Distributed Database Concept

7/21/2019 Distributed Database Concept

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COMP 302 Valentina Tamma

Distributed Databases

Connolly & Begg. Chapter 22. Third edition


Distributed Databases Basic Concepts

Concepts.

Advantages and disadvantages of distributeddatabases.

Functions and architecture for a DDBMS.

Distributed database design.

Levels of transparency.

Comparison criteria for Distributed DBMSs.


Why distributed databases?

Some initial motivations:

The development of computer networks promotesdecentralization.

In a company, the database organization might reflect theorganizational structure, which is distributed into units.Each unit maintains its own database.

Sharing of data can be achieved by developing adistributed database system which:

makes data accessible by all units

stores data close to where it is most frequently used.

COMP 302 Valentina Tamma3

Concepts

Distributed Database

A logically interrelated collection of shared data (and adescription of this data), physically distributed over acomputer network.

Distributed DBMS (DDBMS)

Software system that permits the management of the

distributed database and makes the distributiontransparent to users.


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An example of DDBMS


DDBMS - characteristics

Collection 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 globalapplication.


These are not DDBMSs

Distributed Processing A centralized database that canbe accessed over a computer network.


These are not DDBMSs

Parallel DBMS

A DBMS running across multiple processors anddisks designed to execute operations in parallel,whenever possible, to improve performance.

Based on premise that single processor systems can nolonger meet requirements for cost-effective scalability,reliability, and performance.

Parallel DBMSs link multiple, smaller machines to achievesame throughput as single, larger machine, with greaterscalability and reliability.


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Parallel DBMS

Main architectures for parallel DBMSs are:

Shared memory,

Shared disk,

Shared nothing.


Parallel DBMS

(a) sharedmemory

(b) shared disk

(c) sharednothing


Advantages of DDBMSs

Reflects Organizational Structure

Improved Sharing and Local Autonomy

Improved AvailabilityA failure does not make the entire system inoperable

Improved ReliabilityData may be replicated

Improved PerformanceData are local to the site of greatest demand

Economics

Many small computers cost less than a big one! Modular Growth

easy to add new modules


Disadvantages of DDBMSs

Complexity

CostEspecially in system management

Securitynetwork must be made secure

Integrity Control More Difficult

Lack of Standards

Lack of Experience Database Design More Complex

due to fragmentation, allocation of fragments to a specificsite, ..


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Types of DDBMS

Homogeneous DDBMS

All sites use same DBMS product (eg.Oracle)

Fairly easy to design and manage.

Heterogeneous DDBMS

Sites may run different DBMS products (eg. Oracle andIngress)

Possibly different underlying data models (eg. relationalDB and OO database)

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

We wont consider heterogeneous DDBMSs here.


Multidatabase System (MDBS)

DDBMS in which each site maintains completeautonomy.

DBMS that resides transparently on top of existingdatabase and file systems and presents a singledatabase to its users.

Allows users to access and share data withoutrequiring physical database integration.

Unfederated MDBS (no local users) and federatedMDBS.


Overview of Networking

Network - Interconnected collection of autonomouscomputers, capable of exchanging information.

Local Area Network (LAN) intended for connectingcomputers at same site.

Wide Area Network (WAN) used when computers or LANsneed to be connected over long distances.

WAN relatively slow and less reliable than LANs. DDBMS

using LAN provides much faster response time than oneusing WAN.


Overview of Networking


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Functions of a DDBMS

Expect DDBMS to have at least the functionality ofa DBMS (see Connolly & Begg. Chapter 2. Third edition)

Also to have following functionality: Extended communication services.

Extended Data Dictionary.

Distributed query processing.

Extended concurrency control.

Extended recovery services.

Extended security control.


Reference Architecture for DDBMS

Due to diversity, no accepted architecture equivalent toANSI/SPARC 3-level architecture for DBMSs.

A possible reference architecture consists of: Set of global external schemas.

Global conceptual schema (GCS).

Fragmentation schema and allocation schema.

Set of schemas for each local DBMS conforming to 3-levelANSI/SPARC .

Some levels may be missing, depending on levels oftransparency supported.





Global Conceptual Schema is the logicaldescription of the DB as if it were not distributed. Itcontains definitions of entities, relationships,constraints, security, and integrity information.

