A collection of independent databases on non databases on non-- networked computers

Chapter 13: Chapter 13: Chapter 13: Chapter 13: Distributed Databases Distributed Databases Modern Database Management Modern Database Management

  7

  7 th th

Edition Edition

  7

  

Objectives Objectives Objectives Objectives

 

  Definition of terms Definition of terms Definition of terms Definition of terms

   

  Explain business conditions driving distributed databases Explain business conditions driving distributed databases

     

  Describe salient characteristics of distributed database Describe salient characteristics of distributed database Describe salient characteristics of distributed database Describe salient characteristics of distributed database environments environments

   

  Explain advantages and risks of distributed databases Explain advantages and risks of distributed databases

   

  E Explain strategies and options for distributed database Explain strategies and options for distributed database E l i l i t t t t i i d d ti ti f f di t ib t d d t b di t ib t d d t b design design

   

  Discuss synchronous and asynchronous data replication Discuss synchronous and asynchronous data replication Discuss synchronous and asynchronous data replication Discuss synchronous and asynchronous data replication and partitioning and partitioning

   

  Discuss optimized query processing in distributed Discuss optimized query processing in distributed databases databases databases databases

   

  Explain salient features of several distributed database Explain salient features of several distributed database management systems management systems

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Definitions Definitions Definitions Definitions    

  A A A A single single single single

Distributed Database: Distributed Database: Distributed Database: Distributed Database:

  logical database logical database that is spread that is spread physically across computers in multiple physically across computers in multiple physically across computers in multiple physically across computers in multiple locations that are connected by a data locations that are connected by a data communications link communications link

      A collection A collection A collection A collection

Decentralized Database: Decentralized Database: Decentralized Database: Decentralized Database:

  of of databases on non databases on non-- independent independent networked computers networked computers networked computers networked computers

  They are NOT the same thing! They are NOT the same thing!

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Reasons for Reasons for Reasons for Reasons for

Distributed Database Distributed Database

 

  Business unit autonomy and distribution Business unit autonomy and distribution  

  Data sharing Data sharing  

  Data communication costs Data communication costs Data communication costs Data communication costs  

  

Data communication reliability and costs Data communication reliability and costs

 

  Multiple application vendors Multiple application vendors  

  Database recovery Database recovery Database recovery Database recovery  

  Transaction and analytic processing Transaction and analytic processing y y p p g g

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall Figure 13-1 – Distributed database environments (adapted from Bell and Grimson, 1992) Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Distributed Database Options Distributed Database Options Distributed Database Options Distributed Database Options

 

  Homogeneous -- Same DBMS at each node Homogeneous Same DBMS at each node  

  Autonomous -- I ndependent DBMSs Autonomous I ndependent DBMSs

   

  Non--autonomous Non autonomous -- Central, coordinating DBMS Central, coordinating DBMS

   

  Easy to manage, difficult to enforce Easy to manage, difficult to enforce

    Heterogeneous Heterogeneous -- Different DBMSs at different H t H t Diff Different DBMSs at different Diff t DBMS t DBMS t diff t diff t t nodes nodes

   

  Systems – Systems S t S t – With full or partial DBMS functionality With f ll With f ll With full or partial DBMS functionality ti l DBMS f ti l DBMS f ti ti lit lit

   

  Gateways Gateways -- Simple paths are created to other Simple paths are created to other databases without the benefits of one logical databases without the benefits of one logical databases without the benefits of one logical databases without the benefits of one logical database database

   

  Difficult to manage, preferred by independent Difficult to manage, preferred by independent organizations organizations

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Distributed Database Options (cont.) Distributed Database Options (cont.) p ( ) p ( )

 

  • Supports some or all functionality of Supports some or all functionality of one logical database one logical database

Systems Systems

   

  Full DBMS Functionality Full DBMS Functionality -- All distributed DB functions All distributed DB functions

   

  Partial Partial--Multi database Multi database -- Some distributed DB functions Some distributed DB functions

    Federated Federated -- Supports local databases for unique data requests Supports local databases for unique data requests  

  Loose I ntegration Loose I ntegration -- Local dbs have their own schemas Local dbs have their own schemas  

Tight I ntegration Tight I ntegration -- Local dbs use common schema Local dbs use common schema

 

Tight I ntegration Tight I ntegration -- Local dbs use common schema Local dbs use common schema

 

  Unfederated Unfederated -- Requires all access to go through a central, Requires all access to go through a central, coordinating module coordinating module Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Homogeneous, Non Homogeneous, Non Homogeneous Non-- Homogeneous Non

Autonomous Database Autonomous Database

 

  Data is distributed across all the nodes Data is distributed across all the nodes  

