Abhishek_DBMS-ch1_Database_management.ppsx
- 1. Chapter 1: Introduction Purpose of Database Systems View of Data Data Models Data Definition Language Data Manipulation Language Transaction Management Storage Management Database Administrator Database Users Overall System Structure abhishek.kumar762@gmail.com
- 2. Database Management System (DBMS) Collection of interrelated data Set of programs to access the data DBMS contains information about a particular enterprise DBMS provides an environment that is both convenient and efficient to use. Database Applications: Banking: all transactions Airlines: reservations, schedules Universities: registration, grades Sales: customers, products, purchases Manufacturing: production, inventory, orders, supply chain Human resources: employee records, salaries, tax deductions Databases touch all aspects of our lives abhishek.kumar762@g mail.com
- 3. Purpose of Database System In the early days, database applications were built on top of file systems Drawbacks of using file systems to store data: Data redundancy and inconsistency Multiple file formats, duplication of information in different files Difficulty in accessing data Need to write a new program to carry out each new task Data isolation — multiple files and formats Integrity problems Integrity constraints (e.g. account balance > 0) become part of program code Hard to add new constraints or change existing ones abhishek.kumar762@g mail.com
- 4. Purpose of Database Systems (Cont.) Drawbacks of using file systems (cont.) Atomicity of updates Failures may leave database in an inconsistent state with partial updates carried out E.g. transfer of funds from one account to another should either complete or not happen at all Concurrent access by multiple users Concurrent accessed needed for performance Uncontrolled concurrent accesses can lead to inconsistencies – E.g. two people reading a balance and updating it at the same time Security problems Not provide a systematic way for backup and recovery of data and files. Database systems offer solutions to all the above problems abhishek.kumar762@g mail.com
- 5. Advantages of DBMS Preventing Data Redundancy In the database approach of storing data, the information such as employee name or date of joining is stored at a single place in a database. Therefore storing data in a database prevents data redundancy and saves storage space. Restricting Unauthorized Access In the database approach of storing data, multiple users can access data stored in a database. However some user are authorized to modify the database. Persistent Storage Database provides persistent storage for data structures such as class definitions in C++ and program variables used in programming languages. Data Structures can be stored permanently in the DBMS. Such data stored in the DBMS is called persistent data because data can be called by another program even after the program, in which it was being used, is terminated. abhishek.kumar762@g mail.com
- 6. Advantages of DBMS (Cont.) Multiple User Interface DBMS provides multiple user interfaces for users with varying levels of technical knowledge. Ex : Programming language interface for application programmers. Integrity Constraints DBMS allows us to define and implement the constraints. When we store data in a database, we can specify integrity constraints that hold for the data. Ex: Employee_Id must have a Unique value Backup and Recovery The backup and recovery subsystem of the DBMS allows recovering of data when hardware or software failure occurs. Data independence Application programs should be as independent as possible from details of data representation and storage. The DBMS can provide an abstract view of the data to insulate application code from such details. abhishek.kumar762@g mail.com
- 7. Disadvantages of DBMS Danger of a Overkill: For small and simple applications for single users a database system is often not advisable. Complexity: A database system creates additional complexity and requirements. The supply and operation of a database management system with several users and databases is quite costly and demanding. Qualified Personnel: The professional operation of a database system requires appropriately trained staff. Without a qualified database administrator nothing will work for long. Costs: Through the use of a database system new costs are generated for the system itselfs but also for additional hardware and the more complex handling of the system. Enterprise vulnerability: The centralisation of all the enterprise information in the database makes the database an indispensable resource for the organization. The security of central database becomes a cumbersome task for the organization, as the survival of the organization may depend on the security of the database. abhishek.kumar762@g mail.com
- 8. ACID Properties in DBMS Atomicity It ensures that when an update occurs in a database, either all or none of the update is made available to other users except the user who is performing the update. Consistency It ensures that any change to a value of an instance is consistent with the change to other values in the same instance. Isolation It is used when concurrent transactions occur. Durability It ensures that the updates of committed transactions are maintained and never get lost. abhishek.kumar762@g mail.com
- 9. Levels of Abstraction Physical level describes how a record (e.g., customer) is stored. Logical level: describes data stored in database, and the relationships among the data. type customer = record name : string; street : string; city : integer; end; View level: application programs hide details of data types. Views can also hide information (e.g., salary) for security purposes. abhishek.kumar762@g mail.com
