Database Basics

Database Basics
From developer to developers

Database Basics
 What is a database, DBMS and its types?
 What makes a database?
 Object-Oriented Design vs. Database Design
 Database Normalization
 Structured Query Language (SQL)

What is a database?
Database Definition

What is a database?
 “A database is an organized collection of data. The data is typically
organized to model aspects of reality in a way that supports processes
requiring information”. [Wikipedia.org Definition]
 “A database provides for the storing and control of business information,
independent from (but not separate from the processing requirements of)
one or more applications”. [IBM Definition]
 “A database is a collection of information that is organized so that it can
easily be accessed, managed, and updated”. [WhatIs.com Definition]
 So, What do you think?

Database Models, Types and Formats
 Flat-file Model (Mainframes)
 Hierarchical Model (Tree-Structure, LDAP)
 Relational Model (RDBMS)
 Object-Oriented Model (Apache Derby DB, H2 and In-memory databases)
 Not Only SQL (NoSQL): Semi structured Model, Structure within data

What is a RDBMS?
 RDBMS: Relational Database Management System
 A tool for organizing, storing, retrieving, and communicating groups of
information that have similar characteristics.
 Examples are: ORACLE DB, MySQL, MS Access, MS SQL Server, IBM DB2 and
Sybase

What makes a database?
Database Objects

What makes a database?
Schema
(Owner)
Tables Views Indices Sequences Triggers Constraints Subroutines

Table
 The primary unit of physical storage for data in a database.
 Stores data, so they’re essential building blocks of any database.
 Any database consists of one or more tables (at least one)
 Contains Rows called Records and Columns called Fields.
Cell - ENTRY
Rows – RECORDS
Columns - FIELDS
ID CustomerName Email City
1 Mahmoud mahmoud@test.com Cairo
2 Samy samy@test.com Alex
3 Aly aly@test.com Aswan

View
 Views can represent a subset of the data contained in a table. Consequently,
a view can limit the degree of exposure of the underlying tables to the outer
world: a given user may have permission to query the view, while denied
access to the rest of the base table.
 Views can join and simplify multiple tables into a single virtual table.
 Views can act as aggregated tables, where the database engine aggregates
data (sum, average, etc.) and presents the calculated results as part of the
data.
 Views can hide the complexity of data. For example, a view could appear as
Sales2000 or Sales2001, transparently partitioning the actual underlying
table.
 Views take very little space to store; the database contains only the
definition of a view, not a copy of all the data that it presents.
 It can be read-only or updatable

Index
 A data structure that improves the speed of data retrieval operations on a
database table at the cost of additional writes and storage space to maintain
the index data structure.
 Used to quickly locate data without having to search every row in a database
table every time a database table is accessed.
 Can be created using one or more columns of a database table, providing the
basis for both rapid random lookups and efficient access of ordered records.
 An index is a copy of select columns of data from a table that can be
searched very efficiently that also includes a low-level disk block address or
direct link to the complete row of data it was copied from.
 The Primary Key is merely an index that enforces uniqueness

Sequence
 The sequence is a feature by some database products which just creates
unique values. It just increments a value and returns it.
 The special thing about it is: there is no transaction isolation, so several
transactions can not get the same value, the incremental is also not rolled
back.
 Sequence will allow you to populate primary key with a unique, serialized
number.
 Without a database sequence, it is very hard to generate unique incrementing
numbers.
 Other database products support columns that are automatically initialized
with a incrementing number.

Trigger
 A procedural code that is automatically executed in response to certain
events on a particular table or view in a database.
 The trigger is mostly used for maintaining the integrity of the information on
the database.
 For example, in HRMS database when a new record (representing a new
worker) is added to the employees table, new records should also be created
in the tables of the taxes, vacations and salaries.
 Can run before or after a database change.
 Can run at the cell level, row level, column level, or statement level.
 In some implementations, it can call an external program

Constraints
 It can be a single rule or a set of rules to restrict the data entered in the
table and guarantee its correctness.
 If there is any violation between the constraint and the data action, the
action is aborted by the constraint.
 Can apply to a single column or the entire table
 Can be specified when the table is created or after that
 In SQL, we have the following constraints:
NOT NULL - UNIQUE - PRIMARY KEY - FOREIGN KEY - CHECK – DEFAULT
 Advantages:
1. Input Validation
2. Data Consistency
3. Intelligent Defaults