  Same DBMS at each node Same DBMS at each node  

  All data is managed by the distributed All data is managed by the distributed All data is managed by the distributed All data is managed by the distributed DBMS (no exclusively local data) DBMS (no exclusively local data)  

  

All access is through one, global schema All access is through one, global schema

   

  

The global schema is the The global schema is the The global schema is the The global schema is the of all the of all the of all the of all the

union union union union local schema local schema

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Figure 13-2: Homogeneous Database Identical DBMSs

  Typical Heterogeneous Typical Heterogeneous Typical Heterogeneous Typical Heterogeneous Environment Environment  

  Data distributed across all the nodes Data distributed across all the nodes  

  Different DBMSs may be used at each Different DBMSs may be used at each node node node node  

  

Local access is done using the local DBMS Local access is done using the local DBMS

and schema and schema d d h h  

  Remote access is done using the global Remote access is done using the global Remote access is done using the global Remote access is done using the global schema schema Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Figure 13-3: Typical Heterogeneous Environment Non-identical DBMSs

  

Major Objectives Major Objectives Major Objectives Major Objectives

 

  Location Transparency Location Transparency  

  User does not have to know the location of the User does not have to know the location of the data data

   

  Data requests automatically forwarded to Data requests automatically forwarded to appropriate sites appropriate sites

    Local Autonomy Local Autonomy

   

  Local site can operate with its database when Local site can operate with its database when network connections fail network connections fail

   

  Each site controls its own data, security, logging, Each site controls its own data, security, logging, recovery recovery

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Significant Trade Significant Trade--Offs Offs g g  

Synchronous Synchronous

  Some data inconsistency is tolerated Some data inconsistency is tolerated y y

  NOTE: all this assumes replicated data (to be discussed later)

  faster response time faster response time

   

  Less overhead Less overhead

   

  Lower data integrity Lower data integrity

   

  Data update propagation is delayed Data update propagation is delayed

   

  Distributed Database Distributed Database  

  Distributed Database Distributed Database  

   

  High overhead High overhead   slow response times slow response times g g

   

  Good for data integrity Good for data integrity

   

  Data updates are immediately applied to all copies Data updates are immediately applied to all copies throughout network throughout network oug ou e o oug ou e o

   

  All copies of the same data are always identical All copies of the same data are always identical

   

  All copies of the same data are always identical All copies of the same data are always identical

Asynchronous Asynchronous

  

Advantages of Advantages of

Distributed Database over Distributed Database over

Centralized Databases Centralized Databases Centralized Databases Centralized Databases

    I ncreased reliability/ availability I ncreased reliability/ availability

    Local control over data Local control over data

    Modular growth Modular growth

    Modular growth Modular growth

    Lower communication costs Lower communication costs

    Faster response for certain queries Faster response for certain queries

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Disadvantages of Disadvantages of Disadvantages of Disadvantages of

Distributed Database Distributed Database Compared to Compared to

Centralized Databases Centralized Databases

  S f d l S f d l  

  Software cost and complexity Software cost and complexity  

  Processing overhead Processing overhead  

  Processing overhead Processing overhead  

  Data integrity exposure Data integrity exposure  

  Slower response for certain queries Slower response for certain queries

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Options for Options for Options for Options for

Distributing a Database Distributing a Database g g  

  Data replication Data replication  

  Copies of data distributed to different sites Copies of data distributed to different sites C C i i f d t di t ib t d t f d t di t ib t d t diff diff t it t it

    Horizontal partitioning Horizontal partitioning

   

  Different rows of a table distributed to different sites Different rows of a table distributed to different sites Diff Diff t t f f t bl di t ib t d t t bl di t ib t d t diff diff t it t it

    Vertical partitioning Vertical partitioning

   

  Diff Diff Different columns of a table distributed to different Different columns of a table distributed to different t t l l f f t bl di t ib t d t t bl di t ib t d t diff diff t t sites sites

      Combinations of the above Combinations of the above Combinations of the above Combinations of the above

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Data Replication Data Replication

 

  Advantages: Advantages:  

  Reliability Reliability y y

   

  Fast response Fast response

   

  May avoid complicated distributed transaction May avoid complicated distributed transaction integrity routines (if replicated data is refreshed at integrity routines (if replicated data is refreshed at ( f ( f l l d d d d f f h d h d scheduled intervals) scheduled intervals)

     

  Decouples nodes (transactions proceed even if Decouples nodes (transactions proceed even if Decouples nodes (transactions proceed even if Decouples nodes (transactions proceed even if some nodes are down) some nodes are down)

   

