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A federated database system is a type of meta-database management system (DBMS) which transparently integrates multiple autonomous database systems into a single federated database. Meta (from Greek: μετά = "after" "beyond" "with" "adjacent" is a prefix used in English in order to indicate a concept A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models The constituent databases are interconnected via a computer network, and may be geographically decentralized. A Computer Database is a structured collection of records or data that is stored in a computer system A computer network is a group of interconnected Computers. Networks may be classified according to a wide variety of characteristics Since the constituent database systems remain autonomous, a federated database system is a contrastable alternative to the (sometimes daunting) task of merging together several disparate databases. A federated database (or virtual database) is the fully-integrated, logical composite of all constituent databases in a federated database system. A Computer Database is a structured collection of records or data that is stored in a computer system

McLeod and Heimbigner[1] were one of the first papers to define a Federated Database Architecture define the architecture and interconnect databases that minimize central authority yet supports partial sharing and coordination among database systems

Through data abstraction, federated database systems can provide a uniform front-end user interface, enabling users and clients to store and retrieve data in multiple noncontiguous databases with a single query--even if the constituent databases are heterogeneous. In Computer science, abstraction is a mechanism and practice to reduce and factor out details so that one can focus on a few concepts at a time Front-end and back-end are generalized terms that refer to the initial and the end stages of a process The user interface (or Human Computer Interface) is the aggregate of means by which people&mdash the users '&mdash interact with the System Users in a Computing context refers to one who uses a computer system A client is an application or system that accesses a remote service on another Computer system, known as a server, by way of a Network. Debt AIDS Trade in Africa (or DATA) is a Multinational non-government organization founded in January 2002 in London by U2 's A Computer Database is a structured collection of records or data that is stored in a computer system Heterogeneous is an adjective used to describe an object or system consisting of multiple items having a large number of structural variations To this end, a federated database system must be able to decompose the query into subqueries for submission to the relevant constituent DBMS's, after which the system must composite the result sets of the subqueries. A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models An SQL result set is a set of rows from a Database, as well as meta-information about the query such as the column names and the types and sizes of each column Because various database management systems employ different query languages, federated database systems can apply wrappers to the subqueries to translate them into the appropriate query languages. Query languages are Computer languages used to make queries into Databases and Information systems Broadly query languages can be classified Query languages are Computer languages used to make queries into Databases and Information systems Broadly query languages can be classified

Among other surveys [2] defines Federated Databases as a collection of cooperating component systems which are autonomous and are possibly heterogenous. A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with The three important components of an FDBS as pointed out in [2] is autonomy, heterogeneity and distribution. A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with Another dimension which has also been considered is the Networking Environment Computer Network, e. A computer network is a group of interconnected Computers. Networks may be classified according to a wide variety of characteristics g many DBSs over a LAN or many DBSs over a WAN update related functions of participating DBSs (e. Wide Area Network ( WAN) is a Computer network that covers a broad area (i g no updates, nonatomic transitions,Atomic updates).

Contents

FDBS Architecture

A DBMS can be classified as either centralized or distributed. A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models A centralized system manages a single database while distributed manages multiple databases. A component DBS in a DBMS may be centralized or distributed. A Computer Database is a structured collection of records or data that is stored in a computer system A multiple DBS (MDBS) can be classified into two types depending on the autonomy of the component DBS as federated and non federated. A nonfederated database system is an integration of component DBMS that are not autonomous. A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models A federated database system consists of component DBS that are autonomous yet participate in a federation to allow partial and controlled sharing of their data. A Computer Database is a structured collection of records or data that is stored in a computer system [2]

Federated architectures differ based on levels of integration with the component database systems and the extent of services offered by the federation. A FDBS can be categorized as loosely or tightly coupled systems.

Multiple DBS of which FDBS are a specific type can be characterized along three dimensions: Distribution, Heterogeneity and Autonomy. Another characterization could be based on the dimension of networking For e. g single databases or multiple databases in a LAN or WAN. Wide Area Network ( WAN) is a Computer network that covers a broad area (i

Distribution

Distribution of data in an FDBS is due to the existence of a multiple DBS before an FDBS is built. Data can be distributed among multiple DB which could be stored in a single computer or multiple computers. These computers could be geographically located in different places but interconnected by a network. The benefits of data distribution help in increased availability and reliability as well as improved access times.