- 10. View of Data An architecture for a database system abhishek.kumar762@g mail.com
- 11. Database Schemes and Database Instances Independent from the database model it is important to differentiate between the description of the database and the database itself. The description of the database is called database scheme or also metadata. The database scheme is defined during the database design process and changes very rarely afterwards. The actual content of the database, the data, changes often over the years. A database state at a specific time defined through the currently existing content and relationship and their attributes is called a database instance. The following illustration shows that a database scheme could be looked at like a template or building plan for one or several database instances. abhishek.kumar762@g mail.com
- 12. Data Models A collection of tools for describing data data relationships data semantics data constraints Entity-Relationship model Relational model Other models: object-oriented model semi-structured data models Network model and hierarchical model abhishek.kumar762@g mail.com
- 13. Data Models (Cont.) A collection of concepts that can be used to describe the structure of a database (data types, relationships, and constraints) basic operations (retrieval and updates) specify the dynamic aspect or behavior of a database application( user-defined operations ) example: COMPUTE_GPA, which can be applied to a STUDENT object abhishek.kumar762@g mail.com
- 14. Categories of Data Models High-level or , representational (common users) In between conceptual data models (or implementation) data models can serve both categories above low-level or physical data models (describe the details of how data is stored ) abhishek.kumar762@g mail.com
- 15. Conceptual Data Model Use concepts such as Entities: a real-world object or concept (DEPT) (COURSE) Attributes: property of interest that further describes an entity (dept no, name, telephone, etc) Relationships: interaction among the entities (DEPT) provides (COURSE) abhishek.kumar762@g mail.com
- 16. Physical Data Model Describes how data is stored in the computer. It represents info such as record formats record orderings access path: make search more efficient abhishek.kumar762@g mail.com
- 17. Representational Data Model Used in traditional commercial DMBS they include Relational Data model Network model Hierarchical model abhishek.kumar762@g mail.com
- 18. Entity-Relationship Model The entity-relationship (E-R) data model is based on a perception of a real world that consists of a collection of basic objects, called entities, and of relationships among these objects. An entity is a “thing” or “object” in the real world that is distinguishable from other objects. For example, each person is an entity, and bank accounts can be considered as entities. Entities are described in a database by a set of attributes. For example, the attributes account-number and balance may describe one particular account in a bank, and they form attributes of the account entity set. Similarly, attributes customer-name, customer-street address and customer-city may describe a customer entity. An extra attribute customer-id is used to uniquely identify customers (since it may be possible to have two customers with the same name, street address, and city). A relationship is an association among several entities. For example, a depositor relationship associates a customer with each account that she has. The set of all entities of the same type and the set of all relationships of the same type are termed an entity set and relationship set, respectively. The overall logical structure (schema) of a database can be expressed graphically by an E-R diagram. abhishek.kumar762@g mail.com
- 19. Entity-Relationship Model (Cont.) Example of schema in the entity-relationship model abhishek.kumar762@g mail.com
- 20. Relational Model Relational database is made up of two-dimensional table, which is used to represent data in the form of rows and columns. The two-dimensional table in relational database is known as relation and represents a real world object, which it represents. Entity : An entity is a real world object such as person, place etc about which information is stored inside relations or tables. Each entity has a name associated with it, which is used to identify the entity. An entity is represented by a table in relational model. Ex: employee, student etc are entities. Entity instance refers to a particular occurrence of an entity in a table. Ex : a particular employee in an organization represents as instance of the employee entity. An entity can be classified as strong entity or a weak entity. A strong entity is an entity, which can be uniquely identified by an attribute known as key. A weak entity is an entity, which do not have any key i.e, it cannot be uniquely identified with the help of some of its attribute. Attribute : An attribute of an entity defines the properties of that entity. It is used to describe the specific entity. Ex: An employee entity is characterized by employee_name, cities etc, which are its attribute. abhishek.kumar762@g mail.com
