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Database Administrator: A Person who is responsible for maintening Database and review conntent of Database.Planning, configuration and relating to them other systems for that organization. Data Administrator: The Data Adminitrator is person who is resposible for: 1. Specification of Organization data 2. Acquisition of Data 3. Maintenance of data management software and the design. 4. Validation of files and data 5. Security of files or databases.
Database transaction is a unit of work in database managment system.Database transaction must follow term ACID(Atomocity, Consistency, Isolation, Durability)..Any transaction started then till it complition,that transaction follow ACID,for successful and no error.
ACID means atomicity, consistency, isolation and durability. 1. Atomicity:Each transaction is said to be “atomic".Means if any part of transaction fail then whole transaction failed.In a word say "ALL OR NOTHING".The failure of transaction commanaly depend on Hard disk fail,System crash. 2. Consistency:Consistency means only valid data will be written to the database.If any transaction voilate any consistency rule of database the whole transaction is Rollback, means it starts again from beggining.Each state in transaction must be consistent for database. 3. Isolation: If two transactions occures at a time then both are not impact to each other,seperate complition of each transaction. The isolation property does not ensure which transaction will execute first, merely that they will not interfere with each other.If second transaction depend on frist then it will done, and data update after complition of traction. Durability:Ensures that any transaction committed to the database will not be lost. Durability is ensured through the use of database backups and transaction logs that facilitate the restoration of committed transactions in spite of any subsequent software or hardware failures.
If two transaction occure same time. The system ensure a control,due to that one transaction do not adversely affect the other. This is called concurrency control. 1. Pessimistic concurrency control: System locks prevents users from modifying data in a way that affects other users. After a user performs an action that causes a lock to be applied, other users cannot perform actions that would conflict with the lock until the owner releases it. 2. Optimistic concurrency control: This is called optimistic because it is mainly used in environments where there is low contention for data, and where the cost of occasionally rolling back a transaction outweighs the costs of locking data when read.
Any database system perform many trasaction,a trasaction run and it uses other utility of system.Another transaction needed this utility, then it goes to waiting state. This problem occure among many trasaction is called Deadlock.
Rollback: Undoing the changes made by a transaction in terms: 1. Before transaction commits. 2. To cancel any changes to a database during current transaction. 3. Transaction not be consistent. RollForward: Re-doing the changes made by a transaction in terms 1. After it commits 2. To overwrite the changed value again to ensure consistency.
Database is an important constituent for collection and storage of data.Data provided information after processing on them.To managing record and importent data Databases server used.
Object oriented databases are used to store: 1. Much more complex data. 2. Designed to store information related to multimedia. 3. Engineering databases. 4. Spatial Databases. 5. Databases even stored data about software’s repositories. This type database was adopted in late ninety`s and new features were added.
XML databases came into existence in 2000. This database lets you organize data irrespective of whether it is organized or not.This data can exported and serialized into the desired format. Two major classes of XML database exist: 1. XML-enabled 2. Native XML
The word hierarchi means tree form relationship,like a tree with branches.Means Relationship formed like tree structure in a database called hierarchical model.With this database you form relationship among many tables with certain concept.It has a downward link to describe the nesting and they are arranged in a particular order down the same level of the list.
This model provides greater flexibility and easy access to data.This model provide logical relationship among many parent database.But implimenting this model is more difficult due to time consuming and cost. Its flexible because through link easily accesesing of information.
Relational Database: 1. Data represent in form of coloumn and row, coloumn means attribute and row means touples present instance of data. 2. This Database model came into existence with help of mathematical concepts. 3. Using some other concepts like normalization, touple relational calculus.
1. Data redundancy and consistency:Not easily in File System but in database possible. 2. Difficalty to accessing data:In database easily done. 3. Data isolation:Database provided but in File System not. 4. Data integrity:Database provided but in File System not. 5. Concurrent access is not possible:Database provided but in File System not. 6. Security Problems:Database provided but in File System not.
1. Physical Level:Physical level is the lower level of abstraction.Its define how data is stored in database. 2. Logical Level:The next higher level of abstraction, its describe what data be store and each logical operation done at this level, links and concept apply here. 3. View Level:This is the higher level describe only part of entire database.
Extension: It is the number of tuples(row) present in a table at any instance. This is time dependent. Intension: It is a constant value that gives the: 1. Name 2. Structure of table 3. The constraints laid on it.
Data independence means that, the ability to modify the schema definition in one level should not affect the schema definition in the next higher level. The application is independent of the storage structure and access strategy of data. Two types of Data Independence are: 1. Logical Data Independence: It is more difficult to achieve. Modification in logical level should affect the view level. 2. Physical Data Independence: Modification in physical level should not affect the logical level.
View is a table that does not really exist in its own right, it derived from one or more underlying base table. In other word view is a virtual table. There is no stored file that direct represents view. Following terms: - Views can represent a subset of the data contained in a table. - View perform alogical operations. - View can join multiple table in a single vertual table. - Importent feature is, to hide complexity of data. Now disscuss how view relate data independence, restructuring of base tables is not reflected in views. Thus the view can insulate users from the effects of restructuring and growth in the database. Hence accounts for logical data independence.
E-R model stands for Entity-Relationship model. This data model is based on real world that consists of basic objects called entities and of relationship among these objects. Entity in database, which existence in real world with number of attributes. In a table attribute know as column. Relationship is a logical thing which relates entities. The E-R diagram shows structure of E-R model.