Heterogeneity

Heterogeneities in databases arise due to several factors. A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with Some of them occur due to differences in structures, semantics of data, the constraints supported or query language. Differences in structure occur when two data models provide different primitives such as object oriented (OO) models that support specialization and inheritance and relational models that do not. A data model is an Abstract model that describes how data is represented and accessed Object-Oriented Modeling, or OOM is a modeling paradigm mainly used in Computer programming. The relational model for Database management is a Database model based on first-order predicate logic, first formulated and proposed in 1969 by Edgar Differences due to constrains occur when two models support two different constrains. For example the set type in CODASYL schema may be partially modelled as a referential integrity constraint in a relationship schema. CODASYL (often spelt Codasyl) is an Acronym for "Conference on Data Systems Languages" CODASYL supports insertion and retention that are not captured by referential integrity alone. CODASYL (often spelt Codasyl) is an Acronym for "Conference on Data Systems Languages" The query language supported by a DBMSs can also contribute to heterogeneity between other component DBMSs. A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with A database management system ( DBMS) is Computer software designed for the purpose of managing Databases DBMSes may use any of a variety of Data models For example differences in query languages with same data models or different versions of query languages could contribute heterogeneity. A data model is an Abstract model that describes how data is represented and accessed A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with

Semantic heterogeneities arise when there is a disagreement about meaning, interpretation or intended use of data. Debt AIDS Trade in Africa (or DATA) is a Multinational non-government organization founded in January 2002 in London by U2 's At the schema and data level, some of the possible classification of Heterogeneities that occur are

In creating a federated schema, one has to resolve such heterogeneities before integrating the component DB schemas.

Schema matching, schema mapping

Dealing with incompatible data types or query syntax is not the only obstacle to a concrete implementation of an FDBS. In systems that are not planned top-down, a generic problem lies in matching semantically equivalent, but differently named parts from different schemas (=data models) (tables, attributes). In computer Metadata, semantic equivalence is a declaration that two Data elements from different vocabularies contain data that has similar meaning A Logical Schema is a Data model of a specific problem domain expressed in terms of a particular data management technology A pairwise mapping between n attributes would result in n (n-1) \over 2 mapping rules (given equivalence mappings) - a number that quickly gets too large for practical purposes. A common way out is to provide a global schema that comprises the relevant parts of all member schemas and provide mappings in the form of database views. In Database theory, a view is a stored query accessible as a virtual table composed of the result set of a query. Two principal solutions can be realized, depending on the direction of the mapping:

  1. Global as View (GaV): the global schema is defined in terms of the underlying schemas
  2. Local as View (LaV): the local schemas are defined in terms of the global schema

Both are explained in more detail in the article Data integration. Data integration is the process of combining Data residing at different sources and providing the user with a unified view of these data. Alternate approaches to the schema matching problem and a classification of the same are explained in more detail in the article Schema Matching

Autonomy

Fundamental to the difference between an MDBS and an FDBS is the concept of autonomy. The terms schema matching and mapping are often used interchangeably It is important to understand the aspects of autonomy for component databases and how they can be addressed when a component DBS participates in an FDBS. There are four kinds of autonomies addressed

Heterogeneities in an FDBS is prmarily due to design autonomy. A Heterogeneous Database System is an automated (or semi-automated system for the integration of heterogeneous disparate Database management systems to present a user with

The ANSI/X3/SPARC Study Group outlined a three level data description architecture, the components of which are the conceptual schema, internal schema and external schema of databases. The three level architecture is however inadequate to describing the architectures of an FDBS. It was therefore extended to support the three dimensions of the FDBS namely Distribution, Autonomy and Heterogeneity. The five level schema architecture is explained below.

Concurrency control

The Heterogeneity and Autonomy requirements pose special challenges concerning concurrency control in an FDBS, which is crucial for the correct execution of its concurrent transactions (see also Global concurrency control). In Computer science, especially in the fields of Computer programming (see also Concurrent programming, Parallel programming) Operating systems A database transaction is a unit of work performed against a Database management system or similar system that is treated in a coherent and reliable way independent of other Global concurrency control typically pertains to the Concurrency control of a system comprising several components each with its own concurrency control Achieving global serializability, the major correctness criterion, under these requirements has been characterized as very difficult and unsolved. In Databases ' and Transaction processing, global serializability is a property of a global schedule of Transactions. [2] Commitment ordering, introduced in 1991, has provided a general solution for this issue (See Global serializability; See Commitment ordering also for the architectural aspects of the solution). In Databases ' and Transaction processing, Commitment ordering (or Commit ordering; CO is a Serializability technique In Databases ' and Transaction processing, global serializability is a property of a global schedule of Transactions. In Databases ' and Transaction processing, Commitment ordering (or Commit ordering; CO is a Serializability technique

Five Level Schema Architecture for FDBSs

The five level schema architecture includes the following:-

External links

See also

Schema Matching Virtual Octopus Database Enterprise Information Integration

References

  1. ^ "McLeod and Heimbigner (1985). The terms schema matching and mapping are often used interchangeably Enterprise Information Integration or EII, is a process of Information integration, using Data abstraction to provide a single interface (known as "A Federated architecture for information management". ACM Transactions on Information Systems Vol 3, Issue 3: 253-278.  
  2. ^ a b c d "Sheth and Larson (1990). "Federated Database Systems for Managing Distributed, Heterogenous, and Autonomous Databases". ACM Computing Surveys Vol 22, No. 3: 183-236.  
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