distributed and mobile dbmss transparencies. ©pearson education 2009 chapter 16 - objectives main...

Distributed and mobile DBMSsTransparencies

©Pearson Education 2009

Chapter 16 - ObjectivesMain concepts of distributed DBMSs

(DDBMSs)Differences between DDBMSs and distributed

processing.Advantages and disadvantages of distributed

databases.Main issues associated with distributed

database design.How fragmentation should be carried out.The importance of allocation and replication.

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Chapter 16 - ObjectivesLevels of transparency that should be

provided by DDBMS.Main concepts associated with database

replication.Main concepts associated with mobile

DBMSs.

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DDBMS concepts Distributed Database

A logically interrelated collection of shared data (and a description of this data), physically distributed over a computer network.

Distributed DBMSSoftware system that permits the management of the distributed database and makes the distribution transparent to users.

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DDBMS conceptsCollection of logically-related shared data.Data split into fragments.Fragments may be replicated.Fragments/replicas allocated to sites.Sites linked by a communications network.Data at each site is under control of a DBMS.DBMSs handle local applications

autonomously.Each DBMS participates in at least one global

application.

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Distributed DBMS

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Distributed processingA centralized database that can be accessed

over a computer network.

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Advantages of DDBMSs

Reflects organizational structure

Improved shareability and local autonomy

Improved availability

Improved reliability

Improved performance

Economics

Modular growth.

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Disadvantages of DDBMSs

Complexity

Cost

Security

Integrity control more difficult

Lack of standards

Lack of experience

Database design more complex.

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Types of DDBMSHomogeneous DDBMS

All sites use same DBMS product. Much easier to design and manage. Approach provides incremental growth and

allows increased performance.Heterogeneous DDBMS

Sites may run different DBMS products, with possibly different underlying data models.

Occurs when sites have implemented their own databases and integration is considered later.

Translations required. Typical solution: gateways.

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Multidatabase system (MDBS)

DDBMS in which each site maintains complete autonomy.

DBMS that resides transparently on top of existing database and file systems and presents a single database to its users.

Allows users to access and share data without requiring physical database integration.

Unfederated MDBS (no local users) and federated MDBS.

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Taxonomy of DBMSs

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Distributed database designThree key issues:

Fragmentation,Allocation,Replication.

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©Pearson Education 2009 14

Distributed database design

FragmentationRelation may be divided into a number of sub-relations, which are then distributed.

AllocationEach fragment is stored at site with “optimal” distribution.

ReplicationCopy of fragment may be maintained at several sites.


FragmentationDefinition and allocation of fragments

carried out strategically to achieve:Locality of Reference.Improved Reliability and Availability.Improved Performance.Balanced Storage Capacities and Costs.Minimal Communication Costs.

Involves analyzing most important applications, based on quantitative/qualitative information.


FragmentationQuantitative information may include:

frequency with which an application is run;site from which an application is run;performance criteria for transactions and

applications.

Qualitative information may include transactions that are executed by application, type of access (read or write), and predicates of read operations.


Why fragment?Usage: Applications work with views

rather than entire relations. Efficiency: Data is stored close to where

it is most frequently used. Data that is not needed by local applications is

not stored.Parallelism: With fragments as unit of

distribution, transaction can be divided into several subqueries that operate on fragments.

Security: Data not required by local applications is not stored and so not available to unauthorized users.


Why fragment? - DisadvantagesPerformance,Integrity.


Correctness rules for fragmentationThree correctness rules:

Completeness,Reconstruction,Disjointness.


Correctness rules for fragmentationCompleteness

If relation R is decomposed into fragments R1, R2, ... Rn, each data item that can be found in R must appear in at least one fragment.

ReconstructionMust be possible to define a relational

operation that will reconstruct R from the fragments.

Reconstruction for horizontal fragmentation is Union operation and Join for vertical.


Correctness rules for fragmentationDisjointnessIf data item di appears in fragment Ri, then

it should not appear in any other fragment. Exception: vertical fragmentation, where

primary key attributes must be repeated to allow reconstruction.

For horizontal fragmentation, data item is a tuple.

For vertical fragmentation, data item is an attribute.


Types of fragmentation Four types of fragmentation:

Horizontal,Vertical,Mixed,Derived.

Other possibility is no fragmentation:

If relation is small and not updated frequently, may be better not to fragment relation.


Horizontal and vertical fragmentation


Mixed fragmentation


Horizontal fragmentationConsists of a subset of the records of a table.

Defined using WHERE clause in SQL SELECT.

For example:

DC1: SELECT * FROM DVDCopy WHERE dCenterNo=‘D001’;





Vertical fragmentationConsists of a subset of the columns of a table.

Defined using SELECT clause of SQL SELECT.

