1 Lecture 9: Distributed Databases – Principles and Architectures Advanced Databases CG096 Nick Rossiter

2 Distributed Database (DDB) -- Definition A logically interrelated collection of shared data physically distributed over a computer network. Implies data description at two levels: Global (the view of the whole) Local (where data is actually held)

3 Distributed DBMS DDBMS The software system that permits the management of the distributed database and makes the distribution transparent to users Transparent – users are unaware of the underlying local structure Data requests do not specify distribution sites But they may notice performance differences (e.g. if local data moved to another site with slow line)

4 Characteristics of DDB Collection of logically related shared data Data is split into a number of fragments (horizontal or vertical (select or project)) Fragments may be replicated Fragments/replicas are allocated to sites Fragments are in effect views Replicas are duplicates – only acceptable if redundancy is controlled

5 Why distribute? Natural match of data with location Can have each division, department or office hold its own data with some degree of autonomy Autonomy – to have control (self-determination, self-rule) Users can decide policies locally (devolved) Still need global DBA to ensure entire system works

6 Why distribute? (continued) More flexible operation Improved availability One node failure does not bring the whole system down Improved reliability Replication ensures that copies of data are still available if a node fails Improved performance Accessing most data locally reduces network overheads Readily handle expansion Can add new nodes with local schema Followed by simple adjustments to global definition

7 Problems with distribution Complexity Global and local schema must be integrated Design techniques involve more stages Replications rigorously handled Network made robust Costs Although cheaper to buy power with smaller machines rather than larger ones More people effort in distributed than centralised approach to handle the complexity

8 Problems with distribution (continued) Security Many more potential access points for would be violators Integrity Need to ensure that combination of local and global constraints gives the required effect Experience Fairly immature technology Not yet translated to standards

9 Homogeneous and Heterogeneous DDBMS Homogeneous DDBMS uses the same database product at all sites Heterogeneous DDBMS uses different database products across its sites may arise from corporate mergers

10 Degrees of heterogeneity vary  Same software, different hardware can be handled fairly easily Oracle 9i : Oracle 8i – differences slight Oracle 9i : SQL Server – same underlying relational model, different syntax in places Oracle 9i : Objectivity – object-relational (SQL-1999) to ODMG, different underlying model.

11 Interoperability Ability to work with each other. In loosely coupled environment: full details of each system not needed BUT need to have interfaces for reliably exchanging messages without error or misunderstanding Solutions: standardized specifications mediation Differences in implementation: may still lead to breakdowns in communication

12 Simple Problem in Interoperability Two schemas in SQL-1999 AB author varchar2(50),author_surname varchar2(40), author, initials varchar2(10), title varchar2(300),title varchar2(200), keyword1 varchar2(30),keywd keywordarr; keyword2 varchar2(30); CREATE TYPE keywordarr AS VARRAY(8) OF varchar2(30); Note: homogeneous model -- both SQL but difficulties.

13 Different Standards For example -- Names: Person(surname, first_name,..) or Person(first_name, surname, …) or Person(name, …) First two may easily be made equivalent but convention in third needs to be understood. Note also possibilities of A.N.Other, AN Other, A N Other.

14 Possible Solutions In schema B define function which amalgamates the two parts of author into one value. Will need to look manually at format of author in schema A. If format inconsistent, need some pre-processing. Other inconsistencies require decisions: Fixed two entries for keyword versus array dimension 8. Different name for keyword attribute Different size for title fields (presumably adopt higher). In heterogeneous environment, need also to relate schema constructions. Is class same as table?

15 Simple Problem in Interoperability 2 Homogeneous Models The same information may be held as attribute name, relation name or a value in different databases e.g. fines in library; could be held in a dedicated relation Fine(amount, borrowed_id) or as an attribute Loan(id, isbn, date_out, fine) or as a value Charge(1.25, ‘fine’)

16 Architectures for Interoperability 1 1. Global schema integration Produces single new schema (C) for the different information systems with schemas (A, B). A C B

17 Global Schema Integration Advantages Transparent to end users -- appears as single information system Disadvantages Difficult -- needs human understanding to perform integration Local autonomy lost Static - does not evolve automatically Tightly-coupled

