Presented by: Kai Zhu Professor: Dr. T.Y. Lin Class ID: 220

Slides:



Advertisements
Similar presentations
Lukas Blunschi Claudio Jossen Donald Kossmann Magdalini Mori Kurt Stockinger.
Advertisements

Wrappers in Mediator-Based Systems Chapter 21.3 Information Integration Presented By Annie Hii Toderici.
SECTION 21.5 Eilbroun Benjamin CS 257 – Dr. TY Lin INFORMATION INTEGRATION.
Query Execution Professor: Dr T.Y. Lin Prepared by, Mudra Patel Class id: 113.
Query Execution Professor: Dr T.Y. Lin Prepared by, Mudra Patel Class id: 113.
CS 257 Database Systems Principles Assignment 1 Instructor: Student: Dr. T. Y. Lin Rajan Vyas (119)
Chapter 21.2 Modes of Information Integration ID: 219 Name: Qun Yu Class: CS Spring 2009 Instructor: Dr. T.Y.Lin.
SECTIONS 21.4 – 21.5 Sanuja Dabade & Eilbroun Benjamin CS 257 – Dr. TY Lin INFORMATION INTEGRATION.
CS 257 Database Systems Principles Assignment 1 Instructor: Student: Dr. T. Y. Lin Rajan Vyas (119)
Capability-Based Optimization in Mediators Rohit Deshmukh ID 120 CS-257 Rohit Deshmukh ID 120 CS-257.
Query Execution Professor: Dr T.Y. Lin Prepared by, Mudra Patel Class id: 113.
Chapter 21 Information Integration 21.3 Wrappers in Mediator-Based Systems Presented by: Kai Zhu Professor: Dr. T.Y. Lin Class ID: 220.
Automatic Data Ramon Lawrence University of Manitoba
Chapter 12 Machine Learning ID: Name: Qun Yu (page 1-33) Kai Zhu (page 34-59) Class: CS267 Fall 2008 Instructor: Dr. T.Y.Lin.
Connecting Diverse Web Search Facilities Udi Manber, Peter Bigot Department of Computer Science University of Arizona Aida Gikouria - M471 University of.
On-Line Analytic Processing Chetan Meshram Class Id:221.
Chapter 21.2 Modes of Information Integration ID: 219 Name: Qun Yu Class: CS Spring 2009 Instructor: Dr. T.Y.Lin.
20.5 Data Cubes Instructor : Dr. T.Y. Lin Chandrika Satyavolu 222.
Object Oriented Design Jerry KotubaSYST Object Oriented Methodologies1.
Submitted by: Deepti Kundu Submitted to: Dr.T.Y.Lin
INFORMATION INTEGRATION Shengyu Li CS-257 ID-211.
1 Information Integration. 2 Information Resides on Heterogeneous Information Sources different interfaces different data representations redundant and.
DBMS2001Notes 10: Information Integration1 Principles of Database Management Systems 10: Information Integration Pekka Kilpeläinen University of Kuopio.
Information Integration By Neel Bavishi. Mediator Introduction A mediator supports a virtual view or collection of views that integrates several sources.
Wrappers in Mediator-Based Systems. Introduction Mediator Wrapper Source 1 Source 2 Query Result.
M1G Introduction to Programming 2 3. Creating Classes: Room and Item.
NSF DUE ; Wen M. Andrews J. Sargeant Reynolds Community College Richmond, Virginia.
Section 20.1 Modes of Information Integration Anilkumar Panicker CS257: Database Systems ID: 118.
Introduction to ORM Hibernate Hibernate vs JDBC. May 12, 2011 INTRODUCTION TO ORM ORM is a programming technique for converting data between relational.
Chapter 111 Chapter 11 Information Integration Spring 2001 Prof. Sang Ho Lee School of Computing, Soongsil Univ.
The LC-3 – Chapter 6 COMP 2620 Dr. James Money COMP
Look for Corporate Tax Experts
Database System Implementation CSE 507
Project Management: Messages
Information Integration(cntd.)
4 Integration.
15.1 – Introduction to physical-Query-plan operators
Chapter 14: Protection Modified by Dr. Neerja Mhaskar for CS 3SH3.
Database Security and Authorization
Stored Procedures – Facts and Myths
Chapter 11 Information Integration
Java Software Solutions
Database Management System
On-Line Analytic Processing
Functions CIS 40 – Introduction to Programming in Python
Lecture 2 of Computer Science II
Aggregation Aggregations operations process data records and return computed results. Aggregation operations group values from multiple documents together,
Passing Arguments to a Function
SQL: Structured Query Language DML- Queries Lecturer: Dr Pavle Mogin
Chapter 15 QUERY EXECUTION.
CPSC-310 Database Systems
Chapter 2 Database Environment.
4-2 Functions in C In C, the idea of top–down design is done using functions. A C program is made of one or more functions, one and only one of which.
Chapter 8: Advanced Pattern Matching
Controllers.
Information Integration Introduction (21.1)
Ben’s Lecture Cliff Notes
Query Optimization CS 157B Ch. 14 Mien Siao.
The Linux Command Line Chapter 17
Information Integration
Problem Statement and Significance
INSTRUCTOR: MRS T.G. ZHOU
Addressing confidentiality issue in third party xml publication
A Semantic Peer-to-Peer Overlay for Web Services Discovery
CS 1054: Lecture 2, Chapter 1 Objects and Classes.
Week 4: Sigma Notation and its properties
U3L8 Creating Functions with Parameters
CS561-Spring 2012 WPI, Mohamed eltabakh
Java Software Solutions
Human and Computer Interaction (H.C.I.) &Communication Skills
Presentation transcript:

Presented by: Kai Zhu Professor: Dr. T.Y. Lin Class ID: 220 Chapter 21 Information Integration 21.3 Wrappers in Mediator-Based Systems Presented by: Kai Zhu Professor: Dr. T.Y. Lin Class ID: 220

Intro Templates for Query patterns Wrapper Generator Filter

More complicated than that in most data warehouse system. Wrappers in Mediator-based Systems More complicated than that in most data warehouse system. Able to accept a variety of queries from the mediator and translate them to the terms of the source. Communicate the result to the mediator.

How to design a wrapper? Classify the possible queries that the mediator can ask into templates, which are queries with parameters that represent constants. Simplest way to see a wrapper is like a translator.

Templates for Query Patterns: Use notation T=>S to express the idea that the template T is turned by the wrapper into the source query S.

Example 1 Dealer 1 Cars (serialNo, model, color, autoTrans, navi,…) For use by a mediator with schema AutoMed (serialNo, model, color, autoTrans, dealer)

We denote the code representing that color by the parameter $c, then the template will be: SELECT * FROM AutosMed WHERE color = ’$c’; => SELECT serialNo, model, color, autoTrans, ’dealer1’ FROM Cars WHERE color=’$c’; (Template T => Source query S)

There will be total 2n templates if we have the option of specifying n attributes.

Wrapper Generators The wrapper generator creates a table holds the various query patterns contained in the templates. The source queries that are associated with each.

A driver is used in each wrapper, the task of the driver is to: Accept a query from the mediator. Search the table for a template that matches the query. The source query is sent to the source, again using a “plug-in” communication mechanism. The response is processed by the wrapper.

Filter Not always possible to have a wrapper that can translate a query into another query to get exact results Filters can then be used on a bigger result set to only return wanted results.

Example 2 If wrapper is designed with more complicated template with queries specify both model and color. SELECT * FROM AutosMed WHERE model = ’$m’ AND color = ’$c’; => SELECT serialNo, model, color, autoTrans, ’dealer1’ FROM Cars WHERE model = ’$m’ AND color=’$c’;

Now we suppose the only template we have is color Now we suppose the only template we have is color. However the wrapper is asked by the Mediator to find “blue Gobi model car.”

Solution: 1. Use template with $c=‘blue’ find all blue cars and store them in a temporary relation: TemAutos (serialNo, model, color, autoTrans, dealer) 2.The wrapper would then return to the mediator the desired set of automobiles by executing the local query(filter): SELECT* FROM TemAutos WHERE model= ’Gobi’;

Thank you