distributed dbmss – concepts and design

Distributed DBMSs – Concepts and Design

Chapter 24 in Textbook

Overview

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Concepts. What is a distributed DBMS? Distributed Processing. Homogeneous vs. Heterogeneous.

Functions of a DDBMS. Components of a DDBMS. Advantages and Disadvantages. DDBMS Design.

Fragmentation. Replication. Allocation.

DDBMS Transparencies. Date’s 12 Rules for a DDBMS.

Concepts

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Centralized DBMS systems with a single logical database

located at one site under the control of a single DBMS.

Distributed DBs logically interrelated collection of shared

data physically distributed over a computer network.

Applications can be classified into:

Local applications.

Global applications.

Distributed DBMS

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Distributed DBMS The software system that:

manages the distributed DBs.

makes distribution transparent to users.

allows users to access data on their own site as well

as remote sites.

Transparent distribution is the fundamental

principle of DDBMS.

Characteristics of DDBMS

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• A collection of logically related shared data.

• The data is split into a number of fragments.

• Fragments may be replicated.

• Fragments/replicas are allocated to sites.

• The sites are linked by a communications networks.

• The data at each site is under the control of a DBMS.

• The DBMS at each site can handle local applications.

• Each DBMS participates in at least one global application.

Distributed DBMS Topology

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Site 1

Site 2

Site 3

Site 4

Computer Network

Data itself is distributed and access to it can be local or remote.

Distributed Processing

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Site 1

Site 2

Site 3

Site 4

Computer Network

Data itself is centralized but access to it can be local or remote.

Homogeneous vs. Heterogeneous DDBMS

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Homogenous system: all sites use the same DBMS product.

Heterogeneous system: sites may run different DBMS

products & data model.

Possible differences between data in different DBS:

• Data type difference.

• Value difference.

• Semantic difference.

Functions of a DDBMS

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• Provide access to remote sites and allow transfer of

queries & data among the network’s site.

• Store data distribution details.

• Distributed data processing.

• Security control.

• Concurrency control.

• Recovery services.

Components of a DDBMS

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Site 1

Site 3

Computer Network

DDBMS

DC LDBMS

DDBMS

DC

GSC

GSC

DB

Global system catalog

Data communication component

Advantages of DDBMS

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• Reflects organizational structure.

• Improve sharability & local autonomy.

• Improved availability.

• Improved reliability.

• Improved performance.

Disadvantages of DDBMS

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• Complexity.

• Cost.

• Security.

• Integrity control more difficult.

• Lack of standards.

• Lack of experience.

• DB design more complex.

Distributed Relational DB Design

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We have a group of tables and we want to distribute them between a group of sites.

Consists of 3 major steps:1. Fragmentation divide a relation into a number of sub-relations (fragments).

(Horizontal & vertical).

2. Replication make a copy of a fragment.

3. Allocation decide where (which site) each of the fragments and replicas are

to be stored.

Distributed Relational DB Design

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When we fragment, replicate and allocate, we try

to achieve:• Locality of reference.

• Improved reliability and availability.

• Good performance.

• Balanced storage capacities and costs.

• Minimal communication costs.

Rules of Fragmentation

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Completeness: Nothing (rows or columns) gets lost while we fragment.

Reconstruction: We can get back the original table after we fragmented it.

Dis-jointness: No row or column appears in 2 fragments (there is 1 exception).

Types of Fragmentation

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Horizontal fragmentation

Vertical fragmentation

Mixedfragmentation

Original PropertyForRent Table

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PropertyNo

Street City PostCode Type Rooms Rent OwnerNo

StaffNo BranchNo

PA14 16 Holhead Aberdeen AB7 5SU House 6 650 CO46 SA9 B007

PG4 6 Lawrence Glasgow G11 9QX Flat 3 350 CO40 SG14 B003

PG16 5 Novar Dr Glasgow G12 9AX Flat 4 450 CO93 SG14 B003

PG21 18 Dale Rd Glasgow G12 House 5 600 CO87 SG37 B003

PG36 2 Manor Rd Glasgow G32 4QX Flat 3 375 CO93 SG37 B003

PL94 6 Argy11 St London NW2 Flat 4 400 CO87 SL41 B005

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BranchNo

Based on type of property.

