Architecture - Outline I I ❏ Introduction Background...

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Unformatted text preview: Outline I I ❏ Introduction Background Distributed DBMS Architecture ➠ Datalogical Architecture ➠ Implementation Alternatives ➠ Component Architecture ❏ ❏ ❏ ❏ ❏ Distributed DBMS Architecture Distributed Database Design Semantic Data Control Distributed Query Processing Distributed Transaction Management ❏ ❏ ❏ ❏ Distributed DBMS Parallel Database Systems Distributed Object DBMS Database Interoperability Current Issues © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 1 Architecture I ✝Defines the structure of the system ➠ components identified ➠ functions of each component defined ➠ interrelationships and interactions between components defined Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 2 ANSI/SPARC Architecture Users External Schema External view External view External view Conceptual Schema Conceptual view Internal Schema Internal view Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 3 Standardization Reference Model ➠ A conceptual framework whose purpose is to divide standardization work into manageable pieces and to show at a general level how these pieces are related to one another. Approaches ➠ Component-based Components of the system are defined together with the interrelationships between components. N Good for design and implementation of the system. ➠ Function-based N Classes of users are identified together with the functionality that the system will provide for each class. N The objectives of the system are clearly identified. But how do you achieve these objectives? ➠ Data-based N Identify the different types of describing data and specify the functional units that will realize and/or use data according to these views. N Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 4 Conceptual Schema Definition RELATION EMP [ KEY = {ENO} ATTRIBUTES = { ENO : CHARACTER(9) ENAME : CHARACTER(15) TITLE : CHARACTER(10) } ] RELATION PAY [ KEY = {TITLE} ATTRIBUTES = { TITLE SAL : CHARACTER(10) : NUMERIC(6) } ] Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 5 Conceptual Schema Definition RELATION PROJ [ KEY = {PNO} ATTRIBUTES = { PNO : CHARACTER(7) PNAME : CHARACTER(20) BUDGET : NUMERIC(7) } ] RELATION ASG [ KEY = {ENO,PNO} ATTRIBUTES = { ENO PNO RESP DUR : : : : CHARACTER(9) CHARACTER(7) CHARACTER(10) NUMERIC(3) } ] Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 6 Internal Schema Definition RELATION EMP [ KEY = {ENO} ATTRIBUTES = { ENO ENAME TITLE : CHARACTER(9) : CHARACTER(15) : CHARACTER(10) } ] ========================================= INTERNAL_REL EMPL [ INDEX ON E# CALL EMINX FIELD = { HEADER E# ENAME TIT : BYTE(1) : BYTE(9) : BYTE(15) : BYTE(10) } ] Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 7 External View Definition – Example 1 Create a BUDGET view from the PROJ relation CREATE VIEW BUDGET(PNAME, BUD) AS SELECT PNAME, BUDGET FROM PROJ Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 8 External View Definition – Example 2 Create a Payroll view from relations EMP and TITLE_SALARY CREATE AS VIEW SELECT FROM WHERE PAYROLL (ENO, ENAME, SAL) EMP.ENO,EMP.ENAME,PAY.SAL EMP, PAY EMP.TITLE = PAY.TITLE Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 9 DBMS Implementation Alternatives Distribution Peer-to-peer Distributed DBMS Distributed multi-DBMS Client/server Autonomy Multi-DBMS Federated DBMS Heterogeneity Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 10 Dimensions of the Problem I Distribution ➠ Whether the components of the system are located on the same machine or not I Heterogeneity ➠ Various levels (hardware, communications, operating system) ➠ DBMS important one N data model, query language,transaction management algorithms I Autonomy ➠ Not well understood and most troublesome ➠ Various versions N N N Design autonomy: Ability of a component DBMS to decide on issues related to its own design. Communication autonomy: Ability of a component DBMS to decide whether and how to communicate with other DBMSs. Execution autonomy: Ability of a component DBMS to execute local operations in any manner it wants to. © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 11 Distributed DBMS Datalogical Distributed DBMS Architecture ES1 ES2 ... ESn GCS LCS1 LCS2 ... ... LCSn LIS1 LIS2 LISn Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 12 Datalogical Multi-DBMS Architecture GES1 GES2 ... GESn LES11 … LCS1 LES1n GCS LESn1 … LCSn LESnm LCS2 … … LIS1 LIS2 LISn Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 13 Timesharing Access to a Central Database • No data storage • Host running all software Batch requests Response Network Terminals or PC terminal emulators Communications Application Software DBMS Services Database Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 14 Multiple Clients/Single Server Applications Client Services Communications Applications Client Services Communications Applications Client Services Communications High-level requests Filtered data only Communications DBMS Services LAN Database Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 15 Task Distribution Application QL Interface … Programmatic Interface Communications Manager SQL query result table Query Optimizer Lock Manager Storage Manager Communications Manager Page & Cache Manager Database Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 16 Advantages of Client-Server Architectures I I I I I I More efficient division of labor Horizontal and vertical scaling of resources Better price/performance on client machines Ability to use familiar tools on client machines Client access to remote data (via standards) Full DBMS functionality provided to client workstations Overall better system price/performance I Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 17 Problems With MultipleClient/Single Server I I I Server forms bottleneck Server forms single point of failure Database scaling difficult Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 18 Multiple Clients/Multiple Servers I I I I directory caching query decomposition commit protocols Applications Client Services Communications LAN Communications DBMS Services Communications DBMS Services Database Database Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 19 Server-to-Server I I I SQL interface programmatic interface other application support environments Applications Client Services Communications LAN Communications DBMS Services Communications DBMS Services Database Database Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 20 Peer-to-Peer Component Architecture USER PROCESSOR External Schema User Interface Handler DATA PROCESSOR System Local Conceptual Log Schema Local Recovery Manager Global Conceptual Schema GD/D Local Internal Schema Semantic Data Controller Global Query Optimizer Local Query Processor User requests USER Global Execution Monitor Database Runtime Support Processor System responses Distributed DBMS © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 21 Components of a Multi-DBMS USER Responses GTP GS GUI GRM Global Requests GQP GQO Local Requests Component Interface Processor (CIP) Component Interface Processor Local (CIP) Requests D B M S User Interface Query Processor Query Optimizer Transaction Manager Scheduler Recovery Manager … D B M S Transaction Manager Scheduler Recovery Manager User Interface Query Processor Query Optimizer Runtime Sup. Processor Distributed DBMS Runtime Sup. Processor Page 4. 22 © 1998 M. Tamer Özsu & Patrick Valduriez Directory Issues Type Global & central & non-replicated Local & central & replicated (?) Local & central & non-replicated (?) Local & distributed & non-replicated Global & distributed & non-replicated (?) Location Global & central & replicated (?) Local & distributed & replicated Global & distributed & replicated © 1998 M. Tamer Özsu & Patrick Valduriez Page 4. 23 Replication Distributed DBMS ...
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This note was uploaded on 12/23/2009 for the course DBST 663 taught by Professor Tba during the Spring '09 term at MD University College.

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