DBMS Architecture Features(3)

8/2/2019 DBMS Architecture Features(3)

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Dr James Xue

School of Science & TechnologyUniversity of Northampton

DBMS architecture & features

Database Technologies 2 (CSY3024)


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Database architectures

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There is a wide variety of different DBMS architectures Teleprocessing File-Server Architecture Two-tier Client-Server Architecture

Three-tier Client-Server Architecture N-tier Client-Server Architecture Peer-to-Peer Architecture Distributed DBMS Cloud Architecture

Mobile databases


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Teleprocessing

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Traditional multi-user system architecture Single mainframe and multiple terminals

Heavy load on the central mainframe Run application programs and DBMS

Format data for presentation on terminals Tendency to replace mainframes with network of personalcomputers (downsizing)

File server architectures Client-server architectures .


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File-Server Architecture

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A file-server is a computer that is connected to a network andmainly servers as ashared storage

E.g., for shared access to databases

In afile-server architecturethe processing is distributedover thenetwork Workstations (application and DBMS) request data (files)


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File-Server Architecture (cont.)

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SQL request example

Since the file-server isnot SQL-aware, the DBMS mustrequest files corresponding to theBranchand Staff relationsfrom the file server, rather than just the staff names thatsatisfy the request

Disadvantages Heavy network traffic Each work stations runs a full instance of the DBMS

Complex integrity, concurrency and recovery control Multiple DBMSs may concurrently access the shared file


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Two-tier Client-Server Architecture

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Application consists of a client (1st tier) and a server (2nd tier) thatmight run on different machines

Clear separation of concerns between client and server

Thin client vs thick client Less or more application logic on the client side Support decentralised business environments


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Two-tier Client-Server Architecture

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Client (1st tier) tasks Presentationof data (user interfaces) Business and data application logic Send the database request to the server and process the results

Server (2nd tier) tasks

Manage (concurrent) data access (data services) Authorisation, integrity checks, query/update processing, recovery control,

Business logic (e.g., validation of data) Different possible client-server topologies

Single client and single server Multiple clients and single server Multiple clients and multiple servers


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Three-tier Client-Server Architecture

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In the 1990s, the three-tier client-server architecture wasintroduced to address the enterprise scalability issue

e.g., driven by emerging web applications Application consists of a presentation tier (client) , a logic tier

(application server) and a data tier (database server) that mightrun on different platforms


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Three-tier Client-Server Architecture

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N-tier architecture

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The three-tier architecture can be extended withadditional intermediary tiers for increased flexibility

Increases the flexibility for load balancing by introducing multiple webservers and/or edege servers.


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Peer-to-Peer Architecture

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Systems changing information and services in a peer-to-peer (P2P)manner without a central authority

No global schema and need for schema integration (matching)

Data and service sharing No dedicated clients and servers Sites may dynamically form new client/server relationships


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Middleware

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Software that connects (mediates) between softwarecomponents or applications

Hide complexityof heterogeneous and distributed components andprovide a uniform interface

There exists different types of middleware Remote procedure call (RPC)

Java RMI CORBA XML RPC

Asynchronouspublish/subscribe

Subscribe for different types of messages


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Distributed DBMS (DDBMS)

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Distributed database Legally relatedconnection of shared data and metadatathat is

distributed over a network

Distributed DBMS Software system tomanagethe distributed databases in a transparentway


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Distinction between local and global transaction Local transaction

Accesses only data from the site from which the transaction was initiated Global transaction

Accesses data from several different sites Reasons for building a distributed DBMS

Data sharing Possibility to access data that resides at other sites

Autonomy Each site retains a certain degree of control over the local data

Availability

If one site fails, the other sites may still be able to continue operating Data might be replicated at several sites to increase the availability


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Costs and scalability Use cluster of PCs in stead of large mainframe systems

Integration of existing DBMSs Coexistence of legacy systems with new applications

Dynamic organisational structure Mergers and acquisitions

Implementation issues Transactions have to be executed atomically across different

sites (two-phase commit protocol) Commit decision is left to a singlecoordinator

Distributed concurrency control Deadlock detectionhas to be carried out across multiple sites


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Parallel Database Architectures

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Parallel machines (multiple processors) can be used tospeed up the transaction processing

Different models for parallel database architectures Shared-memory, shared-disk, shared-nothing and hierarchical


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Shared memory Processors and disks have access to shared memory via a bus Very efficient communication between processors

Not scalable since bus becomes a bottleneck

Interconnection network

Memory

CPU CPU CPU CPU

(Shared-memory)


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Shared disk All processors can access all disks via a communication network Each processor has its own memory Certain degree of fault tolerance if processor/memory fails Also disks maybe have fault tolerance (e.g., RAID architecture) Interconnection to the disk systems becomes bottleneck

(Shared-disk)

Interconnection network

CPU CPU CPU CPU

Memory Memory MemoryMemory


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Shared nothing Each node consists of a processor, memory and one or more disks High-speed interconnection network between processors More scalable than shared memory or shared disk model

Increasedcommunicationcosts for non-local disk access

(Shared-nothing)Interconnection network

CPU

CPU CPU

CPU

Memory

Memory

Memory

Memory


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Hierarchical Combines the different models (composition) Top-level is shared nothing between nodes

Each node can be a shared memory or shared disk subsystem


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Object Databases

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Motivation to overcome weakness of relationalapproach.

Richer data models. Closer integration with programming languages.

Better for situations that there are many objects, but lessdata for each object. E.g., CAD

ODMG created OQL standard, but very few vendorsimplemented it


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Object Databases

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Kinds of object databases Object relational (Oracle, DB2, PostgreSQL) Semantic data model (Jasmine) Programming language centred (Objectivity, FastObjects,

ObjectStore). Commercial Object database (ObjectDB)


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Mobile databases

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Users want to access information on the move via mobiledevices

Tourist information systems Salesperson who is visiting their customers Emergency services

New requirements for mobile DBMSs Small footprint databases that can run on mobile devices with

limited resources

Location dependent queries Context-aware queries


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Mobile databases (cont.)

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Communicate with centralised database server via wireless networkor fixed Internet connection

Replicate data on a centralised server and on a mobile device Synchronisation challenges

Caching of data and transactions to cope with potential networkconnection failures

Opportunistic (peer-to-peer based) information exchange with othermobile DBMSs

e.g., dynamic P2P Bluetooth connections with other devices in range(proximity-based information exchange)

Security

Which portion of a database can/should be replicated on a mobile device?


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Cloud computing

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Internet-based computing with on-demand and pay-per-use accessto shared resources, data and software

Main characteristics

Elasticity Pay only for the services that are actually used (pay-as-you-go) Web-based access(e.g., Web Service API or browser)


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Cloud computing Layers

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Cloud data service example

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Amazon Simple Storage Service (Amazon S3) Online storage service with unlimited storage space Store objects (up to 5GB in size) in buckets Web Service API

Amazon SimpleDB Distributed database written in Erlang Offers a Web Service API Makes use of S3 and EC2 On demand scaling Non-relational data store

Schemaless Hashtables with set of key-value pairs


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Exercises

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List the benefits of multi-tiered architecture Compare with the MVC (Model-View-Controller)

architecture

DBMS Architecture Features(3)

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