Fragmentation and Allocation Schemas describehow data are logically partitioned, and where theyare located, taking replication into account.

Local Schemas are the logical descriptions of thelocal DBs.


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Components of a DDBMS



Issues in Distributed Database Design



Three key issues we have to consider:

Data Allocation: where are data placed? Data should bestored at site with "optimal" distribution.

Fragmentation: relation may be divided into a number ofsub-relations (called fragments) , which are stored indifferent sites.

Replication: copy of fragment may be maintained atseveral sites.



Definition and allocation of fragments carried outstrategically to achieve:

Locality of Reference

Improved Reliability and Availability

Improved Performance

Balanced Storage Capacities and Costs

Minimal Communication Costs.

Involves analysing most important transactions,based on quantitative/qualitative information.


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Fragmentation

Quantitative information may include:

frequency with which a transaction is run;

site from which a transaction is run; performance criteria for transactions.

Qualitative information may include transactions that areexecuted such as:

type of access (read or write);

predicates of read operations.


Data Allocation

Four strategies regarding placement of data:

Centralized

Partitioned (or Fragmented)

Complete Replication

Selective Replication


Data Allocation

Centralized: Consists of single database stored at one sitewith users distributed across the network.(This is not a DDB but distributed processing!!)

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

Complete Replication: Consists of maintaining completecopy of database at each site.

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


Fragmentation

A relation R is divided into fragments r1, r2, rn,which contain enough information to allowreconstruction of R

Example:We have a relation Sells(pub, address,price,type)

Type is bitter or lager.

We can split Sells into twp dfferent fragments: SellsBitter= type = bitter(Sells)

SellsLager= type = lager(Sells)


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Vertical Fragmentation

Each fragment consists of a subset of attributes of a relationR.

Defined using projection operation of relational algebra:

a1,an(R)

Determined by establishing affinityof one attribute to another.

Example:

Relation: Bars(name,address,licence,employees,owner)

Fragments:

name,address,licence (Bars)

name,address,employees,owner(Bars)


Mixed Fragmentation

We can also mix horizontal and vertical fragmentation.

We obtain a fragment that consist of an horizontalfragment that is vertically fragmented, or a verticalfragment that is horizontally fragmented.

Defined using Selection and Projection operations ofrelational algebra.

p(a1,an(R))

a1,an(p(R))


Example - Mixed Fragmentation

S1 = staffNo, position, sex, DOB, salary(Staff)

S2 = staffNo, fName, lName, branchNo(Staff)

S21 = branchNo=B003(S2)




Derived Horizontal Fragmentation

A horizontal fragment that is based onhorizontal fragmentation of a parent relation.

Ensures that fragments that are frequentlyjoined together are at same site.

Defined using Semijoin operation of relationalalgebra:

Ri = R>F Si, 1 i w


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Correctness of Fragmentation

Recostruction: we must be able to reconstruct the entire Rfrom fragments.

For horizontal fragmentation is union operation.

R = r1 r2 rn,

For vertical fragmentation is natural join operation.

R = r1>< r2>< r2

Disjointness: The two fragments are disjoint, except for the primarykey, name, which is necessary for reconstruction


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Transparency in Distributed databases


Transparencies in a DDBMS

Distribution Transparency

Transaction Transparency

Performance Transparency

DBMS Transparency


Distribution Transparency

The user has to perceive the DDB as a single,logical entity

Fragmentation Transparency: the user does not need toknow that data is fragmented

Location Transparency: the user does not need to knowthe location of data items

Replication Transparency: the user is unaware ofrelication of data.

Naming transparency: items in a database must have aunique name, but users dont need to worry about it.


Naming Transparency

Each item in a DDB must have a unique name.

DDBMS must ensure that no two sites create adatabase object with same name.

Solution 1: create central name server.

Disadvantages:

loss of some local autonomy;

central site may become a bottleneck;

low availability; if the central site fails, remaining sitescannot create any new objects.


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Naming Transparency

Solution 2: prefix object with identifier of site thatcreated it.

Example: Beer created at site S1 might be namedS1.Beer.

Disadvantage: loss of distribution transparency.


Naming Transparency

Solution 3: use aliases for each database object.

Example: S1.Beer might be known as local_Beerby user at site S1.

The DDBMS has task of mapping an alias toappropriate database object.