Subroutines
 A sequence of program instructions that perform a specific task, packaged as
a unit and stored in the database.
 Can consolidate and centralize logic that was originally implemented in
applications
 Sometimes called a stored procedure (SP), function or User Defined Function
(UDF)
 Advantages:
1. Simple, no overhead
2. Avoidance of network traffic
3. Encapsulation of business logic
4. Delegation of access-rights
5. Some protection from SQL injection attacks

Database Design
In comparison with Object-Oriented Design

Entity Structure
Customer
• id: int
• name: String
• birthDate: Date
• salary: double
• jobCode: String
CUSTOMER
• C_ID: INTEGER
• C_NAME: VARCHAR(25)
• C_BIRTH_DATE: DATE
• C_SAL: DOUBLE
• C_JOB_CODE: CHAR(3)
 CUSTOMER TABLE structure can be represented by a Customer Class
 Every COLUMN is mapped to its equivalent class attribute/variable
 Data types may vary according to the database vendor / programming
language

Entity Data
ID Name Birth Date Salary Job Code
5011 Moneim Emad 03/07/1982 5,000.00 SAR
5012 Kareem Hewady 28/06/1993 3,000.00 OSD
 A single, specific occurrence of an entity is an instance.
 The selected record/row represents a single record in CUSTOMER table
 This is mapped to an instance / object of the Customer class
 The entire table data can be mapped to a list of Customer objects

Entity Relationship Diagram (ERD)
 A relationship is a link that relates two entities that share one or more attributes
 An ERD can be mapped to UML Class Diagram
 Database relations between tables can be mapped to UML association between classes
CustomerPublisher Book
Author Inventory Order

Relationship: Primary Key
5011 Moneim Emad 03/07/1982 5,000.00 SAR
 A primary key is a unique identifier of records in a table.
 A primary key values may be generated manually or automatically
 A primary key can consist of more than one column (composite key)

Relationship: Foreign Key
5011 Moneim Emad 03/07/1982 5,000.00 SAR
 A foreign key is a column reference to the primary key in its original table
 In contrast to primary key, foreign key may be repeated in the child table
ID Customer ID Location Delivery Date
1 5011 El Dokky 27/03/2015 11:45 AM
2 5011 Nasr City 28/03/2015 09:30 AM
3 5897 El Zamalek 28/03/2015 02:15 PM
ORDER (Child table)
CUSTOMER (Parent table)

Relationship Types
 One-to-one
Customer Basic info  Customer Additional Info
 One-to-many
Customer info  Customer Orders Info
 Many-to-many
Customer Info  Customer Books Interest  Books Info

Normalization
Database Best Practices

Normalization
 A set of recommendations to be followed when designing a database that
helps for organizing data elements into tables and optimizing the database.
 We will see an example for database normalization in three steps using the
three normal forms
1NF 2NF 3NF

Normalization: Case Study (Un-normalized)
SalesOrders
• SalesOrderNo
• Date
• CustomerNo
• CustomerName
• CutomerAddress
• ClerkNo
• ClerkName
• Item1Description
• Item1Quantity
• Item1UnitPrice
• Item2Quantity
• Item2UnitPrice
• Item3Quantity
• Item3UnitPrice
• Total

Normalization: Into 1NF
 Separate repeating groups into new tables.
 Start a new table for the repeating data.
 The primary key for the repeating group is usually a composite key.

SalesOrders
• SalesOrderNo
• Date
• CustomerNo
• CustomerName
• CutomerAddress
• ClerkNo
• ClerkName
• Item1Quantity
• Item1UnitPrice
• Item2Quantity
• Item2UnitPrice
• Item3Quantity
• Item3UnitPrice
• Total
• SalesOrderNo
• Date
• CustomerNo
• CustomerName
• CutomerAddress
• ClerkNo
• ClerkName
• Total
SalesOrders
OrderItems
• SalesOrderNo
• ItemNo
• ItemDescription
• ItemQuantity
• ItemUnitPrice

 Remove partial dependencies.
 Start a new table for the partially dependent data and the part of the key it
depends on.
 Tables started at this step usually contain descriptions of resources.