  Reduced network traffic at prime time (if updates Reduced network traffic at prime time (if updates p p ( ( p p can be delayed) can be delayed)

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Data Replication (cont.) Data Replication (cont.) Data Replication (cont ) Data Replication (cont )

 

  Disadvantages: Disadvantages:  

  Additional requirements for storage space Additional requirements for storage space Additional requirements for storage space Additional requirements for storage space  

  

Additional time for update operations Additional time for update operations

 

  Complexity and cost of updating Complexity and cost of updating Complexity and cost of updating Complexity and cost of updating  

  I ntegrity exposure of getting incorrect data I ntegrity exposure of getting incorrect data if replicated data is not updated if if if replicated data is not updated li li t d d t t d d t i i t t d t d d t d simultaneously simultaneously

  

Therefore, better when used for non--volatile Therefore, better when used for non volatile

(read--only) data (read only) data

Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Types of Data Replication Types of Data Replication yp yp p p

    P P Push Replication – – Push Replication h R h R li li ti ti

      updating site sends changes updating site sends changes updating site sends changes updating site sends changes to other sites to other sites

  Pull Replication – Pull Replication   receiving sites control when receiving sites control when update messages will be update messages will be update messages will be update messages will be processed processed

  • –  

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Types of Push Replication Types of Push Replication Types of Push Replication Types of Push Replication

 

  Broadcast update orders without requiring Broadcast update orders without requiring

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Update messages stored in message queue until Update messages stored in message queue until processed by receiving site processed by receiving site

   

  Done through use of triggers Done through use of triggers

   

  Done through use of triggers Done through use of triggers

   

  Broadcast update orders without requiring Broadcast update orders without requiring confirmation confirmation

   

  Near Real Near Real--Time Replication Time Replication --  

  Snapshot Replication Snapshot Replication -- p p p p  

  Dynamic vs. shared update ownership Dynamic vs. shared update ownership

   

  Dynamic vs. shared update ownership Dynamic vs. shared update ownership

   

  Full or differential (incremental) snapshots Full or differential (incremental) snapshots

   

  Master collects updates in log Master collects updates in log Master collects updates in log Master collects updates in log

   

  Changes periodically sent to master site Changes periodically sent to master site

  processed by receiving site processed by receiving site

  

I ssues for Data Replication I ssues for Data Replication

 

  Data timeliness – Data timeliness – high tolerance for out high tolerance for out--of of--date date data may be required data may be required data may be required data may be required  

  DBMS capabilities DBMS capabilities – – if DBMS cannot support if DBMS cannot support multi--node queries, replication may be necessary multi multi node queries replication may be necessary multi node queries, replication may be necessary node queries replication may be necessary  

  Performance implications – Performance implications – refreshing may refreshing may cause performance problems for busy nodes cause performance problems for busy nodes cause performance problems for busy nodes cause performance problems for busy nodes  

  Network heterogeneity – Network heterogeneity – complicates replication complicates replication  

  

N t N t Network communication capabilities – Network communication capabilities k k i i ti ti biliti biliti – complete complete l t l t

refreshes place heavy demand on refreshes place heavy demand on telecommunications telecommunications telecommunications telecommunications

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

H i t l P titi i H i t l P titi i Horizontal Partitioning Horizontal Partitioning

 

  Unions across partitions Unions across partitions   ease of query ease of query

  No data replication No data replication   backup vulnerability backup vulnerability

   

  inconsistent inconsistent d d access speed access speed

   

  Accessing data across partitions Accessing data across partitions

   

    Disadvantages Disadvantages

   

  Different rows of a table at different sites Different rows of a table at different sites  

  Only relevant data is available Only relevant data is available   security security

   

  better performance better performance

   

  Local access optimization Local access optimization

   

  Data stored close to where it is used Data stored close to where it is used   efficiency efficiency

  Advantages Advantages -- g g  

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Vertical Partitioning Vertical Partitioning

 

  

Different columns of a table at different Different columns of a table at different

sites sites    

  Advantages and disadvantages are the Advantages and disadvantages are the Advantages and disadvantages are the Advantages and disadvantages are the same as for horizontal partitioning except same as for horizontal partitioning except that combining data across partitions is that combining data across partitions is that combining data across partitions is that combining data across partitions is more difficult because it requires joins more difficult because it requires joins (instead of unions) (instead of unions)

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Figure 13-6

Distributed processing system for a manufacturing company Distributed processing system for a manufacturing company

Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Five Distributed Database Five Distributed Database Five Distributed Database Five Distributed Database

Organizations Organizations g g

   Centralized database, distributed access Centralized database, distributed access  Replication with periodic snapshot update Replication with periodic snapshot update   Replication with near real Replication with near real time Replication with near real Replication with near real--time time time synchronization of updates synchronization of updates

