Chapter 12 Distributed Data Bases

Learning Objectives What a distributed database management system (DDBMS) is and what its components are How database implementation is affected by different levels of data and process distribution How transactions are managed in a distributed database environment How database design is affected by the distributed database environment

Objectives of DDS B Provide ease of access to users at different sites Local autonomy Create transparency Faster response

DDB A DB PHYSICALLY SPREAD ACROSS COMPUTERS AT MULTIPLE LOCATIONS CONNECTED BY A NETWORK AND IN WHICH USERS CAN ACCESS DATA AT ANY SITE IN THE NETWORK IS DEFINED AS DDB

DISTRIBUTE DBMS A DBMS CAPABLE OF SUPPORTING AND MANIPULATING DDB DETERMINE LOCATION OF REQUESTED DATA TRANSFER REQUEST FROM ONE NODE TO ANOTHER NODE RECOVERY, CONCURRENCY, DEADLOCK etc

DDBMS a DDBMS is like a DBMS with additional responsibilities of communication and coordination of data storage and processing over several distributed sites

Advantages of DDB Data is located at the demand site faster data access faster data processing growth facilitation better communication reduced operating costs user-friendly interface less problem of a single point failure

DDB disadvantages management & control security lack of standards storage problem

A Fully Distributed Database Management System

Distributed processing & distributed Databases Distributed processing: Data is processed at multiple sites (Data maybe all in ONE location) DDB: Database is actually located on multiple sites (see fig 12.3) Skip pp

Levels of processing Single site processing; single site data (see fig 12.6) Multiple site process; single site data (MPSD) All work is done (locking, selection etc. is done at user level) Multiple-site processing; multiple site data

TRANSPARENCY: 1.DISTRIBUTION 1.FRAGMENTATION HIGHEST LEVEL DO NOT NEED TO SPECIFY FRAGMENT NAME OR LOCATION 2. LOCATION MUST SPECIFY NAME BUT not LOCATION 3. LOCAL Must specify both name and location of fragment

Transparency Assuming part table is fragmented based on warehouse # Select * from Part Where warehouse =1; Select * from part1 Where warehouse=1; Select * from part1 node Chicago Where warehouse =1;

Data fragmentation A process of splitting data in two or more fragments Horizontal Vertical mixed

Using SQL type statements Begin: Define fragment fragment-name AS SQL statements End; Horizontal Fragmentation: (Based on warehouse) Ex: Begin: Define fragment PART1 AS Select * From PART Where warehouse=1 End;

Vertical (based on say price) Inventory department maybe interested in on hand inventory only but other may be interested in other attributes Inventory..partnum,onhand,part desc Production..partnum,class,warehouse,price

Mixed Each item by warehouse number (horizontal) and then by inventory & production

Transaction Transparency Remote request (see 12.10) (single request) Remote transaction (multiple requests)

Distributed transaction (12.12/p472) (allows a transaction to reference several different locations Each single request can reference only one single site

Distributed Request Each transaction can request data from multiple sites

Data Allocation: data should be as close to the user as possible

ISSUES IN DDB SOFTWARE COSTS & COMPLEXITY COORDINATION AMONG SITES DATA INTEGRITY SLOW RESPONSE Q1/p487