 Functional dependency:
The value of one attribute depends entirely on the value of another.
 Partial dependency:
An attribute depends on only part of the primary key. (The primary key must
be a composite key.)
 Transitive dependency:
An attribute depends on an attribute other than the primary key.

OrderItems
• SalesOrderNo
• ItemNo
• ItemDescription
• ItemQuantity
• ItemUnitPrice
OrderItems
• SalesOrderNo
• ItemNo
• ItemQuantity
• ItemUnitPrice
Item
• ItemNo
• ItemDescription

Normalization: Into 2NF – Problems Solved
 Duplication of data:
ItemDescription would appear for every order.
 Insert anomaly:
To insert an inventory item, you must insert a sales order.
 Delete anomaly:
Information about the items stay with sales order records. Delete a sales
order record, delete the item description.
 Update anomaly:
To change an item description, you must change all the sales order
records that have the item.

 Remove transitive dependencies.
 Start a new table for the transitively dependent attribute and the attribute it
depends on.
 Keep a copy of the key attribute in the original table.

• SalesOrderNo
• Date
• CustomerNo
• CustomerName
• CutomerAddress
• ClerkNo
• ClerkName
• Total
SalesOrders
Clerk
• ClerkNo
• ClerkName
Customer
• CustomerNo
• CustomerName
• CustomerAddress
• SalesOrderNo
• Date
• CustomerNo
• ClerkNo
• Total
SalesOrders

Normalization: Into 3NF – Problems Solved
 Duplication of data:
Customer and Clerk details would appear for every order.
 Insert anomaly:
To insert a customer or clerk, you must insert a sales order.
 Delete anomaly:
Information about the customers and clerks stay with sales order records.
Delete a sales order record, delete the customer or clerk.
 Update anomaly:
To change the details of a customer or clerk, you must change all the sales
order that involve that customer or clerk.

Normalization: Final Results
Clerk
• ClerkNo
• ClerkName
Customer
• CustomerNo
• CustomerName
• CustomerAddress
• SalesOrderNo
• Date
• CustomerNo
• ClerkNo
• Total
SalesOrders
SalesOrders
• SalesOrderNo
• Date
• CustomerNo
• CustomerName
• CutomerAddress
• ClerkNo
• ClerkName
• Item1Quantity
• Item1UnitPrice
• Item2Quantity
• Item2UnitPrice
• Item3Quantity
• Item3UnitPrice
• Total
OrderItems
• SalesOrderNo
• ItemNo
• ItemQuantity
• ItemUnitPrice
Item
• ItemNo
• ItemDescription

Structured Query Language
Database Development

SQL
 SQL is a standard language for accessing and manipulating databases.
 Stands for Structured Query Language.
 SQL can execute administrative, structural and data manipulation statements
 Administrative:
Set permissions on schemas, tables, procedures and views
 Structural:
Create, Drop or Alter tables, procedures and views
 Data Manipulation:
Retrieve data from a database
Insert, update or delete records from a database

SQL
 Although SQL is an ANSI (American National Standards Institute) standard,
there are different versions of the SQL language.
 Most of the big database vendors have their own proprietary extensions in
addition to the SQL standard.
 However, to be compliant with the ANSI standard, they all support at least the
major commands (such as SELECT, UPDATE, DELETE, INSERT, WHERE) in a
similar manner.
 SQL is NOT case sensitive: select is the same as SELECT.
 As a coding convention, we should write all SQL keywords in upper-case.
 Semicolon is the standard way to separate each SQL statement in database
systems that allow more than one SQL statement to be executed in the same
call to the server.
 Some database vendors let you choose your statement terminator character.