   Partitioned, one logical database Partitioned, one logical database   Partitioned, independent, nonintegrated Partitioned, independent, nonintegrated Partitioned independent nonintegrated Partitioned independent nonintegrated segments segments

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Factors in Choice of Factors in Choice of Factors in Choice of Factors in Choice of

Distributed Strategy Distributed Strategy gy gy

 

  Funding, autonomy, security Funding, autonomy, security  

  Site data referencing patterns Site data referencing patterns  

  Growth and expansion needs Growth and expansion needs Growth and expansion needs Growth and expansion needs  

  Technological capabilities Technological capabilities  

  

Costs of managing complex technologies Costs of managing complex technologies

 

  Need for reliable service Need for reliable service Need for reliable service Need for reliable service

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Table 13-1: Distributed Design Strategies Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Distributed DBMS Distributed DBMS   requires requires

Distributed database Distributed database distributed DBMS distributed DBMS

    Functions of a distributed DBMS: Functions of a distributed DBMS:

   

  Locate data with a Locate data with a distributed data dictionary distributed data dictionary

   

  Determine location from which to retrieve data and Determine location from which to retrieve data and process query components process query components

   

  DBMS translation between nodes with different local DBMS translation between nodes with different local DBMSs (using DBMSs (using ))

  middleware middleware  

  Data consistency (via Data consistency (via multiphase commit protocols multiphase commit protocols ))

   

  Global primary key control Global primary key control

   

  Scalability Scalability

   

  Security, concurrency, query optimization, failure recovery Security, concurrency, query optimization, failure recovery

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Figure 13-10: Distributed DBMS architecture Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Local Transaction Steps Local Transaction Steps

1.

  2. Distributed DBMS checks distributed Distributed DBMS checks distributed data repository for location of data. data repository for location of data. data repository for location of data data repository for location of data Finds that it is Finds that it is local local

  3.

  3 3.

  3 Distributed DBMS sends request to local Distributed DBMS sends request to local Distributed DBMS sends request to local Distributed DBMS sends request to local

  4. Local DBMS processes request Local DBMS processes request l l S S 5.

  5. Local DBMS sends results to application Local DBMS sends results to application pp pp

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

Figure 13-10: Distributed DBMS Architecture (cont.) (showing local transaction steps)

  2

  1

  3

  5

  4 Local transaction – all data stored locally Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Global Transaction Steps Global Transaction Steps

1.

  Local DBMS at emote site sends es lts to dist ib ted Local DBMS at emote site sends es lts to dist ib ted 6.

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  8. Distributed DBMS at originating site sends results to Distributed DBMS at originating site sends results to

  originating site originating site 8.

  7. Remote distributed DBMS sends results back to Remote distributed DBMS sends results back to

  7 Remote distributed DBMS sends results back to Remote distributed DBMS sends results back to 7.

  7

  DBMS at remote site DBMS at remote site

  6. Local DBMS at remote site sends results to distributed Local DBMS at remote site sends results to distributed

  5. Local DBMS at remote site processes request Local DBMS at remote site processes request

  1. Application makes request to distributed DBMS Application makes request to distributed DBMS

  its local DBMS if necessary, and sends request to local its local DBMS if necessary, and sends request to local DBMS DBMS DBMS DBMS 5.

  4. Distributed DBMS at remote site translates request for Distributed DBMS at remote site translates request for

  3. Distributed DBMS routes request to remote site Distributed DBMS routes request to remote site 4.

  3. Distributed DBMS routes request to remote site Distributed DBMS routes request to remote site 3.

  location of data. Finds that it is location of data. Finds that it is remote remote 3.

  2. Distributed DBMS checks distributed data repository for Distributed DBMS checks distributed data repository for

  2 Distributed DBMS checks distributed data repository for Distributed DBMS checks distributed data repository for 2.

  2

  application application

Figure 13-10: Distributed DBMS architecture (cont.) (showing global transaction steps)

  2

  3

  1

  6

  3

  

7

  4

  6

  

7

  8

  5 Global transaction – some data is at remote site(s) Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall Distributed DBMS Distributed DBMS Transparency Objectives Transparency Objectives Location T anspa enc Location T anspa enc

    Location Transparency Location Transparency

    User/ application does not need to know where data resides User/ application does not need to know where data resides

  R li ti T R li ti T  

  Replication Transparency Replication Transparency  

  User/ application does not need to know about duplication User/ application does not need to know about duplication F il T F il T

    Failure Transparency Failure Transparency

    Either all or none of the actions of a transaction are Either all or none of the actions of a transaction are committed committed committed committed