For example:

S1: SELECT staffNo, position, salary FROM Staff;

S2: SELECT staffNo, name, eMail, dCenterNo

FROM Staff;


Mixed fragmentationConsists of a horizontal fragment that is

vertically fragmented, or a vertical fragment that is horizontally fragmented.

For example, from above example:

SELECT * FROM S2 WHERE dCenterNo = ‘D001’;





Derived horizontal fragmentation A horizontal fragment that is based on horizontal

fragmentation of a parent relation.Ensures that fragments that are frequently joined

together are at same site.For example:

DR1: SELECT dr.* FROM DVDRental dr, DC1

WHERE dr.DVDNo = DC1.DVDNo;








Data allocation

Centralized: Consists of single database and DBMS stored at one site with users distributed across the network.

Partitioned: Database partitioned into disjoint fragments, each fragment assigned to one site.

Complete Replication: Consists of maintaining complete copy of database at each site.

Selective Replication: Combination of partitioning, replication, and centralization.


Comparison of data allocation strategies


Distributed database design methodology1. Use normal methodology to produce a design for

the global relations.2. Examine topology of system to determine where

databases will be located.3. Analyze most important transactions and identify

appropriateness of horizontal/vertical fragmentation.

4. Decide which tables are not to be fragmented.5. Examine tables on 1 side of relationships and

determine a suitable fragmentation schema. Tables on many side may be suitable for derived fragmentation.


Transparencies in a DDBMSDistribution Transparency

Fragmentation TransparencyLocation TransparencyReplication TransparencyLocal Mapping TransparencyNaming Transparency


Transparencies in a DDBMSTransaction Transparency

Concurrency TransparencyFailure Transparency

Performance Transparency

DBMS Transparency


Distribution transparencyDistribution transparency allows user to

perceive database as single, logical entity. If DDBMS exhibits distribution

transparency, user does not need to know:data is fragmented (fragmentation

transparency), location of data items (location transparency),otherwise call this local mapping

transparency. With replication transparency, user is

unaware of replication of fragments.


Transaction transparencyEnsures that all distributed

transactions maintain distributed database’s integrity and consistency.

In IBM’s Distributed Relational Database Architecture (DRDA), four types of transactions:Remote requestRemote unit of workDistributed unit of workDistributed request.


IBM’s DRBA


Concurrency transparencyAll transactions must execute independently

and be logically consistent with results obtained if transactions executed one at a time, in some arbitrary serial order.

Same fundamental principles as for centralized DBMS.

DDBMS must ensure both global and local transactions do not interfere with each other.

Similarly, DDBMS must ensure consistency of all subtransactions of global transaction.


Concurrency transparencyReplication makes concurrency more complex. If a copy of a replicated data item is updated,

update must be propagated to all copies. Could propagate changes as part of original

transaction, making it an atomic operation. However, if one site holding copy is not reachable, then transaction is delayed until site is reachable.

Could limit update propagation to only those sites currently available. Remaining sites updated when they become available again.

Could allow updates to copies to happen asynchronously, sometime after the original update. Delay in regaining consistency may range from a few seconds to several hours.


Failure transparencyDDBMS must ensure atomicity and

durability of global transaction.Means ensuring that subtransactions of

global transaction either all commit or all abort.

Thus, DDBMS must synchronize global transaction to ensure that all subtransactions have completed successfully before recording a final COMMIT for global transaction.

Must do this in presence of site and network failures.


Failure transparency – Two-phase CommitTwo phases: a voting phase and a decision phase. Coordinator asks all participants whether they are

prepared to commit transaction. If one participant votes abort, or fails to respond within a

timeout period, coordinator instructs all participants to abort transaction.

If all vote commit, coordinator instructs all participants to commit.

All participants must adopt global decision.If participant votes abort, free to abort transaction

immediatelyIf participant votes commit, must wait for

coordinator to broadcast global-commit or global-abort message.


Failure transparency – Two-phase Commit


Performance transparencyDDBMS must perform as if it were a centralized

DBMS. DDBMS should not suffer any performance degradation

due to distributed architecture. DDBMS should determine most cost-effective strategy to

execute a request.

Must consider fragmentation, replication, and allocation schemas.

Distributed QP maps data request into ordered sequence of operations on local databases. DQP has to decide: which fragment to access; which copy of a fragment to use; which location to use.


Performance transparencyDQP produces execution strategy optimized

with respect to some cost function. Typically, costs associated with a distributed

request include:

I/O cost;CPU cost;communication cost.


Performance transparency - ExampleMember(memberNo, mCity) 100000 records in

Seattle

DVDCopy(DVDNo, catalogNo) 1000000 records in NY

Rental(memberNo, DVDNo) 1000000 records in Seattle

SELECT dc.DVDNo

FROM DVDCopy dc, Rental r, Member m

WHERE dc.DVDNo=r.DVDNo AND r.memberNo=m.memberNo AND dc.catalogNo = ‘634817’ AND m.mCity = ‘Chicago’;

Each record is 20 characters long.1000 members in Chicago; 200 000 rentals of ‘War of the

Worlds’ (634817).Computation time negligible compared to communication

time.