SQL
 SELECT - extracts data from a database
 UPDATE - updates data in a database
 DELETE - deletes data from a database
 INSERT INTO - inserts new data into a database
 CREATE DATABASE - creates a new database
 ALTER DATABASE - modifies a database
 CREATE TABLE - creates a new table
 ALTER TABLE - modifies a table
 DROP TABLE - deletes a table
 CREATE INDEX - creates an index (search key)
 DROP INDEX - deletes an index

SQL Syntax
SELECT col1_name,col2_name FROM table_name;
SELECT * FROM table_name;
 The SELECT DISTINCT statement is used to return only distinct (different) values.
SELECT DISTINCT column1_name,column2_name FROM table_name;
 The WHERE clause is used to extract only those records that fulfill a specified criterion.
SELECT col1_name,col2_name FROM table_name WHERE boolean_condition;
WHERE CITY=‘Cairo’
WHERE (CUSTOMER_ID=5011 OR CITY<>’Alex’)
WHERE CUSTOMER_ID IN(5011,5378,5834)
WHERE (PRICE>=5000 AND PRICE<10000)
WHERE CUSTOMER_NAME LIKE ’%Moneim%’
WHERE HIRE_DATE BETWEEN 2006-12-31 AND 2004-01-01

SQL Syntax
INSERT INTO table_name VALUES (value1,value2,value3,...);
INSERT INTO table_name (col1,col2,col3) VALUES (val1,val2,val3);
UPDATE table_name SET col1=val1,col2=val2 WHERE col5=val5;
DELETE FROM table_name WHERE col3=val5;
 The WHERE clause specifies which record or records that should be updated or deleted.
 If you omit the WHERE clause, all records will be updated or deleted!
 Using Aliases for tables and columns
SELECT CUSTOMER_NAME AS C_NAME FROM CUSTOMER AS C;
SELECT CUSTOMER_NAME C_NAME FROM CUSTOMER C;

SQL Syntax
 Using NOT & Wildcards
WHERE ID NOT IN (5011,5012); or WHERE PROVIDER NOT LIKE ‘%mobinil%’;
WHERE City LIKE '_erlin'; or WHERE City LIKE 'L_n_on';
 City starting with "b", "s", or "p": WHERE City LIKE '[bsp]%'
 starting with "a", "b", or "c": WHERE City LIKE '[a-c]%
 City NOT starting with "b", "s", or "p":
WHERE City LIKE '[!bsp]%'; or WHERE City NOT LIKE '[bsp]%';
WHERE Price NOT BETWEEN 10 AND 20;
WHERE ProductName BETWEEN 'C' AND 'M'; -- beginning with C,D,…,M
 Ordering Data
SELECT col1,col2 FROM table_name ORDER BY col1 ASC|DESC;-- Ascending
ORDER BY col1 ASC|DESC, col2 ASC|DESC;

SQL Syntax - JOINs
 An SQL JOIN clause is used to combine rows from two or more tables, based on a common
field between them.
 The most common type of join is: SQL INNER JOIN (simple join).
 INNER JOIN: Returns all rows when there is at least one match in BOTH tables
 LEFT JOIN: Return all rows from the left table, and the matched rows from the right table
 RIGHT JOIN: Return all rows from the right table, and the matched rows from the left table
 FULL JOIN: Return all rows when there is a match in ONE of the tables

SQL Syntax - JOINs
A B A B
A B A B
INNER JOIN LEFT OUTER JOIN
RIGHT OUTER JOIN FULL JOIN

SQL Syntax – INNER JOIN
OrderID CustomerID OrderDate
10308 2 1996-09-18
10309 2 1996-09-19
10310 1 1996-09-20
10311 1996-09-21
SELECT Customers.CustomerName, Orders.OrderID
FROM Customers [INNER] JOIN Orders
ON Customers.ID=Orders.CustomerID
ORDER BY Customers.CustomerName; CustomerName OrderID
Mahmoud 10310
Samy 10308
Samy 10309

SQL Syntax – LEFT OUTER JOIN
10308 2 1996-09-18
10309 2 1996-09-19
10310 1 1996-09-20
10311 1996-09-21
FROM Customers LEFT JOIN Orders
Aly NULL
Mahmoud 10310
Samy 10308
Samy 10309

SQL Syntax – RIGHT OUTER JOIN
10308 2 1996-09-18
10309 2 1996-09-19
10310 1 1996-09-20
10311 1996-09-21
FROM Customers RIGHT JOIN Orders
Mahmoud 10310
Samy 10308
Samy 10309
NULL 10311

SQL Syntax – FULL OUTER JOIN
10308 2 1996-09-18
10309 2 1996-09-19
10310 1 1996-09-20
10311 1996-09-21
FROM Customers FULL JOIN Orders
Aly NULL
Mahmoud 10310
Samy 10308
Samy 10309
NULL 10311