- 21. Relational Model (Cont.) Attributes can be classified into three categories : Composite Vs simple attribute : Composite attributes are the attributes, which can be subdivided into smaller attributes. Ex : the name of an employee can divided into first name, middle name and last name. Simple attributes are the attributes, which cannot be further subdivided into smaller attributes. Single valued Vs multivalued attributes : Single valued attributes are the attribute, which have a single value for a particular entity. Ex : Employee name. Multivalued attributes are the attributes, which can have more than 1 value for a particular entity. Ex : Contact Number. Derived Vs Stored attributes : Derived attributes are the attributes whose values can be derived from the value of some other attributes. Ex : working years of an employee can be derived from the date of joining of the employee and present date. The attribute date of joining is said to be the stored attribute from which we derive the value of some other attribute. abhishek.kumar762@g mail.com
- 22. Relational Model (Cont.) In Relational Model Concepts There are certain terms that are used in context of relational model. These are: Domain : It is a set of atomic values. The values that cannot be divided into subcomponents are called atomic values. Generally, we specify a domain as a data type from which the values forming the domain are taken. Ex : the employee name attribute has domain from a to z, i.e, it can accept values between a to z only. Tuple: In relational data model, a row of a table is termed as a tuple that gives complete information of an enitity. Ex: the row with employee_name Rahul in the Employee relation is a tuple. Relationship : It shows the association between two or more relations i.e how entities are related to one other. Ex : An employee belongs to one department and here, Belongs_To is the relationship. Degree : Degree of relationship is the number of relations participating in that relationship. Ex: the degree of Belongs_To relationship is two is known as binary relationship. abhishek.kumar762@g mail.com
- 23. Relational Model Example of tabular data in the relational model customer- name Customer-id customer- street customer- city account- number Johnson Smith Johnson Jones Smith 192-83-7465 019-28-3746 192-83-7465 321-12-3123 019-28-3746 Alma North Alma Main North Palo Alto Rye Palo Alto Harrison Rye A-101 A-215 A-201 A-217 A-201 Attributes abhishek.kumar762@g mail.com
- 24. A Sample Relational Database abhishek.kumar762@g mail.com
- 26. Database Languages A database system provides a data definition language to specify the database schema and a data manipulation language to express database queries and updates. In practice, the data definition and data manipulation languages are not two separate languages; instead they simply form parts of a single database language, such as the widely used SQL language. abhishek.kumar762@g mail.com
- 27. Data Definition Language (DDL) Specification notation for defining the database schema E.g. create table account ( account-number char(10), balance integer) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata (i.e., data about data) database schema Data storage and definition language language in which the storage structure and access methods used by the database system are specified Usually an extension of the data definition language abhishek.kumar762@g mail.com
- 28. Data Manipulation Language (DML) Language for accessing and manipulating the data organized by the appropriate data model DML also known as query language Two classes of languages Procedural – user specifies what data is required and how to get those data Nonprocedural – user specifies what data is required without specifying how to get those data SQL is the most widely used query language abhishek.kumar762@g mail.com
- 29. SQL SQL: widely used non-procedural language E.g. find the name of the customer with customer-id 192-83-7465 select customer.customer-name from customer where customer.customer-id = ‘192-83-7465’ E.g. find the balances of all accounts held by the customer with customer-id 192-83-7465 select account.balance from depositor, account where depositor.customer-id = ‘192-83-7465’ and depositor.account-number = account.account-number Application programs generally access databases through one of Language extensions to allow embedded SQL Application program interface (e.g. ODBC/JDBC) which allow SQL queries to be sent to a database abhishek.kumar762@gmail.com
- 30. Data Dictionary We can define a data dictionary as a DBMS component that stores the definition of data characteristics and relationships. We can call data dictionary as “data about data” labelled metadata. The DBMS data dictionary provides the DBMS with its self describing characteristic. In effect, the data dictionary resembles and X-ray of the company’s entire data set, and is a crucial element in the data administration function. The two main types of data dictionary exist, integrated and stand alone. An integrated data dictionary is included with the DBMS. For example, all relational DBMSs include a built in data dictionary or system catalogue that is frequently accessed and updated by the RDBMS. Other DBMSs especially older types, do not have a built in data dictionary instead the DBA may use third party stand alone data dictionary systems. Data dictionaries can also be classified as active or passive. An active data dictionary is automatically updated by the DBMS with every database access, thereby keeping its access information up-to-date. A passive data dictionary is not updated automatically and usually requires a batch process to be run. Data dictionary access information is normally used by the DBMS for query optimization purpose. The data dictionary’s main function is to store the description of all objects that interact with the database. abhishek.kumar762@g mail.com