P1: Type=‘House’ (PropertyForRent)

P2: Type=‘Flat’ (PropertyForRent)

Horizontal Fragmentation

PropertyNo


StaffNo BranchNo



PropertyNo


StaffNo BranchNo





Fragment P1

Fragment P2

Original Staff Table

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StaffNo Position sex DOB Salary FName LName BranchNo

SL21 Manager M 1 Oct 93 30000 John White B005

SG37 Assistant F 10 Nov 60 12000 Ann Beech B003

SG14 Supervisor M 24 Mar 58 18000 David Ford B003

SG5 Assistant F 3 Jun 40 24000 Susan Brand B007

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S1: staffno,Position,sex,DOB, Salary(STAFF)

S2: staffno,fname,lname,BranchNo(STAFF)

Vertical Fragmentation

StaffNo Position sex DOB Salary

SL21 Manager M 1 Oct 93 30000

SG37 Assistant F 10 Nov 60 12000

SG14 Supervisor M 24 Mar 58 18000

SG5 Assistant F 3 Jun 40 24000

StaffNo FName LName BranchNo

SL21 John White B005

SG37 Ann Beech B003

SG14 David Ford B003

SG5 Susan Brand B007

Fragment S1 Fragment S2

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FName LName BranchNoFragment S2.3


Fragment S2.1

StaffNo LName BranchNo

Fragment S2.2S2.1: BranchNo=‘B005’ (S2)

S2.2: BranchNo=‘B003’ (S2)

S2.3: BranchNo=‘B007’ (S2)

S1: staffno,Position,sex,DOB, Salary(STAFF)

S2: staffoo,fname,lname,BranchNo(STAFF)

Fragment S1

Mixed Fragmentation – Vertical then Horizontal


SL21 John White B005


SG37 Ann Beech B003

SG14 David Ford B003


SG5 Susan Brand B007

StaffNo Position sex DOB Salary

SL21 Manager M 1 Oct 93 30000

SG37 Assistant F 10 Nov 60 12000

SG14 Supervisor M 24 Mar 58 18000

SG5 Assistant F 3 Jun 40 24000

Derived Horizontal Fragmentation

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Derived Horizontal Fragmentation is the horizontal fragmentation of a table (child), T1, because we horizontally fragmented another related table (parent), T2.

It is not explicitly specified in design but implied from fragmentation of T2.

T1 (child) has a foreign key that belongs to T2 (parent).

Relationship between T1 and T2 either 1-to-1 or Many-to-1.

Use Semi-join operation:


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You were required by the design to horizontally fragment Staff table. S1: BranchNo=‘B003’ (Staff) S2: BranchNo=‘B005’ (Staff) S3: BranchNo=‘B007’ (Staff)







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Fragment S1

Fragment S2

Fragment S3









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After we fragmented Staff, we found out that there is a table related to it, PropertyForRent.

Because Staff is now fragmented, it makes sense to fragment PropertyForRent too.

PropertyForRent

Staffhandle

s1 N

S1: BranchNo=‘B003’ (Staff)

S2: BranchNo=‘B005’ (Staff) Pi: PropertyForRent staffNo Si

S3: BranchNo=‘B007’ (Staff)

Original PropertyForRent Table

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PropertyNo


StaffNo BranchNo







27


PropertyNo


StaffNo BranchNo





PropertyNo


StaffNo BranchNo


PropertyNo


StaffNo BranchNo


Fragment P1

Fragment P2

Fragment P3

Transparencies in a DDBMS

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4 main transparencies:1. Distribution Transparency.

a. Fragmnetation.b. Location. c. Replication.d. Local Mapping.e. Naming.

2. Transaction Transparency.3. Performance Transparency.4. DBMS Transparency.

1. Distribution Transparency

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Allows the user to perceive the DB as a single, logical entity. Types:

a. Fragmentation: the user does not need to know the data is fragmented.

b. Location: the user does not need to know the location of fragments.

c. Replication: the user does not need to know the fragments are replicated.

d. Local Mapping: the user specifies the fragment and its location.

e. Naming: DDBMS makes sure every item name is unique.

