Computer Science
Database Schemas
Database schemas are the structure or blueprint of a database, defining how data is organized and stored. They include tables, fields, relationships, and constraints. Schemas provide a framework for ensuring data integrity and consistency within a database system.
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9 Key excerpts on "Database Schemas"
eBook - PDF- Jan L. Harrington(Author)
- 2003(Publication Date)
- Morgan Kaufmann(Publisher)
lee Managing Database Structure This Page Intentionally Left Blank L)' Schemas and Tables As a complete data manipulation language, SQL contains state- ments that let you create, modify, and delete structural elements in a database. In this chapter we will begin the discussion of a data- base's structural elements by looking at schemas and the perma- nent base tables that you create within them. This discussion will be concluded in Chapter 10, which covers additional structural ele- ments such as views, temporary tables, and indexes. The actual file structure of a database is implementation dependent, as is the procedure needed to create database files. Therefore, the discussion in this chapter assumes that the necessary database files are already in place. 157 158 SCHEMAS AND TABLES Database Object Hierarchy The objects in a database maintained by SQL-92 are arranged in a hierarchy, diagrammed in Figure 9-1. The smallest units with which a database works~the columns and rows~appear in the center. These in turn are grouped into tables and views. Figure 9-1: The SQL-92 database object hierarchy DATABASEOBJECTHIERARCHY 159 The tables and views that constitute a single logical database are collected into a schema. Multiple schemas are grouped into catalogs, which can then be grouped into clusters. A catalog usually contains information describing all the schemas handled by one DBMS. Cat- alog creation is implementation dependent and therefore not part of the SQL-92 standard. Prior to SQL-92, clusters often represented database files, and the clustering of objects into files was a way to increase database per- formance by placing objects accessed together in the same physical file. The SQL-92 concept of a cluster, however, is a group of catalogs that are accessible using the same connection to a database server. Under SQL-92, none of the groupings of database objects are related to physical storage structures.
eBook - PDF- Graeme Simsion, Graham Witt(Authors)
- 2004(Publication Date)
- Morgan Kaufmann(Publisher)
For exam-ple, the data might be organized so that all the insurance policies belonging to a given customer were stored close together, allowing them all to be retrieved into the computer’s memory in a single operation. An index might be provided to enable rapid location of customers by name. We can think of the physical database design as the inside of a black box, or the engine under the hood. (To pursue the architecture analogy, it represents the foundations, electrical wiring, and hidden plumbing; the owner will want only to know that the house will be sound and that the lights and faucets will work.) The external schemas specify views that enable different users of the data to see it in different ways. As a simple example, some users of policy data might not require details of the commission paid. By providing them with a view that excludes the Commission Rate column, we would not only shield them from unwanted (and perhaps unauthorized) information, but also insulate them from changes that might be made to the format of that data. We can also combine tables in various ways. For example, we could add data from the relevant customer to each row of the Policy table. 7 It is usual to provide one external schema that covers the entire conceptual 18 ■ Chapter 1 What Is Data Modeling? Figure 1.4 Three-schema architecture. External Schema External Schema External Schema Conceptual Schema (User views of data) (Common view of data) Internal Schema (Internal storage of data) 7 The ways in which views can be constructed and the associated constraints (e.g., whether data in a view constructed using particular operators can be updated) are beyond the scope of this book. Some suitable references are suggested at the end of this book under “Further Reading.” schema, and then to provide a number of external schemas that meet spe-cific user requirements.
eBook - PDFSolutions for Networked Databases
How to Move from Heterogeneous Structures to Federated Concepts
- Dimitris N. Chorafas, Heinrich Steinmann(Authors)
- 2014(Publication Date)
- Academic Press(Publisher)
PART II Schemata, Dictionaries, and Protocols This page intentionally left blank CHAPTER 6 Schemata, Metaphors, and Distributed Databases 6.1 Introduction Schema combines in one word view, form, and meaning. Etymologi-cally, it means a diagrammatic representation, a scheme or outline. In logic, schema is a syllogistic figure bringing reflection into the picture and the formation of concept(s). Gottfried Wilhelm Leibnitz (1646-1716) saw in schema monadology; the principle essential in each monad (unit), constituted of its own peculiar characteristics. Immanuel Kant (1724-1804) considered schema a medidating factor, making possible the application of catego-ries of phenomena and their classification. Schematism is a particular form or disposition of something, an exhi-bition or outline in a systematic arrangement. The formation or use of schemata often constitutes a system which in logic forms a character or figure of syllogism. In database-oriented applications, • Schemata are descriptions of data managed by one or more DBMS. • A schema consists of schema objects and their interrelationships. • Typically, every DBMS has its own schema. Schema objects are class definitions or data structure descriptions, e.g., table definitions in a relational model. They can be entity types as well and relationship types in an entity-relationship model. Schemata can be viewed as application-specific components that de-fine database contents and structure. This is vital to database users performing ad hoc operations as well as to application programs. • Schema-to-schema mapping leads to functions that correlate schema objects to objects in another schema. 95 96 6. Schemata, Metaphors, and Distributed Databases • The task of schema translation involves transforming schema X (describing information elements in one data model) into an equivalent schema Y describing the same IE in a different data model.
