60 AS “Minutes”
FROM film;

41
SQL Statement Categories (So Far…)
 Data Definition Language (DDL)
 Deals primarily with metadata
 CREATE…
 DROP…
 ALTER …
 Data Manipulation Language (DML)
 Deals primarily with user data
 INSERT
 SELECT
 UPDATE
 DELETE

42
DML: UPDATE
 Modifies existing user data
UPDATE tableName
SET field1 = value1, …, fieldN = valueN
WHERE condition; <- WHERE clause is optional
 tableName is the name of the table we’re updating
 condition is an expression to limit which records are updated
 field1…fieldN are the names of the fields to be updated
 value1…valueN are the new values
Example:
UPDATE film
SET replacementCost = replacementCost +5
WHERE replacementCost=9.99;

43
DML: DELETE
 Removes record(s) from a table
DELETE
FROM tableName
WHERE condition(s); <- WHERE clause is optional
 tableName is the name of the table we’re deleting records from
 condition is an expression to limit which records are deleted (similar to
WHERE in the SELECT statement)
 Without WHERE all data is deleted from the table
 Example:
DELETE
FROM film
WHERE rating=‘R’;

44
ALTER TABLE
Now that you can create a table, if you need to change
the structure, you can alter it instead of dropping and
creating again.
Databases are no different than programs
 Version 1 is just the starting point
 There will be many versions as time goes on
 There are lots of changes that can be made through ALTER TABLE.
The syntax is shown in MySQL Help System
 https://dev.mysql.com/doc/refman/8.0/en/alter-table.html

45
What to Alter?
You can use the ALTER TABLE statement to:
Add/Drop a primary key constraint
Add/Modify/Drop a column
Add/Drop/Modify a default value
You cannot modify a table level constraint…

46
Altering Primary Key
Let’s get rid of the PRIMAY KEY constraint:
ALTER TABLE film
DROP PRIMARY KEY;
Add it back
ALTER TABLE film
ADD PRIMARY KEY film_pk (filmID);

47
ADD|DROP Columns
General Syntax Format:
ALTER TABLE tableName
{ADD|DROP} COLUMN columnspec;
Example: What if we wanted to add a “URL”
column to the film table:
ALTER TABLE film
ADD COLUMN url VARCHAR(50);
Example: What if we wanted to remove the
replacement cost from the film table:
ALTER TABLE film
DROP COLUMN replacementCost;

48
Altering Defaults
Defaults are the only “property” you can alter.
We will see in the next slide how to change data types.
Let’s add a default value of ‘Not entered.’ to the
description column in the table:
ALTER TABLE film
ALTER description SET DEFAULT ‘Not entered.’;
And if we change our mind and don’t want it after all:
ALTER TABLE film
ALTER description DROP DEFAULT;

49
ALTER TABLE…MODIFY COLUMN
 Through the ALTER TABLE…MODIFY statement, you can edit an existing attribute’s
specification including changing the data type or adding/removing a not null constraint
or default value
 ALTER TABLE tableName
 MODIFY attribute DATATYPE [NOT NULL] [DEFAULT];
 CHANGE (instead of modify) can also be used:
CHANGE currAttrName newAttrName newDATATYPE;
Read more: https://dev.mysql.com/doc/refman/8.0/en/alter-table.html
 Note that we need to state the FULL attribute specification, not just what
we want to change
Example: Let’s modify releaseYear to require a value and set a
default value to 2020.
ALTER TABLE film
MODIFY COLUMN releaseYear SMALLINT NOT NULL DEFAULT 2020;

50
Storing an Output Table
 Check out to how to CREATE TABLE from SELECT.
 https://dev.mysql.com/doc/refman/8.0/en/create-table-select.html

51
MISC
 To clear the screen in the MySQL command prompt:
 mysql> system cls;
 To log results, use T as follows:
 mysql> T <fullLogFilePath.txt>
 To check which database is being used
 mysql> SELECT DATABASE();
 To create a table from the result of a SELECT statement:
 CREATE TABLE IF NOT EXISTS destTblName
 SELECT … FROM …;
 Remember to precede it with “DROP TABLE IF EXISTS tblName” if you want to
store an update result of SELECT.

53
MySQL Workbench
 Start  MySQL Installer

55
MySQL Workbench
 Execute current statement: Ctrl + Enter
 Execute all statements: Ctrl + Shift + Enter
 File  Open SQL Script
 Edit  Format
 Edit  Preferences  SQL Editor  Query Editor  “Use UPPERCASE
keywords on completion”

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