DBMS Unit 2 PDF

SQL 1. SQL stands for Structured Query Language. 2. It is designed for managing data in a relational database management system (RDBMS). 3. It is pronounced as S-Q-L or sometime See-Qwell. 4. SQL is a database language, it is used for database creation, deletion, fetching rows, a...

SQL 1. SQL stands for Structured Query Language. 2. It is designed for managing data in a relational database management system (RDBMS). 3. It is pronounced as S-Q-L or sometime See-Qwell. 4. SQL is a database language, it is used for database creation, deletion, fetching rows, and modifying rows, etc. 5. SQL is based on relational algebra and tuple relational calculus. SQL is required: 1. To create new databases, tables and views 2. To insert records in a database 3. To update records in a database 4. To delete records from a database 5. To retrieve data from a database Applications of SQL: Allows users to access data in the relational database management systems. Allows users to describe the data. Allows users to define the data in a database and manipulate that data. Allows to embed within other languages using SQL modules, libraries & pre-compilers. Allows users to create and drop databases and tables. Allows users to create view, stored procedure, functions in a database. Allows users to set permissions on tables, procedures and views. SQL Data Types: Data types are used to represent the nature of the data that can be stored in the database table. For example, in a particular column of a table, if we want to store a string type of data then we will have to declare a string data type of this column. Data types mainly classified into three categories for every database. String Data types Numeric Data types  Date and time Data types Relational data model is the primary data model, which is used widely around the world for data storage and processing. This model is simple and it has all the properties and capabilities required to process data with storage efficiency. Concepts: Tables − In relational data model, relations are saved in the format of Tables. This format stores the relation among entities. A table has rows and columns, where rows represents records and columns represent the attributes. Tuple − A single row of a table, which contains a single record for that relation is called a tuple. Relation instance − A finite set of tuples in the relational database system represents relation instance. Relation instances do not have duplicate tuples. Relation schema − A relation schema describes the relation name (table name), attributes, and their names. Relation key − Each row has one or more attributes, known as relation key, which can identify the row in the relation (table) uniquely. Attribute domain − Every attribute has some pre-defined value scope, known as attribute domain. Constraints: Every relation has some conditions that must hold for it to be a valid relation. These conditions are called Relational Integrity Constraints. There are three main integrity constraints − Key constraints Domain constraints Referential integrity constraints Key Constraints: There must be at least one minimal subset of attributes in the relation, which can identify a tuple uniquely. This minimal subset of attributes is called key for that relation. If there are more than one such minimal subsets, these are called candidate keys. Key constraints force that − in a relation with a key attribute, no two tuples can have identical values for key attributes. a key attribute can not have NULL values. Key constraints are also referred to as Entity Constraints. Domain Constraints Attributes have specific values in real-world scenario. For example, age can only be a positive integer. The same constraints have been tried to employ on the attributes of a relation. Every attribute is bound to have a specific range of values. For example, age cannot be less than zero and telephone numbers cannot contain a digit outside 0-9. Referential integrity Constraints Referential integrity constraints work on the concept of Foreign Keys. A foreign key is a key attribute of a relation that can be referred in other relation. Referential integrity constraint states that if a relation refers to a key attribute of a different or same relation, then that key element must exist. Relational database systems are expected to be equipped with a query language that can assist its users to query the database instances. There are two kinds of query languages − relational algebra and relational calculus. Relational Algebra: Relational algebra is a procedural query language, which takes instances of relations as input and yields instances of relations as output. It uses operators to perform queries. An operator can be either unary or binary. They accept relations as their input and yield relations as their output. Relational algebra is performed recursively on a relation and intermediate results are also considered relations. The fundamental operations of relational algebra are as follows − Select Project Union Set different Cartesian product Rename We will discuss all these operations in the following sections. Select Operation (σ) It selects tuples that satisfy the given predicate from a relation. Notation − σp(r) Where σ stands for selection predicate and r stands for relation. p is prepositional logic formula which may use connectors like and, or, and not. These terms may use relational operators like − =, ≠, ≥, < , >, ≤. For example − σsubject = "database"(Books) Output − Selects tuples from books where subject is 'database'. σsubject = "database" and