1. Lecture 2 Database Management Systems

2. Outline Data Models and Their Categories
Schemas, Instances, and States
Three-Schema Architecture
Data Independence
DBMS Languages and Interfaces
Database System Utilities and Tools
Centralized and Client-Server Architectures
Classification of DBMSs
Research topics for Graduate-term-paper
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3. The architecture of DBMS
A general term to describe buildings, physical structures, and computer-based systems
E.g.,
DBMS Architecture
DBMS has also architecture
Monolithic
client/server
Client module
Server module
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4. Architecture: Some examples of
LOCKHEED F-117A NIGHT HAWK
Brunelleschi’s dome
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5. Data Models: 1 Data Model? A set of concepts to describe
the structure of a database,
the operations for manipulating these structures,
the constraints that the database should obey.
Provides proper means to describe the design of a database at the
Physical level
Logical level
View levels
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6. Data Models: 2 Data Model Structure? By structure
data and data types and entities (e.g., record, table)
relationships among data
Constraints on data
These are restrictions/conditions on valid data;
must be enforced at all times
E.g.,
Each department must have at least 5 employees
A student can not have more than one advisor
The salary of employee cannot exceed the salary of his/her immediate supervisors
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7. Data Models: 2 Data Model Operations (behaviors)
operations that are used for specifying database retrievals and updates by referring to the constructs of the data model
Operations on the data model may include
basic model operations
e.g. generic insert, delete, update
user-defined operations
e.g. compute_student_gpa, update_inventory
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8. Categories of Data Models
Conceptual (high-level, semantic) data models:
Provide concepts that are close to the way many users perceive data (ERD)
(Also called entity-based or object-based data models.)
Physical (low-level, internal) data models:
Provide concepts that describe details of how data is stored in the computer (e.g., access control)
Implementation (representational) data models:
Provide concepts that fall between the above two
used by many commercial DBMS implementations (e.g. relational data models, and OO-Model)
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9. Schemas and Instances: 1
Database Schema:
The description or specification of a database
Includes descriptions of the database
structure
data types
the constraints on the database.
Schema Diagram?
An illustrative display of (most aspects of) a database schema.
Schema Construct?
A component of the schema or an object within the schema,
e.g., STUDENT, COURSE.
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10. Example of a Database Schema
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11. Schemas and Instances:2
Database State:
The actual data stored in a database at a particular moment in time.
includes the collection of all the data in the database.
Also called database instance (snapshot).
The term instance is also applied to individual database components,
e.g.
record instance
table instance …
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12. Example of a Database State
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13. Database Schema vs. Database State: 1
Initial Database State?
Refers to the database state when it is initially loaded into the system
Valid State?
A state that satisfies the structure and constraints of the database.
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14. Database Schema vs. Database State: 2
Major Distinction
The database schema changes very infrequently.
The database state changes very frequently
Schema are stored in the DBMS catalog
Schema is also called intension.
State is also called extension.
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15. Three-Schema Architecture
Proposed to support DBMS characteristics of:
Self-describing nature of DBMS
Program-data independence.
Support of multiple views of the data
Not explicitly used in commercial DBMS products, but has been useful in explaining database system organization
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16. Three-Schema Architecture
Defines DBMS schemas at three levels:
Internal schema:
This level describe physical storage structures and access paths (e.g., indexes).
Typically uses a physical data model.
Conceptual schema
this level describe the structure and constraints for the whole database for a community of users.
Uses a conceptual (implementation) data model.
External schemas
This level describe the various user views.
Usually uses the same data model as the conceptual schema.
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17. The three-schema architecture
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18. Three-Schema Architecture: Overhead
Mappings among schema levels are needed to transform requests and data.
Programs refer to an external schema are mapped (i.e., translated) by the DBMS to the internal schema for execution.
Data extracted from the internal DBMS level is reformatted to match the user’s external view
e.g.,
formatting the results of an SQL query for display in a Web page
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19. Data Independence: 1
Three-schema architecture is used to achieve data independence
changing schema at one level without changing the schema at the next higher level
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20. Data Independence: 2 Logical Data Independence:
change the conceptual schema without having to change the external schemas and their associated application programs
E.g., view should not be changed if the base tables are changed
Physical Data Independence:
change the internal schema without having to change the conceptual schema.
examples
the internal schema may be changed whenever certain file structures are reorganized
new indexes are created to improve database performance
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21. Data Independence: Implications
When a schema at a lower level is changed, only the mappings between this schema and its higher-level schemas need to be changed.
The higher-level schemas themselves are unchanged.
i.e., the application programs need not be changed since they refer to the external schemas.
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22. DBMS Languages Data Definition Language (DDL):
Used by the DBA and database designers to specify the conceptual schema of a database;
Also used to define internal and external schemas
Storage Definition Language (SDL)
SDL is typically realized via DBMS commands provided to the DBA and database designers
View Definition Language (VDL)
Used to define internal and external schemas.
