This document provides an overview and summary of key concepts related to advanced databases. It discusses relational databases including MySQL, SQL, transactions, and ODBC. It also covers database topics like triggers, indexes, and NoSQL databases. Alternative database systems like graph databases, triplestores, and linked data are introduced. Web services, XML, and data journalism are also briefly summarized. The document provides definitions and examples of these technical database terms and concepts.

1. ADVANCED DATABASES
REVISION 1

2. REVISION TACTICS
• Watch the videos from emails and moodle
• Take notes
• Follow these slides
• Visit the web resources
• Learn the keywords and concepts
• Learn SQL
• Use Cmap tools to link concepts /t erms
• Revisit your patchwork

3. THE BUILDING BLOCKS
TERMS AND CONCEPTS YOU SHOULD KNOW BY NOW…
• XML • NoSQL
• Graph • ODBC
• Relational Database • MySQL
• SQL
• Linked Data
• RDF
• Trigger
• Database Index

4. REVISION TOOL: CMAP TOOLS
• http://cmap.ihmc.us/download/
• Tool for creating concept maps

5. TOPICS
• Relational Databases (MySQL)
• SQL
• Triggers
• Transactions
• Webservices
• XML
• NoSQL / Alternative Database systems

6. RELATIONAL DATABASES
MYSQL

7. RELATIONAL DATABASES
‘FORMALLY DESCRIBED TABLES’
• This module focused on MySQL: an Open source
implementation of a relational database
• Oracle, PostgreSQL, SQLite
• Most patchworks should be done in MySQL
(Triggers, indexs)
• ODBC Component
• Looked at alternatives: NoSQL (Not Only
SQL), Graph Database, triplestore

8. RELATIONAL DATABASES: SQL
(STRUCTURED QUERY LANGUAGE)
• Language to manage data in relational
management systems
• Should be examples in your patchwork
CREATE TABLE example_autoincrement (
id INT NOT NULL AUTO_INCREMENT PRIMARY KEY, data VARCHAR(100)
);

9. RELATIONAL DATABASES
TRANSACTIONS

10. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE
MANAGEMENT SYSTEM’
• A transaction is a unit of work
• Treated independently of each other

11. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE MANAGEMENT SYSTEM’
• In a relational database each transaction must have
ACID properties
• Proposed in 1970s
• Key idea in relational databases
• Atomicity
• Consistency
• Isolation
• Durability
• A transaction need to reach these 4 goals to be reliable

12. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE MANAGEMENT SYSTEM’
• Atomicity
• All or Nothing
• both pay for and reserve a seat; OR neither pay for nor
reserve a seat.
• Consistency
• Only ever writes valid data
• Isolation
• Transactions will not interfere with each other
• Durability
• Once a transaction is complete it will always remain. Even
in the event of a powerloss

13. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE MANAGEMENT SYSTEM’
• Sometimes we can’t use ACID
• CAP THEORY
• A theory by Eric Brewer in 2000
It is only possible to have 2 of the following in a
distributed computer system
• Consistency
• Availability
• Partition Tolerance

14. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE
MANAGEMENT SYSTEM’
• Consistency
All the nodes in the distributed system have the same
system
• Availability
A guarantee that every requests get a response
(even if it fails)
• Partition tolerance
If a node fails then the whole system will continue to
operate

15. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE MANAGEMENT
SYSTEM’
• So what do large companies/distributed computer
systems do?
• Use alternatives to ACID
• Most popular alternative to ACID is BASE
• Basic Availability
• Soft State
• Eventual Consistency
For when it’s OK to use stale data, and it’s OK to give
approximate answers.
http://www.cs.berkeley.edu/~brewer/cs262b-2004/PODC-keynote.pdf

16. TRANSACTIONS
‘UNIT OF WORK PERFORMED WITHIN A DATABASE
MANAGEMENT SYSTEM’
• Basically Available
• Availability is achieved through multiple data stores rather
than one fault tolerant system
• Soft state
• Consistency is abandoned, or at least is the problem of the
application and not the database
• Eventual Consistency
• At some point in the future data will converge so that data
on nodes is in a consistent state

17. RELATIONAL
DATABASES: ODBC
OPEN DATABASE CONNECTIVITY

18. RELATIONAL DATABASES: ODBC
OPEN DATABASE CONNECTIVITY
• Standard database access method
• SQL Access group
• Independent of database system
http://shivasoft.in/blog/microsoft/csharp/what-is-odbc-and-oledb-interview-
question/

19. RELATIONAL DATABASES:
TRIGGERS
• SQL statement or SET of statements fired when an event
occurs. (for example INSERT, UPDATE and DELETE)
CREATE
TRIGGER `event_name` BEFORE/AFTER
INSERT/UPDATE/DELETE
ON `database`.`table`
FOR EACH ROW BEGIN
-- trigger body
-- this code is applied to every
-- inserted/updated/deleted row
END;
http://www.sitepoint.com/how-to-create-mysql-triggers/

20. DATABASE INDEX
• improves the speed of data retrieval operations
• Stops searching through each row one by one
• Created on columns
• Most Common
• B-tree (MySQL default?)
• Hash
Really good -> http://20bits.com/article/interview-questions-database-indexes
http://dev.mysql.com/doc/refman/5.5/en/index-btree-hash.html

21. B TREE INDEXING
• B-Tree
• Stores data in logical way
• We want people younger than 13.. Look left

22. INDEXS
• Hash Tables
• Speeds up = or <=>
• Not > or <
B-tree vs Hash Tables
http://dev.mysql.com/doc/refman/5.5/en/index-btree-hash.html

23. WEBSERVICE

24. WEBSERVICE
• A way to communicate between systems (machine
to machine interaction)
• Service Provider
• Service Requester

25. WEB SERVICES
• 3 types of nodes
• Registries (Service Broker)
• Providers
• Requesters

26. XML
• XML:
• EXtensible Markup Language
• Designed to store and transport data
• (whereas html was designed to display data)
http://www.w3schools.com/xml/xml_whatis.asp

27. WEB SERVICES
ADVANTAGES
• Advantages
• Work outside of private networks
• Interoperability
• Could be the content processing/logic module in Three-tier
architecture?

28. WEB SERVICES
DISADVANTAGES
• Availability?
• Based in a stateless (unreliable?) protocol :http
• Security?

29. NOSQL

30. NOSQL
• Not Only SQL
• Databases that are not like relational database
management systems
• Not built around the idea of tables
• Not likely to use SQL
• Usually built around BASE style principles (not ACID)
• Examples : Graph Databases

31. GRAPH DATABASE
• Every Element has a pointer to another element

32. TRIPLE STORE
• Similar to Graph Data
• Built to store and retrieve triples (David eats
chocolate bars, Mars is a chocolate bar, etc etc)
• Data is stored in a standardized way (such as
RDF/XML)
• Has a querying service (sparql)

33. LINKED DATA
• Method of publishing structured data
• Different datasets can be interlinked
• Built on the following technologies
• URI’s
• HTTP
• Structured formats RDF/XML
• Sometimes this data is stored in triplestores
• Served by website (content negotiation)
• Like prod.cetis.ac.uk
• Could have a relational database behind it
• Example: dbpedia

34. LINKED DATA
• Linked Data is made up of triples!
• Subject, predicate object
• David -> eats -> cake
• David (Subject) Eats (Predicate) Cake

35. DATA JOURNALISM
• Explosion of visual analytic tools
• Gephi
• Visualise a network/graph
• Visually Identify complex patterns / markets