    Each site has a transaction manager Each site has a transaction manager

    Logs transactions and before and after images Logs transactions and before and after images

    Logs transactions and before and after images Logs transactions and before and after images

   

Concurrency control scheme to ensure data integrity Concurrency control scheme to ensure data integrity

    Requires special Requires special commit protocol commit protocol

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  Two--Phase Commit Two Phase Commit Two Two Phase Commit Phase Commit  

Prepare Phase Prepare Phase Prepare Phase Prepare Phase

    Coordinator receives a commit request Coordinator receives a commit request

    Coordinator instructs all resource managers to Coordinator instructs all resource managers to get ready to “go either way” on the get ready to “go either way” on the t transaction. Each resource manager writes all transaction. Each resource manager writes all t ti ti E E h h it it ll ll

updates from that transaction to its own updates from that transaction to its own

physical log physical log physical log physical log

    Coordinator receives replies from all resource Coordinator receives replies from all resource managers. I f all are ok, it writes commit to managers. I f all are ok, it writes commit to managers I f all are ok it writes commit to managers I f all are ok it writes commit to its own log; if not then it writes rollback to its its own log; if not then it writes rollback to its log log log log

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Two--Phase Commit (cont.) Two Phase Commit (cont.)

 

Commit Phase Commit Phase

   

  Coordinator then informs each resource manager of Coordinator then informs each resource manager of its decision and broadcasts a message to either its decision and broadcasts a message to either commit or rollback (abort). I f the message is commit, commit or rollback (abort). I f the message is commit, commit or rollback (abort) commit or rollback (abort) I f the message is commit I f the message is commit then each resource manager transfers the update then each resource manager transfers the update from its log to its database from its log to its database from its log to its database from its log to its database

   

  A failure during the commit phase puts a transaction A failure during the commit phase puts a transaction “in limbo.” This has to be tested for and handled with “in limbo.” This has to be tested for and handled with timeouts or polling timeouts or polling

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Concurrency Control Concurrency Control

Concurrency Transparency Concurrency Transparency

    Design goal for distributed database Design goal for distributed database

    Timestamping Timestamping

    Timestamping Timestamping

    Concurrency control mechanism Concurrency control mechanism

    Alternative to locks in distributed databases Alternative to locks in distributed databases

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Query Optimization Query Optimization

 

  I n a query involving a multi I n a query involving a multi--site join and, possibly, a site join and, possibly, a distributed database with replicated files the distributed distributed database with replicated files the distributed distributed database with replicated files, the distributed distributed database with replicated files, the distributed DBMS must decide where to access the data and how to DBMS must decide where to access the data and how to proceed with the join. Three step process: proceed with the join. Three step process:

  1

  1 Query decomposition Query decomposition -- rewritten and simplified rewritten and simplified

  2

  2 Data localization Data localization -- query fragmented so that query fragmented so that

  fragments reference data at only one site fragments reference data at only one site fragments reference data at only one site fragments reference data at only one site

  3

  3 Global optimization Global optimization --  

  Order in which to execute query fragments Order in which to execute query fragments  

  Order in which to execute query fragments Order in which to execute query fragments  

  Data movement between sites Data movement between sites  

  Where parts of the query will be executed Where parts of the query will be executed

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Evolution of Distributed DBMS Evolution of Distributed DBMS

 

“Unit of Work” -- All of a transaction’s steps. “Unit of Work” All of a transaction’s steps.

 

  Remote Unit of Work Remote Unit of Work    

  SQL statements originated at one location can be SQL statements originated at one location can be SQL statements originated at one location can be SQL statements originated at one location can be

executed as a single unit of work on a single executed as a single unit of work on a single

remote DBMS remote DBMS remote DBMS remote DBMS

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall

  

Evolution of Distributed DBMS Evolution of Distributed DBMS Evolution of Distributed DBMS Evolution of Distributed DBMS

(cont.) (cont.)

 

  Distributed Unit of Work Distributed Unit of Work    

  Different statements in a unit of work may refer to Different statements in a unit of work may refer to Different statements in a unit of work may refer to Different statements in a unit of work may refer to different remote sites different remote sites

   

  All databases in a single SQL statement must be All databases in a single SQL statement must be at a single site at a single site ll

    Distributed Request Distributed Request

   

  A single SQL statement may refer to tables in A single SQL statement may refer to tables in more than one remote site more than one remote site

     

  May not support replication transparency or failure May not support replication transparency or failure May not support replication transparency or failure May not support replication transparency or failure transparency transparency

  Chapter 13 © 2005 by Prentice Hall © 2005 by Prentice Hall