Transaction Transparency

Ensures that all distributed transactions maintaindistributed databases integrity and consistency.

Distributed transaction accesses data stored at more thanone location.

Each transaction is divided into number of sub-transactions, one for each site that has to be accessed.

DDBMS must ensure the indivisibility of both the globaltransaction and each sub-transactions.

Must ensure both concurrency transparency, and failuretransparency


Example - Distributed Transaction

Relation: Sells(pub, beer,price,type)

Fragments:

SellsBitter= type = bitter(Sells)

SellsLager= type = lager(Sells)

The two fragments are at two different sites.

Transaction T prints out the names of all pubs in the relation

sells. This transaction is split into two sub-transactions,one for each fragment.


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Example - Distributed Transaction

T prints out names of all staff, using schema

defined above as S1, S2, S21, S22, and S23.Define three subtransactions TS3, TS5, and TS7to represent agents at sites 3, 5, and 7.


Concurrency Transparency

All transactions must execute independently and belogically consistent with results obtained if transactionsexecuted one at a time, in some arbitrary serial order.

Same fundamental principles as for centralised DBMS.

DDBMS must ensure both global and local transactions donot interfere with each other.

Similarly, DDBMS must ensure consistency of all sub-transactions of global transaction.

Techniques for concurrency control. Usually different fromthe ones for DBMS.



Replication 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 originaltransaction, 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 sitescurrently available. Remaining sites updated whenthey become available again.

Could allow updates to copies to happenasynchronously, sometime after the originalupdate. Delay in regaining consistency may rangefrom a few seconds to several hours.


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Failure Transparency

DDBMS must ensure atomicity and durability ofglobal transaction.

Means ensuring that sub-transactions of globaltransaction either all commit or all abort.

Thus, DDBMS must synchronize globaltransaction to ensure that all sub-transactionshave completed successfully before recording afinal COMMIT for global transaction.

Must do this in presence of site and networkfailures.



DDBMS must perform as if it were acentralized DBMS:

DDBMS should not suffer any performancedegradation due to distributed architecture.

DDBMS should determine most cost-effectivestrategy to execute a request.



Distributed Query Processor (DQP) maps datarequest into ordered sequence of operations onlocal databases.

It must consider fragmentation, replication, andallocation schemas.

DQP has to decide:

which fragment to access;

which copy of a fragment to use; which location to use.



DQP produces execution strategy optimisedwith respect to some cost function.

Typically, costs associated with a distributedrequest include:

I/O cost;

CPU cost;

communication cost.


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Performance Transparency - Example

Property(Pno, City) 10000 records in London

Renter(Rno,Max_Price) 100000 records in Glasgow

Viewing(Pno, Rno) 1000000 records in London

SELECT p.pno

FROM property p INNER JOIN

(renter r INNER JOIN viewing v ON r.rno = v.rno)

ON p.pno = v.pno

WHERE p.city=Aberdeen AND r.max_price > 200000;



Assume:

Each tuple in each relation is 100 characters long.

10 renters with maximum price greater than200,000.

100 000 viewings for properties in Aberdeen.

Computation time negligible compared tocommunication time.




Dates 12 Rules for a DDBMS

0. Fundamental Principle

To the user, a distributed system should look exactly likea non-distributed system.

1. Local Autonomy

2. No Rel iance on a Centra l Site

3 . Con tinuous Operat ion

4 . Loca tion Independence

5. Fragmentation Independence

6. Replication Independence


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Dates 12 Rules for a DDBMS

0. Fundamental Principle

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

7. Dis tr ibuted Query Process ing

8. Distributed Transaction Processing

9. Hardware Independence

10. Operating System Independence

11. Network Independence

12. Database Independence

Note: last four rules are ideal!


Distributed Transaction Management

DDBMS must ensure:

synchronization of sub-transactions with other local

transactions executing concurrently at a site; synchronization of sub-transactions with global

transactions running simultaneously at same or differentsites.

Global transaction manager (transactioncoordinator) at each site, to coordinate global andlocal transactions initiated at that site.


Distributed Concurrency Control

Techniques for Distributed Concurrency Controlmust ensure distributed serializability.

Locking protocols (extensions of 2PL protocol)Distributed Deadlock management.

Timestamping methods (extend the definition oftimestamp so that it includes a site identifier)

Documents

Distributed Database Concept