eBook - PDF- Vanitha, G M.Kalpana(Authors)
- 2020(Publication Date)
- NEW INDIA PUBLISHING AGENCY (NIPA)(Publisher)
a logical schema (data model) describes the semantics, as represented by a particular data manipulation technology. This consists of descriptions of tables and columns. a physical schema (data model) describes the physical means by which data are stored. This is concerned with partitions, CPUs, tablespaces, and the like. Relational Database Model A relational database is a database that conforms to the relational model, and refers to a database’s data and schema. Common usage of the term “Relational database management system” technically refers to the software used to create a relational database, but sometimes mistakenly refers to a relational database. A relational database is a database that conforms to the relational model, and could also be defined as a set of relations or a database built in an RDBMS. A relational database management system (RDBMS) is a system that manages data using the relational model. Frequently, the term “RDBMS” is inaccurately used as a generic label for the relational database concept. Ironically, most RDBMS software packages are not technically considered “relational” because they do not fully conform to the relational model. Table A table is a set of data elements (values) that is organized using a model of horizontal rows and vertical columns. The columns are 133 Database Management System (DBMS) identified by name, and the rows are identified by the values appearing in a particular column subset which has been identified as a candidate key. Table is another term for relations; although there is the difference in that a table is usually a multi-set (bag) of rows whereas a relation is a set and does not allow duplicates. A table has a specified number of columns but can have any number of rows. View A view is a virtual or logical table composed of the result set of a query.
- Adele Kuzmiakova(Author)
- 2023(Publication Date)
- Arcler Press(Publisher)
There has been a physical level beneath the interior level, which can be controlled by the OS under the guidance of the DBMS. Furthermore, at the physical level, the functions of the DBMS and the OS stay not straightforward The Creation and Management of Database Systems 78 and differ from scheme to scheme. Certain DBMSs utilize several of the OS access mechanisms, whilst others utilize only the fundamental ones and develop their file structures. The physical level beneath the DBMS contains information that is only known by the operating system, like how the sequencing has been performed or if the fields of interior records are saved as continuous bytes on the disk (Li & Wang, 2007). 3.2.4. Mappings, Schemas, and Instances The comprehensive detail of a database has been referred to as the database schema. There have been 3 distinct schema kinds in the database, each of which is defined by the degrees of abstraction of the 3-level architecture depicted in Figure 3.1. Various external schemas (also known as subschemas) relate to distinct data views at the higher level (de Brock, 2018). At the conceptual level, there is the conceptual schema, that specifies all items, characteristics, and connections along with integrity limitations. The internal schema is a thorough detail of the interior model, and it contains the detail of contained records, the techniques of depiction, the data fields, as well as the indexes and storage structures that are utilized. This schema exists at the most fundamental level of abstraction. There has been one conceptual schema and one inner schema associated with a particular database (Fischer et al., 2010). The DBMS oversees mapping such 3 kinds of schema together. It should also ensure that the schemas are consistent; in other words, every external schema should be deducible from the conceptual schema, and the conceptual schema should be used to map internal and external schemas.
eBook - ePub- Mark Horninger(Author)
- 2011(Publication Date)
- Syngress(Publisher)
Ask the Author ” form.Q: What is a schema?A: A schema is a container that objects such as tables, stored procedures, and views are placed into. In versions of SQL Server prior to 2005, schemas were the same things as users, and therefore, each time a user was added to a database a new schema was added as well. In SQL Server 2005, schemas and users have been separated.Q: Why is the user-schema separation important from the perspective of security?A: There are several reasons that this is important. First, it gives us an improved ability to group together objects that require similar permissions, creating a security boundary around those objects. It also provides clear separation between the ownership of objects and permission on objects. you have a better ability to implement the principle of least privilege Also, it reduces security holes that arise when administrators need to remove or alter the access level of a user in some way, but cannot do this immediately due to the change the namespace of the objects that user may own, as well as the application code that accesses those objects.Q: Can a schema be owned by more than one entity?A: No, a schema can have only a single owner. However, in previous versions of SQL Server, the schema was the owner of an object. Therefore, it was impossible to separate these two concepts. By definition, the schema was owned by the user that was tied to the schema. The dbo schema must be owned only by dbo. In SQL Server 2005, schemas and users are no longer fused together. A schema is simply a container, and administrators can assign ownership of the container to any principal. Although a schema can still have only one owner, the owner can be a group, and ownership can be changed easily.Q: How do schemas and ownership chains relate to each other?A: Ownership chains have not changed. However, since “schema” is no longer just another word for the owner of an object, an object can be owned by a user, but be contained in a schema belonging to a different user. Taking it a step further, objects can have their owner property set to SCHEMA OWNER