SQL Syntax - Advanced
 Using SELECT INTO
INTO CustomersOrderBackup2013
FROM Customers LEFT JOIN Orders ON Customers.ID=Orders.CustomerID;
 Using INSERT INTO SELECT
INSERT INTO Customers (CustomerName, Country)
SELECT SupplierName, Country FROM Suppliers;
 Using SQL Create
CREATE DATABASE dbname;
CREATE TABLE Persons(PersonID int NOT NULL UNIQUE,LastName varchar(255),
FirstName varchar(255),Address varchar(255),City varchar(255));

SQL Aggregate Functions
 AVG() Returns the average value
 COUNT() Returns the number of rows
 FIRST() Returns the first value
 LAST() Returns the last value
 MAX() Returns the largest value
 MIN() Returns the smallest value
 SUM() Returns the sumUsing SELECT INTO

SQL Scalar Functions
 UCASE() Converts a field to upper case
 LCASE() Converts a field to lower case
 MID() Extract characters from a text field
 LEN() Returns the length of a text field
 ROUND() Rounds a numeric field to the number of decimals specified
 NOW() Returns the current system date and time
 FORMAT() Formats how a field is to be displayed

SQL GROUP BY Statement
 The GROUP BY statement is used in conjunction with the aggregate functions
to group the result set by one or more columns.
 It can be used for summary reports
SELECT Shippers.ShipperName,COUNT(Orders.OrderID) AS NumberOfOrders
FROM Orders LEFT JOIN Shippers ON Orders.ShipperID=Shippers.ShipperID
GROUP BY ShipperName;
ShipperName NumberOfOrders
Federal Shipping 68
Speedy Express 54
United Package 74

SQL GROUP BY Statement
 Group by two columns
SELECT Shippers.ShipperName, Employees.LastName,
COUNT(Orders.OrderID) AS NumberOfOrders FROM ((Orders
INNER JOIN Shippers ON Orders.ShipperID=Shippers.ShipperID)
INNER JOIN Employees ON Orders.EmployeeID=Employees.EmployeeID)
GROUP BY ShipperName,LastName;
ShipperName Last Name NumberOfOrders
Federal Shipping Baher 38
Federal Shipping Mona 30
Speedy Express Aly 54
United Package Kareem 70
United Package Yasser 4

SQL HAVING Clause
 The HAVING clause was added to SQL because the WHERE keyword could not be
used with aggregate functions.
 Suppose that we want to find if any of the employees has registered more than 10 orders.
SELECT Employees.LastName, COUNT(Orders.OrderID) AS NumberOfOrders
FROM (Orders INNER JOIN Employees
ON Orders.EmployeeID=Employees.ID)
GROUP BY LastName
HAVING COUNT(Orders.OrderID) > 10;
Last Name NumberOfOrders
Aly 54
Baher 38
Kareem 70
Mona 30

SQL Injection
 An SQL injection can destroy your database
 SQL injection is a technique where malicious users can inject SQL commands into an SQL
statement, via web page input.
 Injected SQL commands can alter SQL statement and compromise the security of a web
application.
 txtUserId = getRequestString("UserId");
txtSQL = "SELECT * FROM Users WHERE UserId = " + txtUserId;
 UserId: 105 or 1=1
 SELECT * FROM Users WHERE UserId = 105 or 1=1
 SELECT * FROM Users WHERE UserId = 105 or ""=""
 UserId: 105; DROP TABLE SUPPLIERS
 Use SQL Parameters / PreparedStatements

References
 W3Schools.com
http://www.w3schools.com/sql/sql_default.asp
 Wikipedia.org
https://en.wikipedia.org/
 WhatIs.com
http://whatis.techtarget.com/
 IBM IMS for z/OS – Chapter 12
http://csis.pace.edu/lixin/mainframe/zos-slides/Chapter12%20Database%20slides.ppt
 North Carolina Virtual Public School – Database Fundamentals
http://www.ncvps.org/BbContent/CompApp/6411.08_Apps_1_V2%20Word/6411.08-v2-Unit-B-
5.01/Database-Fundamentals.ppt

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