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23. DBMS Languages Data Manipulation Language (DML):
Used to specify database retrievals and updates
Retrieval of information
Insertion of new information
Deletion and/or modification of information stored in the DB
Two main types DMLs
High-level (nonprocedural) DML
stand-alone DML commands can be applied directly (called a query language).
Low level (procedural ) DML
embedded in a general-purpose programming language (host language), such as COBOL, C, C++, or Java.
Used to retrieve individual records/objects from database
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24. DBMS Programming Language Interfaces
Programmers interface for embedding DML in a programming languages:
Embedded Approach:
embedded SQL (for C, C++, etc.), and SQLJ (for Java)
Procedure Call Approach:
JDBC (Java Database Connectivity )for Java,
ODBC (Open Database Connectivity )for other programming languages
Database Programming Language Approach:
e.g.
Oracle’s PL/SQL: a programming language based on SQL;
language incorporates SQL and its data types as integral components
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25. User-Friendly DBMS Interfaces
Menu-based:
popular for browsing on the web
Forms-based:
designed for naïve users
Graphics-based:
Point and Click, Drag and Drop, etc.
Natural language:
Requests in written English
Combinations of the above:
For example, both menus and forms used extensively in Web database interfaces
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26. More on DBMS Interfaces
Speech as Input and Output
Web Browser as an interface
Parametric interfaces:
e.g., bank tellers using function keys.
Interfaces for the DBA:
Creating user accounts, granting authorizations
Setting system parameters
Changing schemas or access paths
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27. Database System Utilities
To perform certain functions such as:
Loading data stored in files into a database. Includes data conversion tools
Backing up the database periodically on tape
Reorganizing database file structures
Report generation utilities
Performance monitoring utilities.
Other functions,
sorting,
user monitoring,
data compression, etc.
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28. Database System Utilities: 2
Data dictionary / repository:
Used to store schema descriptions and other information such as design decisions, application program descriptions, user information, usage standards, etc.
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29. Database System Utilities: 3
Application Development Environments and CASE (Computer-Aided Software Engineering) tools:
Examples:
PowerBuilder (Sybase)
JBuilder (Borland)
JDeveloper 10G (Oracle)
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30. The Database System Environment
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31. DBMS Architectures : Centralized and Client-Server
Centralized DBMS Architecture:
Combines everything into single system including
DBMS software,
hardware,
application programs,
user interface processing software.
User can connect through a remote terminal – however, all processing is done at centralized site.
E.g.,
time-sharing systems (good old days!)
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32. A Physical Centralized Architecture
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33. Client-Server Architectures: two tier C/S
Clients (users) can access the specialized servers as needed
Provide GUI and local processing
Server?
Specialized Servers with Specialized functions
Print server (share printer)
File server (share files)
DBMS server (share DBMS)
Web server (share web-pages)
server
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34. Logical two-tier client server architecture
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35. Clients
Provide appropriate interfaces through a client software module to access and utilize the various server resources.
Clients may be diskless machines or PCs or Workstations with disks with only the client software installed.
Connected to the servers via some form of a network.
(LAN: local area network, wireless network, etc.)
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36. Servers
Provides database query and transaction services to the clients
Relational DBMS servers are often called
SQL servers
Query servers
Transaction servers
Applications running on clients uses Application Program Interface (API) to access server databases via standard interface such as:
ODBC: Open Database Connectivity standard
JDBC: for Java programming access
Client and Server must install appropriate client and server modules software for ODBC or JDBC
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37. 2-Tier Client-Server Architecture
A client program may connect to several DBMSs, sometimes called the data sources.
E.g.,
data sources can be files
non-DBMS software that manages data.
Other variations of clients are possible (thin, fat, p2p, SOA, etc)
e.g.,
in some object DBMSs, more functionality is transferred to clients including data dictionary functions, optimization and recovery across multiple servers, etc.
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38. 3-Tier C/S Architecture
Common for Web applications
Intermediate Layer called Application Server or Web Server:
Stores the web connectivity software and the business logic part of the application used to access the corresponding data from the database server
Used as a channel for sending partially processed data between the database server and the client.
Three-tier Architecture
Enhances Security:
Database server only accessible via middle tier
Clients cannot directly access database server
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39. 3-tier client-server architecture
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40. Classification of DBMSs
Based on the data model used
Classical:
Relational, Network, Hierarchical.
Emerging:
Object-oriented, Object-relational.
Based on Users
Single-user
multi-user
Based on Distributeness
Centralized
Distributed
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41. Variations of Distributed DBMSs (DDBMSs)
Based on Homogeneity
Homogeneous DDBMS
Heterogeneous DDBMS
Federated or Multi-database Systems
(Autonomy, distributeness, heterogeneously)
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42. Cost considerations for DBMSs
Based on Cost
from free open-source systems
to configurations costing millions of dollars
Examples of free relational DBMSs:
MySQL,
PostgreSQL
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43. History of Data Models Network Model Hierarchical Model
Relational Model
Object-oriented Data Models
Object-Relational Models
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44. History of Data Models Network Model:
The first network DBMS was implemented by Honeywell in (IDS System).
