Download Introduction to Database Systems

Principles of Data Management
Syllabus & Intro
Welcome!

Course website:
 http://cis-linux1.temple.edu/~edragut/CIS5516Spr16/teaching.htmImportant Pre-Req
Text Book(s)
 Workload
 Intended Schedule
 Projects

 Grading

Reading List
What Is a DBMS?
A very large, integrated collection of data.
 Models real-world enterprise.
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


Entities (e.g., students, courses)
Relationships (e.g., Madonna is taking CS564)
A Database Management System (DBMS) is a
software package designed to store and
manage data.
Files vs. DBMS
Application must stage large datasets
between main memory and secondary
storage (e.g., buffering, page-oriented access,
32-bit addressing, etc.)
 Special code for different queries
 Must protect data from inconsistency due to
multiple concurrent users
 Crash recovery
 Security and access control

Why Use a DBMS?
Data independence and efficient access.
 Reduced application development time.
 Data integrity and security.
 Uniform data administration.
 Concurrent access, recovery from crashes.

Why Study Databases??

Shift from computation to information
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
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at the “low end”: scramble to webspace (a mess!)
at the “high end”: scientific applications
Datasets increasing in diversity and volume.



?
Digital libraries, interactive video, Human
Genome project, EOS project
... need for DBMS exploding
DBMS encompasses most of CS

OS, languages, theory, AI, multimedia, logic
A Brief DB History

Early 1970s
 Many database systems
 Incompatible, exposing many implementation details

Then Ted Codd came along
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Relational model
Structured Query Language (SQL)
Implementation differences became irrelevant
A few major DB systems dominated the market
Then Web 2.0 & 3.0, Big Data Happen
 What
do you think happen?
 Semi-structured data happen.
•A lot of it and in many forms…
Some Facts about Web x.0 and Big
Data



Twitter: 255 million monthly active users and 500
million Tweets are sent per day,
Facebook: over 1 billion monthly users and faces 3
million message per 20 minute
Instagram: 200 Million Monthly Active Users and 1.6
Billion Likes and 60 Million Photos shared every day
Database Systems Landscape Nowadays
Somebody, Please, Bring Some
Order to This Madness – Cont’d
Somebody, Please, Bring Some
Order to This Madness – Cont’d

NoSQL Databases
Somebody, Please, Bring Some
Order to This Madness




Different Interfaces
Different hardware
support
Different application
support
Lack of Uniformity
Source: http://www.infoq.com/articles/State-of-NoSQL
Database Evolution Timeline
Additional Resources
Tutorial by C. Mohan, An In-Depth Look at
Modern Database Systems
 https://docs.google.com/file/d/0B7lNUaak
0bK1encwYnBVUWZSWjA/edit

Relational Data

Tables or Relations
Relational Database: Schemas
Relational Database: Query
Language
 SQL
- Structured Query Language
 a declarative language designed for
managing data held in a relational database
management system
• Tell what you want and from where
• Do not tell: how to get the data
Key-Value Store
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
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Implemented as an associative array, map, symbol
table, or dictionary abstract data type composed of
a collection of (key, value) pairs such that each
possible key appears at most once in the collection.
A simple put/get interface
Great properties: scalability, availability, reliability
Key-Value Store Usage Scenarios

Increasingly popular within data centers and in P2P
Data center
amazon.com
LinkedIn
Facebook
Dynamo
Voldemort
Cassandra
P2P
Vuze
uTorrent
Vuze DHT
uTorrent DHT
Row Store and Column Store
Source: Column-Oriented Database Systems, VLDB 2009. Tutorial; S.
Harizopoulos, D. Abadi, P. Boncz


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In row store data are stored in the disk tuple by tuple.
Where in column store data are stored in the disk column by
column.
Column-stores are more I/O efficient for read-only queries as
they read, only those attributes which are accessed by a query.
Row Store and Column Store
Row Store
Column Store
(+) Easy to add/modify a
record
(+) Only need to read in
relevant data
(-) Might read in
unnecessary data
(-) Tuple writes require
multiple accesses

So column stores are suitable for read-mostly,
read-intensive, large data repositories
Graph Databases
Biological
Network
Ecological
Network
Social
Network
Chemical
Network
Program Flow
Web Graph
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
24
Graph Databases: Query

Find all the restaurants my friends (in Facebook) like
So, Why Study Relational DBs?

Jack Clark, The Register, 30 August 2013: “The tech world is turning
back toward SQL, bringing to a close a possibly misspent half-decade in
which startups courted developers with promises of infinite scalability
and the finest imitation-Google tools available, and companies found
themselves exposed to unstable data and poor guarantees.”

Google Spanner paper, October 2012: “We believe it is better to have
application programmers deal with performance problems due to
overuse of transactions as bottlenecks arise, rather than always coding
around the lack of transactions.”

Sean Doherty in Wired, September 2013: “But don’t become
unnecessarily distracted by the shiny, new-fangled, NoSQL red buttons
just yet. Relational databases may not be hot or sexy but for your
important data there is no substitute.”
And, The Key Reason of All

Gartner estimates RDBMS market at $26B with
about 9% annual growth, whereas Market
Research Media Ltd expects NoSQL market to
be at $3.5B by 2018.
 Source: C Mohan’s tutorial
Databases make these folks happy ...
End users and DBMS vendors
 DB application programmers
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
E.g., smart webmasters
Database administrator (DBA)
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Designs logical /physical schemas
Handles security and authorization
Data availability, crash recovery
Database tuning as needs evolve
Must understand how a DBMS works!
These layers
must consider
concurrency
control and
recovery
Structure of a DBMS



A typical DBMS has a
Query Optimization
layered architecture.
and Execution
The figure does not
Relational Operators
show the concurrency
Files and Access Methods
control and recovery
components.
Buffer Management
This is one of several
Disk Space Management
possible architectures;
each system has its own
variations.
DB
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
29
Summary
DBMS used to maintain, query large datasets.
 Benefits include recovery from system crashes,
concurrent access, quick application
development, data integrity and security.
 Levels of abstraction give data independence.
 A DBMS typically has a layered architecture.
 DBAs hold responsible jobs
and are well-paid! 
 DBMS R&D is one of the broadest,
most exciting areas in CS.