- 31. Data Dictionary (Cont.) Although, there is no standard format for the information stored in the data dictionary several features are common. For example, the data dictionary typically stores descriptions of all : Data elements that are define in all tables of all databases. Specifically the data dictionary stores the name, data types, display formats, internal storage formats, and validation rules. The data dictionary tells where an element is used, by whom it is used and so on. Tables define in all databases. For example, the data dictionary is likely to store the name of the table creator, the date of creation access authorizations, the number of columns, and so on. Indexes define for each database tables. For each index the DBMS stores at least the index name the attributes used, the location, specific index characteristics and the creation date. Define databases: who created each database, the date of creation where the database is located, who the DBA is and so on. End users and The Administrators of the data base Programs that access the database including screen formats, report formats application formats, SQL queries and so on. Access authorization for all users of all databases. Relationships among data elements which elements are involved: whether the relationship are mandatory or optional, the connectivity and cardinality and so on. abhishek.kumar762@g mail.com
- 32. Data Independence The three-schema architecture can be used to explain the concept of data independence, which can be defined as the capacity to change the schema at one level of a database system without having to change the schema at the next higher level. We can define two types of data independence: 1. Logical data independence is the capacity to change the conceptual schema without having to change external schemas or application programs. We may change the conceptual schema to expand the database (by adding a record type or data item), or to reduce the database (by removing a record type or data item). In the latter case, external schemas that refer only to the remaining data should not be affected. Only the view definition and the mappings need be changed in a DBMS that supports logical data independence. Application programs that reference the external schema constructs must work as before, after the conceptual schema undergoes a logical reorganization. Changes to constraints can be applied also to the conceptual schema without affecting the external schemas or application programs. 2. Physical data independence is the capacity to change the internal schema without having to change the conceptual (or external) schemas. Changes to the internal schema may be needed because some physical files had to be reorganized— for example, by creating additional access structures—to improve the performance of retrieval or update. If the same data as before remains in the database, we should not have to change the conceptual schema. abhishek.kumar762@g mail.com
- 33. Data Independence (Cont.) Whenever we have a multiple-level DBMS, its catalog must be expanded to include information on how to map requests and data among the various levels. The DBMS uses additional software to accomplish these mappings by referring to the mapping information in the catalog. Data independence is accomplished because, when the schema is changed at some level, the schema at the next higher level remains unchanged; only the mapping between the two levels is changed. Hence, application programs referring to the higher-level schema need not be changed. The three-schema architecture can make it easier to achieve true data independence, both physical and logical. However, the two levels of mappings create an overhead during compilation or execution of a query or program, leading to inefficiencies in the DBMS. Because of this, few DBMSs have implemented the full three-schema architecture. abhishek.kumar762@gmail.com
- 34. Database Users Users are differentiated by the way they expect to interact with the system Application programmers – interact with system through DML calls Sophisticated users – form requests in a database query language Specialized users – write specialized database applications that do not fit into the traditional data processing framework Native users – invoke one of the permanent application programs that have been written previously E.g. people accessing database over the web, bank tellers, clerical staff abhishek.kumar762@g mail.com
- 35. Database Administrator Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs. Database administrator's duties include: Schema definition Storage structure and access method definition Schema and physical organization modification Granting user authority to access the database Specifying integrity constraints Acting as liaison with users Monitoring performance and responding to changes in requirements abhishek.kumar762@g mail.com
- 36. Transaction Management A transaction is a collection of operations that performs a single logical function in a database application Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures. Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. abhishek.kumar762@g mail.com
- 37. Storage Management Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system. The storage manager is responsible to the following tasks: interaction with the file manager efficient storing, retrieving and updating of data abhishek.kumar762@g mail.com
- 39. Application Architectures Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database Three-tier architecture: E.g. web-based applications, and applications built using “middleware” abhishek.kumar762@gmail.com