- Mark L. Gillenson, Paulraj Ponniah, Alex Kriegel, Boris M. Trukhnov, Allen G. Taylor, Gavin Powell, Frank Miller(Authors)
- 2012(Publication Date)
- Wiley(Publisher)
Microsoft SQL Server is one of the most full-featured database products on the market. It includes a wide range of features and supports something of an object-relational database model. Different versions, called editions, are available to support a wide range of database needs. A SQL Server database is physically made up of at least two and pos- sibly more files. One required file is the database file and contains the database objects and data. The other is the transaction log that tracks any activity that modifies the database. The data storage model is designed so you can create additional data files as needed and specify the physical file locations. You can then define the file in which a database object is cre- ated. This gives you a way of spreading a database across multiple hard disks. You have control over how the space is used and, by sharing the work between multiple drives, a way of improving database performance and I/O throughput. 44 INTRODUCING DATABASES AND DATABASE MANAGEMENT SYSTEMS The data storage component also relates to the storage of the structure defin- itions in the data dictionary, the database’s metadata. Metadata is a term referring to data about data. It’s the data that describes the database and database objects. The storage format is specific to the database management system software used. Structure definitions specify database and object schemas. In this context, schema refers to the design and structure of database objects. For example, a table’s schema describes, among other items, the columns that make up the table. Speed is of the essence for the storage devices holding the data dictionary. This is especially true because, with many database systems, the data dictionary must be accessed first before the data is accessed. You may also have removable storage media components, such as a tape drive or writeable CD or DVD drive, to support database backups and data archiving.
eBook - PDFOrganizing Information
Principles of Data Base and Retrieval Systems
- Dagobert Soergel(Author)
- 1985(Publication Date)
- Morgan Kaufmann(Publisher)
9 .1 Conceptual schema for the University Data Base. information to be included in the ISAR system and as the basis for retrieving information or entities from the system. Thus, the conceptual schema is at the heart of ISAR system design. Its development must be based on user needs. The conceptual schema defines the intellectual or logical content of the entity store (data base). There are many ways to arrange the physical organization of this content for easy access; these are discussed in Chapter 11, 'Data Structures and Access.' Communication with the store of data is through one or more input for-mats and one or more output formats. 9.1 DESIGNING A CONCEPTUAL SCHEMA The design of a conceptual schema should proceed from an analysis of the needs to be served. This yields a list of entity types to be included in the ISAR system. Some of these entities are of interest in themselves and can occur as 9.1 Designing a Conceptual Schema 139 focal entities in queries; they are main entities (our term). Other entities are of interest only as they relate to main entities. In the University Data Base all entities except Semester, Grade, and Subject are main entities; each of them could be the focus of a query. For each entity type derived from the needs analysis, the designer must define the domain or scope and decide on the en-tity identifiers to be used. The next step is to determine the types of relationships that should be established between entities. Each relationship gives information on both en-tities involved. For example, COF3 < has instructor > B. Simms gives infor-mation about COF3: B. Simms is the instructor. It also gives information about B. Simms; she teaches COF3. Such an item of information about an entity is called a data element.
eBook - PDFData Mining
Technologies, Techniques, Tools, and Trends
- Bhavani Thuraisingham(Author)
- 2014(Publication Date)
- CRC Press(Publisher)
For example, for many applications, a DBMS may have to be extended with a layer to support objects or to process rules or to handle multimedia data types or even to do mining. Such an extensible architecture is illustrated in Figure 2-11 . 7 Note that a B-Tree is a representation scheme used to physically represent the data. However, it is at a higher level than the bits and bytes level. For a discussion on physical structures and models, we refer to [DATE90]. Database Systems Technology 31 Figure 2-10. Three-Schema Architecture Figure 2-11. Extensible DBMS 32 Data Mining: Technologies, Techniques, Tools, and Trends 2.4 DATABASE DESIGN Designing a database is a complex process. Much of the work has been on designing relational databases. There are three steps which are illustrated in Figure 2-12 . The first step is to capture the entities of the application and the relationships between the entities. One could use a model such as the entity-relationship model for this purpose. More recently, object-oriented data models, which are part of object-oriented design and analysis methodologies, are becoming popular to represent the application. The second step is to generate the relations from the representa-tions. For example, from the entity-relationship diagram of Figure 2-3 , one could generate the relations EMP, DEPT, and WORKS. The relation WORKS will capture the relationship between employees and departments. Figure 2-12. Database Design Process The third step is to design good relations. This is the normalization process. Various normal forms have been defined in the literature (see, for example, [MAIE83] and DATE90]). For many applications, rela-tions in third normal form would suffice. With this normal form, redundancies, complex values, and other situations that could cause potential anomalies are eliminated. 2.5 DATABASE ADMINISTRATION A database has a database administrator (DBA). It is the responsi-bility of the DBA to define the various schemas and mappings.
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