18 Architectures for Interoperability 2 2. Federated Database Systems Less tightly coupled schema (than in 1) Each service through an export schema specifies sharable objects Common data model Internal command language Decentralised control (local autonomy) Five-level architecture for federated system e.g. Objectivity as Federated OODBMS

19 Federated DBMS - five-level Architecture Local CS Local IS DB Global CS Global ES Local ES DB

20 Terminology FDBMS IS is Internal Schema defining layout on disk of a conceptual schema CS is Conceptual Schema defining logical database (e.g. relational -- tables, attributes, domains) ES is External Schema defining views on conceptual schema

21 Federated Databases: Loosely- coupled Created by users. A E, B E are export schema. V is view. A,B are base schema, autonomy retained over that part of schema not exported. A B V AEAE BEBE

22 Federated Databases: Tightly- Coupled Created by administrators Global schema integration on all export schemas More formal than loosely-coupled Much effort to resolve semantic inconsistencies

23 Federated Database Systems - General Advantages Preserves local autonomy Not all data needs to be integrated Provides metadata structures for views (external and export schema, data dictionary)

24 Federated Database Systems - Disadvantages by Approach Tightly-coupled similar to global schema integration 1) complex, difficult to make changes dynamically 2) much effort in resolving semantic inconsistencies Loosely-coupled duplication by different users in building views updating data defined in views can be difficult

25 Multidatabase Language Approach No attempt at schema integration All sites maintain complete autonomy Various schema in services provided can be heterogeneous, inconsistent and duplicate information in different ways. Language (e.g. MSQL) is used to integrate databases at run time. Relational data model used as Common Data Model

26 Multidatabase Language Approach - Diagram A,B are schema MSQL is runtime language A B MSQL

27 Multidatabase Language Approach - Advantages No preparatory work to understand semantics of schema Dynamic -- access latest versions Very skilled users can succeed in reaching their goals Interesting work on multidatabase dependencies

28 Example Multidatabase Language MSQL (Multidatabase SQL) Biased towards relational model Illustrates problems Consider 2 databases Each on publications of a computing society And query: “What is the name, , title for each publication of an author appearing in both of the society’s databases?”

29 MSQL - Schema Schema 1 (for AIIA Database): Contacts (PersonID, Name, , …) Conference (Name, Type, …) Attendees(ID, Conf_ID, Speaker, …) Publ_Papers(P_ID, Title, Author_ID, …) Schema 2 (for IFIP Database): Member_Socs(Soc_Name, …) Conf (Conf_ID, …) Publ_Papers(P_Ref, Title, Conf_Ref, …) Authors(Name, , Paper_ID, …) Underlined attributes are primary key; attributes in italics are foreign key.

30 MSQL for Query USE AIIA, IFIP SELECT Name, , Title FROM Authors, IFIP.Publ_Papers IFIP_Paper, Contacts, AIIA.Publ_papers AIIA_Paper WHERE Authors.Name = Contacts.Name AND Contacts.Person_ID = AIIA_Paper. Author_ID AND Authors.Paper_ID = IFIP_Paper.P_Ref; The USE statement declares the multidatabases which are aliased in the FROM statement to distinguish tables with the same name. Retrieves Name, and Title from both databases.

31 Potential Problems with MSQL Are domains on name comparable? Can use LET command to create equivalencies of names but does not solve domain mismatch. What if one schema not relational? Entity- Relationship model often used as neutral schema for translation and comparison of heterogeneous features

32 Multidatabase Language - Disadvantages in General Distribution is not transparent Users must resolve inconsistencies themselves Common language may restrict scope of heterogeneity (relational bias) Local autonomous system may change schema freely (so that existing queries fail)

33 Comparison of Approaches By coupling: how tightly is the interoperable system connected to its underlying systems By adaptability: the ability for the interoperable system to evolve in line with underlying schema By transparency: the need for the end-user to understand the underlying schema

34 Comparison of Approaches Coupling AdaptabilityTransparency Approach Global Schema TightLowHigh Integration FederatedMediumMediumMedium Data Bases Multidatabase LowHighLow Languages

35 Summary Trend: From Global Schema Integration Federated Database Multidatabase Language of lower coupling, higher adaptability, and lower transparency.

36 Further Reading Management of Heterogeneous and Autonomous Database Systems Elmagarmid, Ahmed Rusinkiewicz, Marek Sheth, Amit Morgan Kaufmann 1999.