This model is based on collection of objects. An object is instance variables which store value and bodies of code, that codes are called method. These codes have written to operate the objects. Objects that contain same types of values and the same methods are grouped together into classes. In other words classes are a group of object. This model also follows the some concept related to the OOPs
Entity is dependent on another entity called weak entity. An entity set may not have sufficient attributes to form a primary key is a Weak Entity set.
Attribute is a property which describe entity. In Database table it’s known as Column
A relation Schema is made up of the relation and the list of attributes. It is denoted by R(C1, C2, ?, Cn), where R is the relation name and C1…Cn is the number of attribute. A relation is a set of tuples. Let r be the relation which contain attribute list p1,p2..pn. Each touple is a ordered list of values p=(t1,t1…..tn).
Degree of a relation is the number of attribute of its relation schema and Cardinality of a relation is the number of tuples.
A set of definitions specified data base schema is called DDL (Data Definition Language).
This language that enable user to access and manipulate data. Data are organized by appropriate data model. Two types DML: 1. Procedural DML or Low level: DML requires a user to specify what data are needed and how to get those data. 2. Non-Procedural DML or High level: DML requires a user to specify what data are needed without specifying how to get those data.
DML Compiler translates DML statements in a query language or we say into low-level instruction. That instruction is understandable by Query evaluation engine.
Query evaluation engine execute low level instruction generate by DML Compiler
Relational algebra is procedural query language in database. It consists of a set of instructions that operate one or two relations and produce a new relation. These set of instruction is known as Relation Algebra operations
It is a set of rules to manipulate table through constrains. It is an applied predicate calculus specifically tailored for relational databases proposed by E.F. Codd. E.g. of languages based on it are DSL ALPHA, QUEL.
To remove the redundancy of a table as called Normalization. In other words duplicity or repetitions of data never occur in database. Normalization is mainly minimizing redundancy, insertion, deletion and update anomalies. Normalization achieve through functional dependency. Normalization is much type: All categories are in sequential order: 1.1NF 2.2NF 3.3NF 4.BCNF 5.4NF 6.5NF
Functional dependencies (FDs) are used to specify formal measures of the "goodness" of relational designs and used to define normal forms for relations. FDs are constraints that are derived from the meaning and interrelationships of the data attributes. FDs are derived from the real-world constraints on the attributes For example: A set of attributes X functionally determines a set of attributes Y if the value of X determines a unique value for Y X-->Y holds if whenever two tuples have the same value for X, they must have the same value for Y If t1[X] =t2[X], then t1[Y] =t2[Y] in any relation instance r(R) X-->Y in R specifies a constraint on all relation instances r(R)
There is no repetition of values and data in table known as 1NF. In other words the 1NF disallows composite attributes, multivalued attributes, and nested relations, attributes whose values for an individual tuple are non-atomic.
A functional dependency X --> Y is full functional dependency if any attribute A removed from X. It means that the dependency does not hold any more then it is not Fully Functional dependence. Means each attribute is functionally dependent.
A relation schema R is in 2NF when 1.It is in 1NF 2.Every non-prime attribute A in R is fully functionally dependent on primary key.
If there a set of attribute Z that are neither a primary or candidate key and both X à Z and Y à Z holds
A relation schema R is in 3NF 1.It is in 2NF 2.No non-prime attribute A in R is transitively dependent on the primary key. Transitive dependent means if there a set of attribute Z that are neither a primary or candidate key and both X-->Z and Y-->Z holds.
A relation schema R is in BCNF 1.It is in 3NF 2.Additional constraints that for every FD X -> A, X must be a candidate key
A relation schema R is said to be in 4NF 1.It is in BCNF 2.For every Multivalued dependency X --> Y that holds over R, Either X is subset or equal to (or) XY = R. or X is a super key
A relation schema R is said to be in 5 NF
1.It is in 4NF
2.A Relation schema R is said to be 5NF if for every join dependency {R1, R2, ..., Rn} that holds R, one the following is true Ri = R for some i. and The join dependency is implied by the set of FD, over R in which the left side is key of R.
A database key is a attribute utilized to sort and identify data in some manner. There are many keys: 1. Primary keys 2. Foreign Keys 3. Candidate keys 4. Alternate keys 5. Conposite key
The primary key is a attribute of a relational table uniquely identifies the each tuple of a table or each record in the table. It can either be a normal attribute that is guaranteed to be unique. Such as Social Security Number in a table with no more than one record per person. Examples: Imagine we have a employees table that contains a record for each employee at a organization. The employee's unique employee ID number would be a good choice for a primary key in the employees table. The employee's first and last name would not be a good choice, as there is always the chance that more than one employee might have the same name.
These keys are used to create relationships between tables. Natural relationships exist between tables in most database structures. Example:Let’s assume that the Departments table uses the Department Name column as the primary key. To create a relationship between the two tables, we add a new column to the Employees table called Department. We then fill in the name of the department to which each employee belongs. We also inform the database management system that the Department column in the Employees table is a foreign key that references the Departments table. The database will then enforce referential integrity by ensuring that all of the values in the Departments column of the Employees table have corresponding entries in the Departments table.
Any number of attributes that are uniquely identifying a row in a table is “candidate key” for the table. We select one of the candidate key as Primary key. All candidate keys which are not chosen as "primary key" are “Alternate keys”. The key which uniquely identify the rows of the table and which is made up of more than one attribute is called “composite key”. For Example: In a class we have to select Class Representative. So A, B, C and D stand for that post. So A, B, C and D are candidate for Class Representative so these are candidate key. We select B as Class Representative so B is primary key and A, C and D can be Class Representative but not selected as a Class Representative so they are alternative choice. So A, C and D are alternate key. When two students of class work together in a project then they are composite key for the class.