Performance transparency - ExampleStrategy Time

(1) Move DVDCopy table to Seattle and process query there. 33.3 mins

(2) Move Member and Rental tables to New York and process query there. 1.17hours

(3) Join Member & Rental at Seattle, select records for Chicago members, and for

each of these in turn, check at New York for an associated catalogNo = ‘634817’. 33.3mins

(4) Select DVD copies with catalogNo = ‘634817’ at New York and for each

one found, check at Seattle for a rental involving a member living in Chicago. 11.12hours

(5) Join Member and Rental tables at Seattle, select Chicago members, project

result over DVDNo, and move this result to New York for matching with

catalogNo = ‘634817’. 2 seconds

(6) Select DVD copies with catalogNo = ‘634817’ at New York and move the

result to Seattle for matching with rentals associated with Chicago members. 41 seconds


Dates 12 rules for a DDBMS0. Fundamental Principle

To the user, a distributed system should look exactly like a nondistributed system.

1. Local Autonomy2. No Reliance on a Central Site3. Continuous Operation4. Location Independence5. Fragmentation Independence6. Replication Independence


Dates 12 rules for a DDBMS7. Distributed Query Processing8. Distributed Transaction

Processing9. Hardware Independence10. Operating System Independence11. Network Independence12. Database Independence

Last four rules are ideals.


Replication serversReplication

Process of generating and reproducing multiple copies of data at one or more sites.

Provides users with access to current data where and when they need it.

Provides number of benefits, including improved performance when centralized resources get overloaded, increased reliability and data availability, and support for mobile computing and data warehousing.


Replication serversSynchronous – updates to replicated data are part of enclosing transaction. If one or more sites that hold replicas are

unavailable transaction cannot complete. Large number of messages required to

coordinate synchronization.Asynchronous - target database updated after source database modified. Delay in regaining consistency may range

from few seconds to several hours or even days.


Replication - functionalityAt basic level, has to be able to copy data

from one database to another (synch or asynchronous).

Other functions include:Scalability.Mapping and Transformation.Object Replication.Specification of Replication Schema.Subscription mechanism. Initialization mechanism.


Replication – data ownershipOwnership relates to which site has

privilege to update the data. Main types of ownership are:

Master/slave (or asymmetric replication), Workflow, Update-anywhere (or peer-to-peer or

symmetric replication).


Replication – Master/Slave OwnershipAsynchronously replicated data is owned by

one (master) site, and can be updated by only that site.

Using ‘publish-and-subscribe’ metaphor, master site makes data available.

Other sites ‘subscribe’ to data owned by master site, receiving read-only copies.

Potentially, each site can be master site for non-overlapping data sets, but update conflicts cannot occur.


Replication – Workflow OwnershipAvoids update conflicts, while providing

more dynamic ownership model. Allows right to update replicated data to

move from site to site. However, at any one moment, only ever one

site that may update that particular data. Example is order processing system, which

follows steps, such as order entry, credit approval, invoicing, shipping, and so on.


Replication – Update Anywhere OwnershipCreates peer-to-peer environment where

multiple sites have equal rights to update replicated data.

Allows local sites to function autonomously, even when other sites are not available.

Shared ownership can lead to conflict scenarios and have to detect conflict and resolve it.


Mobile databasesWitnessing increasing demands on mobile computing to

provide support for growing number of mobile workers. Such a workforce require to work as if in the office but

in reality they are working from remote location places. With rapid expansion of cellular, wireless, and satellite

comms, soon be possible for mobile users to access any data, anywhere, at any time.

However, , business etiquette, practicalities, security, and costs may still limit communication (eg. can’t get online connection for as long as want, whenever you want).

Mobile databases offer a solution for some of these restrictions.


Mobile databasesMobile database

A database that is portable and physically separate from a centralized database server but is capable of communicating with that server from remote sites allowing the sharing of corporate data.

Components of a mobile database environment include:corporate database server and DBMS that manages and

stores the corporate data and provides corporate applications;

remote database and DBMS that manages and stores the mobile data and provides mobile applications;

mobile database platform that includes laptop, PDA, or other Internet access devices;

two-way communication links between the corporate and mobile DBMS.


Mobile database environment


Mobile DBMSsAdditional functionality required of mobile

DBMSs includes ability to:communicate with centralized database server

through modes such as wireless or Internet access;replicate data on centralized database server and

mobile device;synchronize data on centralized database server

and mobile device;capture data from various sources such as the

Internet; manage data on the mobile device; analyze data on a mobile device; create customized mobile applications.

distributed and mobile dbmss transparencies. ©pearson education 2009 chapter 16 - objectives main...

Documents

database replication

single database

existing database

data split

physical database integration

local users

related shared data

different dbms products