Consider the distribution of the STAFF relation: S1: staffno,Position,sex,DOB, Salary(STAFF) S2: staffno,fname,lname,BranchNo(STAFF) S21: BranchNo=‘B003’ (S2) S22: BranchNo=‘B005’ (S2) S22: BranchNo=‘B007’ (S2)

a. Fragmentation Transparency

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Highest level of distribution transparency. The user does not need to know that the data is

fragmented. User treats DDB like a centralized DB. The database access are based on the global schema. Fragmentation of the data can be changed without

impacting the user.

Example:

SELECT Fname, Lname

FROM Staff

WHERE position = ‘Manager’;

b. Location Transparency

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The middle level of distribution transparency.

The user must know that the data is fragmented but still does not need

to know the location of the data.

Data location can be changed without impact on the user.

Example:

SELECT Fname, Lname FROM S21

WHERE staffNo IN (SELECT staffNo FROM S1 WHERE position=‘Manager’)

UNION



UNION



c. Replication Transparency

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User unaware of replication and location but knows that data is fragmented.

On the same level with location transparency.

d. Local Mapping Transparency

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The lowest level of distribution transparency.

The user knows that the data is fragmented and the location of the data.

Example:

SELECT Fname, Lname FROM S21 AT SITE 3

WHERE staffNo IN

(SELECT staffNo FROM S1 AT SITE 5 WHERE position=‘Manager’)

UNION


WHERE staffNo IN


UNION


WHERE staffNo IN


e. Naming Transparency

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Each item in distributed database must have a unique name.

DDBMS must ensure that no two sites violate that.

Solutions Create a central name server.

Bottleneck. against local autonomy.

Prefix an object with the identifier of the site. loss of distribution transparency.

2. Transaction Transparency

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All transactions must ensure the consistency and integrity of the DDB.

Each transaction that needs to access data in multiple sites is divided into multiple sub-transactions.

Even if transaction is split, atomicity has to be maintained.

3. Performance Transparency

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DDBMS performs as if it were a centralized DBMS.

Should not suffer because it is distributed (network communication cost).

When a site issues a query, the system must figure out the fastest way of executing it.

Distributed Query Processor (DQP) must figure out: Which fragment to access. Which copy of fragment to access (if replication is used). Where are the fragments.


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Consider the following distributed DB: Property(PropertyNo, city) 10,000 records in London Client(ClientNo, maxPrice) 100,000 records in Glasgow Viewing(PropertNo, ClientNo) 1,000,000 records in London

London site wants to list properties in Aberdeen that have been viewed by clients who have a maximum price limit greater than 200,000.

SELECT p.propertyNo

FROM Property P INNER JOIN

(Client c INNER JOIN Viewing v ON c.clientNo = v.clientNo)

ON p.propertyNo = v.propertyNo

WHERE p.city = ‘Aberdeen’ AND

c.maxprice > 200000;


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After the query is issued, DDBMS must determine the most cost-effective strategy to execute the query.

Strategies:

1. Move Client table to London and process query there.

2. Move Property and Viewing relation to Glasgow and process query there then return result.

3. Join Property and Viewing at London, project only property number and client number and move result to Glasgow to join with clients with maxPrice > 200,000 then return results.

4. Select clients at Glasgow with maxPrice > 200000, move them to London and join with viewing and Aberdeen property.

4. DBMS Transparency

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Hides the fact that different sites have different local DBMSs.

Heterogeneous DDBMSs.

Date’s 12 Rules for a DDBMS

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1. Local autonomy.

2. No reliance on a central site.

3. Continuous operation.

4. Location independence.

5. Fragmentation independence.

6. Replication independence.

7. Distributed query processing.

8. Distributed transaction processing.

9. Hardware independence.

10. Operating system independence.

11. Network independence.

12. Database independence.

distributed dbmss – concepts and design

Documents

distributed data processing

distributed dbs

distributed dbms topology6site

networks site

distributed processing7site

single dbms

remote sites

data type difference