price = "450"(Books) Output − Selects tuples from books where subject is 'database' and 'price' is 450. σsubject = "database" and price = "450" or year > "2010"(Books) Output − Selects tuples from books where subject is 'database' and 'price' is 450 or those books published after 2010. Project Operation (∏) It projects column(s) that satisfy a given predicate. Notation − ∏A1, A2, An (r) Where A1, A2 , An are attribute names of relation r. Duplicate rows are automatically eliminated, as relation is a set. For example − ∏subject, author (Books) Selects and projects columns named as subject and author from the relation Books. Union Operation (∪) It performs binary union between two given relations and is defined as − r ∪ s = { t | t ∈ r or t ∈ s} Notation − r U s Where r and s are either database relations or relation result set (temporary relation). For a union operation to be valid, the following conditions must hold − r, and s must have the same number of attributes. Attribute domains must be compatible. Duplicate tuples are automatically eliminated. ∏ author (Books) ∪ ∏ author (Articles) Output − Projects the names of the authors who have either written a book or an article or both. Set Difference (−) The result of set difference operation is tuples, which are present in one relation but are not in the second relation. Notation − r − s Finds all the tuples that are present in r but not in s. ∏ author (Books) − ∏ author (Articles) Output − Provides the name of authors who have written books but not articles. Cartesian Product (Χ) Combines information of two different relations into one. Notation − r Χ s Where r and s are relations and their output will be defined as − r Χ s = { q t | q ∈ r and t ∈ s} σauthor = 'tutorialspoint'(Books Χ Articles) Output − Yields a relation, which shows all the books and articles written by tutorialspoint. Rename Operation (ρ) The results of relational algebra are also relations but without any name. The rename operation allows us to rename the output relation. 'rename' operation is denoted with small Greek letter rho ρ. Notation − ρ x (E) Where the result of expression E is saved with name of x. Additional operations are − Set intersection Assignment Natural join Relational Calculus In contrast to Relational Algebra, Relational Calculus is a non-procedural query language, that is, it tells what to do but never explains how to do it. Relational calculus exists in two forms − Tuple Relational Calculus (TRC) Filtering variable ranges over tuples Notation − {T | Condition} Returns all tuples T that satisfies a condition. For example − { T.name | Author(T) AND T.article = 'database' } Output − Returns tuples with 'name' from Author who has written article on 'database'. TRC can be quantified. We can use Existential (∃) and Universal Quantifiers (∀). For example − { R| ∃T ∈ Authors(T.article='database' AND R.name=T.name)} Output − The above query will yield the same result as the previous one. Domain Relational Calculus (DRC) In DRC, the filtering variable uses the domain of attributes instead of entire tuple values (as done in TRC, mentioned above). Notation − { a1, a2, a3,..., an | P (a1, a2, a3,... ,an)} Where a1, a2 are attributes and P stands for formulae built by inner attributes. For example − {< article, page, subject > | ∈ TutorialsPoint ∧ subject = 'database'} Output − Yields Article, Page, and Subject from the relation TutorialsPoint, where subject is database. Just like TRC, DRC can also be written using existential and universal quantifiers. DRC also involves relational operators. The expression power of Tuple Relation Calculus and Domain Relation Calculus is equivalent to Relational Algebra. SQL Set Operation: The SQL Set operation is used to combine the two or more SQL SELECT statements. Types of Set Operation 1. Union 2. UnionAll 3. Intersect 4. Minus UNION Operation UNION is used to combine the results of two or more SELECT statements. However it will eliminate duplicate rows from its resultset. In case of union, number of columns and datatype must be same in both the tables, on which UNION operation is being applied. Example of UNION The First table, ID Name 1 abhi 2 adam The Second table, ID Name 2 adam 3 Chester Union SQL query will be, SELECT * FROM First UNION SELECT * FROM Second; The resultset table will look like, ID NAME 1 abhi 2 adam 3 Chester UNION ALL This operation is similar to Union. But it also shows the duplicate rows. Example of Union All The First table, ID NAME 1 abhi 2 adam The Second table, ID NAME 2 adam 3 Chester Union All query will be like, SELECT * FROM First UNION ALL SELECT * FROM Second; The resultset table will look like, ID NAME 1 abhi 2 adam 2 adam 3 Chester INTERSECT Intersect operation is used to combine two SELECT statements, but it only retuns the records which are common from both SELECT statements. In case of Intersect the number of columns and datatype must be same. NOTE: MySQL does not support INTERSECT operator. Example of Intersect The First table, ID NAME 1 abhi 2 adam The Second table, ID NAME 2 adam 3 Chester Intersect query will be, SELECT * FROM First INTERSECT SELECT * FROM Second; The resultset table will look like  ID NAME 2 adam MINUS The Minus operation combines results of two SELECT statements and return only those in the final result, which belongs to the first set of the result. Example of Minus The First table, ID NAME 1 abhi 2 adam The Second table, ID NAME 2 adam 3 Chester Minus query will be, SELECT * FROM First MINUS SELECT * FROM Second; The resultset table will look like, ID NAME 1 abhi