Adopted heavily due to the support by CODASYL (Conference on Data Systems Languages) (CODASYL - DBTG report of 1971).
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45. Example of Network Model Schema
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46. Network Model Advantages:
Network Model is able to model complex relationships and represents semantics of add/delete on the relationships.
Can handle most situations for modeling using record types and relationship types.
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47. Network Model Disadvantages:
Navigational and procedural nature of processing
Database contains a complex array of pointers that thread through a set of records.
Little scope for automated “query optimization”
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48. History of Data Models Hierarchical Data Model:
Initially implemented as a joint effort by IBM and North American Rockwell around 1965.
Resulted in the IMS family of systems.
IBM’s IMS product had (and still has) a very large customer base worldwide
Hierarchical model was formalized based on the IMS system
Other systems based on this model: System 2k (SAS inc.)
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49. Hierarchical Model Advantages: Disadvantages:
Simple to construct and operate
Corresponds to a number of natural hierarchically organized domains,
e.g., organization (“org”) chart
Language is simple:
Uses constructs like GET, GET UNIQUE, GET NEXT, GET NEXT WITHIN PARENT, etc.
Disadvantages:
Navigational and procedural nature of processing
Database is visualized as a linear arrangement of records
Little scope for "query optimization"
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50. History of Data Models Relational Model:
Proposed in 1970 by E.F. Codd (IBM),
first commercial system in
Now in several commercial products
e.g. DB2, ORACLE, MS SQL Server, SYBASE, INFORMIX
Several free open source implementations,
e.g. MySQL, PostgreSQL
SQL relational standards:
SQL-89 (SQL1), SQL-92 (SQL2), SQL-99, SQL3, …
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51. History of Data Models Object-oriented Data Models:
Several models have been proposed for implementing in a database system.
One set comprises models of persistent O-O Programming Languages such as C++ (e.g., in OBJECTSTORE or VERSANT), and Smalltalk (e.g., in GEMSTONE).
Additionally, systems like O2, IRIS (at HP- used in Open OODB).
Chapters describe this model.
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52. History of Data Models Object-Relational Models: Most Recent Trend.
Started with Informix Universal Server.
Relational systems incorporate concepts from object databases leading to object-relational.
Exemplified in the versions of Oracle-10i, DB2, and SQL Server and other DBMSs.
Standards included in SQL-99 and expected to be enhanced in future SQL standards.
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53. For Graduate Students

54. About Graduate Research Report
Report Format
IEEE/ACM Format
8-10 pages
One column
Fully Citied
References must be completed (i.e., authors, title, source, page, year, etc)
Use the same format for References
No dangling references
HTTP: must have title
Tables/Figures must be numbered and briefly explained
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55. Organization of the paper
Title
Name
Affiliation (e.g., UND)
Paper content
Abstract
words
Introduction
Background
Related works
Approach
Discussion
Conclusion and Future work
Acknowledgments (if any)
References
Appendix
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56. Graduate Students Research Report Possible Topics: Cloud Computing (CC)- 1
One of the biggest IT game changer
Estimates market growth rates for public cloud products and services is 20% growth annually
$ B in 2012 in just U.S.
Cloud Computing and Databases as a service (DaaS)
DBMS vs. HDBMS/DDBMS vs. CLOUD COMPUTING
If and how you’re adopting cloud services
Which applications you’re using for the cloud
The benefits you’re realizing – and challenges you’re facing
When to use cloud computing (CC)?
When not to use cloud computing (CC)?
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57. Graduate Students Report: Cloud Computing (CC)-2
What are the quality attributes of cloud computing from cloud user (consumer) and cloud providers (producer) point of view.
What are the architectural design decision regarding CC?
What are the risks associated with CC?
Type of analysis and tradeoff techniques to analyze the quality of CC?
Transition of DB and its deployment on CC
How to provide service elasticity, co-locateability, and other cloud related qualities in CC?
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58. Big Data? Big DATA? Approaches
Referred to data (structured and unstructured) that is measured in exabytes and beyond
Approaches
Hadoop (NOSQL) to support Distributed application using distributed file system and MapRedure
Big and High Performance Database Mgt System solutions (MPP DBMS)
What are the technologies being applied to big data
massively parallel-processing databases,
search-based applications
data-mining grids,
distributed file systems,
distributed databases,
cloud based infrastructure
(Saas, Daas, Paas, etc.)
What are the challenges of using (e.g., CC, RDBMS, DDBMS, ) to search, analyze, etc. of BIG Data?
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59. Summary Data Models and Their Categories History of Data Models
Schemas, Instances, and States
Three-Schema Architecture
Data Independence
DBMS Languages and Interfaces
Database System Utilities and Tools
Centralized and Client-Server Architectures
Classification of DBMSs
Graduate Research Topics
Big Data, Cloud Computing, etc.
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