Chap 1

Motivation

Centralized DBMS in a network

Distributed DBMS environment

IntroductionIntroduction

Distributed Database changes the way of data sharing, conceptually from centralization into decentralization.

Development of computer networks promotes a decentralized mode of work.

Development of distributed systems should improve the sharing ability of the data and the efficiency of data access

Distributed systems should help resolve the "islands of information" problem

12.3 Introduction

ConceptsConcepts

DDBMS to Avoid `islands of information’ problem…

A “Distributed Database”: is a logically interrelated collection of shared data (and a description of this data), physically distributed over a computer network.

A “Distributed DBMS” (DDBMS): is a Software system that permits the management of the distributed database and makes the distribution transparent to users.

Fundamental Principle: make distribution transparent to user. The fact that fragments are stored on different computers is hidden from the users

Concepts (cont’d)Concepts (cont’d)

In a distributed DBMS , single logical database is split into a number of fragments.

Each fragment is stored on one or more computers under the control of a separate DBMS

with the computer connected to a network. Each site is capable of independently processing user requests that require access to local data and is also capable of processing data stored on other computers in the network.

Concepts (cont’d)Concepts (cont’d)

There are two applications

1) local application: do not require data from other sites

2) global application: do require data from other sites

Distributed DBMS need to have at least one global application.

DATABASE ARCHITECUREDATABASE ARCHITECURE

Architecture of DB system is influenced by:

1. Networking

2. Parallel Processing

3. Distributing data

Homogeneous and Heterogeneous DDBMSs Homogeneous and Heterogeneous DDBMSs

Homogeneous DDBMS

In homogeneous DDBMS, all sites use the same DBMS product.

Much easier to design and manage.

This design provides incremental growth by making additional new sites to DDBMS easy

Allows increased performance by exploiting the parallel processing capability of multiple sites.

Heterogeneous DDBMSs Heterogeneous DDBMSs

• In heterogeneous DDBMS, all sites may run different DBMS products, which need not to be based on the same underlying data model and so the system may be composed of RDBMS, ORDBMS and OODBMS products.

In heterogeneous system, communication between different DBMS are required for translations.

In order to provide DBMS transparency, users must be able to make requests in the language of the DBMS at their local site.

Data from the other sites may have different hardware, different DBMS products and combination of different hardware and DBMS products.

The task for locating those data and performing any necessary translation are the abilities of heterogeneous DDBMS.

The Evolution of Distributed DBMSThe Evolution of Distributed DBMS

DDBMS Advantages

Data are located near the “greatest demand” site.

Faster data access

Faster data processing

Growth facilitation

Improved communications

Reduced operating costs

User-friendly interface

Less danger of a single-point failure

Processor independence

DDBMS Disadvantages

Complexity of management and control

Security

Lack of standards

Increased storage requirements

Distributed Processingand Distributed DatabaseDistributed Processing

and Distributed Database Distributed processing shares the database’s logical

processing among two or more physically independent sites that are connected through a network.

Distributed database stores a logically related database over two or more physically independent sites connected via a computer network.

Important difference between DDBMS and distributed processing !Important difference between DDBMS and distributed processing !

DDBMSDistributed processing of centralised DBMS

12.3 Introduction

Distributed processing of a centralised DBMS has following characteristics :•Much more tightly coupled than a DDBMS.•Database design is same as for standard DBMS•No attempt to reflect organisational structure•Much simpler than DDBMS•More secure than DDBMS•No local autonomy

12.3 Introduction

DDBMS

Important difference between DDBMS and Parallel Database

Parallel Database Architectures: Shared: a)memory b)disk c)nothing

Distributed Processing Environment

Distributed Database Environment

Distributed Processingand Distributed DatabaseDistributed Processing

and Distributed Database

Distributed processing does not require a distributed database, but a distributed database requires distributed processing.

Distributed processing may be based on a single database located on a single computer. In order to manage distributed data, copies or parts of the database processing functions must be distributed to all data storage sites.

Both distributed processing and distributed databases require a network to connect all components.

What Is A Distributed DBMS?What Is A Distributed DBMS?

A distributed database management system (DDBMS) governs the storage and processing of logically related data over interconnected computer systems in which both data and processing functions are distributed among several sites.

What Is A Distributed DBMS?What Is A Distributed DBMS?

Functions of a DDBMS Application interface

Validation to analyze data requests

Transformation to determine request’s components

Query-optimization to find the best access strategy

Mapping to determine the data location

I/O interface to read or write data

Formatting to prepare the data for presentation

Security to provide data privacy

Backup and recovery

Database administration

Concurrency control

Transaction management

Charactersitic of DDBMSCharactersitic of DDBMS

Collection of logically related shared data

Data split into fragments

Fragments can be replicated

Fragments/replicas may be allocated to sites

sites linked by communication network

data at each site is under control of DBMS

Centralized Database Management System

Fully Distributed Database Management System

Figure 10.4

DDBMS ComponentsDDBMS Components

Computer workstations that form the network system.

Network hardware and software components that reside in each workstation.

Communications media that carry the data from one workstation to another.

Transaction processor (TP) receives and processes the application’s data requests.

Data processor (DP) stores and retrieves data located at the site. Also known as data manager (DM).

Distributed Database System Components

DDBMS ComponentsDDBMS Components

DDBMS protocol determines how the DDBMS will:

Interface with the network to transport data and commands between DPs and TPs.

Synchronize all data received from DPs (TP side) and route retrieved data to the appropriate TPs (DP side).

Ensure common database functions in a distributed system -- security, concurrency control, backup, and recovery.

Levels of Data & Process DistributionLevels of Data & Process Distribution

Single-Site Processing, Single-Site Data (SPSD) All processing is done on a single CPU or host computer. All data are stored on the host computer’s local disk. The DBMS is located on the host computer. The DBMS is accessed by dumb terminals. Typical of most mainframe and minicomputer DBMSs. Typical of the 1st generation of single-user microcomputer

database.

Nondistributed (Centralized) DBMS

Levels of Data & Process DistributionLevels of Data & Process Distribution

Multiple-Site Processing, Single-Site Data (MPSD) Typically, MPSD requires a network file server on which

conventional applications are accessed through a LAN.

A variation of the MPSD approach is known as a client/server architecture.

Figure 10.7

Figure 10.8 Heterogeneous Distributed Database Scenario

Typically, distributed DBs:

Geographically distributedData sharing is goal (may run into heterogeneity, autonomy)Disconnected operation possible

1.Local Site Independence

2.Central Site Independence

3.Failure Independence

4.Location Transparency

5.Fragmentation Transparency

6.Replication Transparency

7.Distributed Query Processing

8.Distributed Transaction Processing

9.Hardware Independence

10.Operating System Independence

11.Network Independence

12.Database Independence