Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University

Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University
DBMS Fundamentals Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University Database Management Systems - Placement Training

Database Management Systems - Placement Training
Agenda Introduction DDL DML DCL TCL ER Design Normalization Database Management Systems - Placement Training

Introduction Data Facts and statistics collected together for reference or analysis Database It is an organized collection of data that is organized so that it can easily be accessed, managed, and updated Database Systems Database system is a system to achieve an organized, store a large number of dynamical associated data, facilitate for multi-user accessing to computer hardware, software and data, that it is a computer system with database technology Database Management Systems - Placement Training

Introduction Database Management Systems They are specially designed software applications that interact with the user, other applications, and the database itself to capture and analyse data. A general-purpose DBMS is a software system designed to allow the definition, creation, querying, update, and administration of databases. Data Model It is a specification describing how a database is structured and used Database Management Systems - Placement Training

Data Model - Types Flat model: This may not strictly qualify as a data model.. Hierarchical model: In this model data is organized into a tree-like structure Network model: This model organizes data using two fundamental constructs, called records and sets. Relational model: is a database model based on first-order predicate logic. Database Management Systems - Placement Training

Database Management Systems
MySQL MariaDB PostgreSQL SQLite Microsoft SQL Server Microsoft Access Oracle IBM DB2 SAP HANA dBASE, LibreOffice Base FileMaker Pro InterSystems Caché FoxPro Database Management Systems - Placement Training

Database Objects Object Description Table Basic unit of storage; composed of rows and columns View Logically represents subsets of data from one or more tables Sequence Numeric value generator Index Improves the performance of some queries Synonym Gives alternative names to objects Database Objects An Oracle database can contain multiple data structures. Each structure should be outlined in the database design so that it can be created during the build stage of database development. Table: Stores data View: Subset of data from one or more tables Sequence: Numeric value generator Index: Improves the performance of some queries Synonym: Gives alternative names to objects Oracle9i Table Structures Tables can be created at any time, even while users are using the database. You do not need to specify the size of any table. The size is ultimately defined by the amount of space allocated to the database as a whole. It is important, however, to estimate how much space a table will use over time. Table structure can be modified online. Note: More database objects are available but are not covered in this course. Instructor Note Tables can have up to 1,000 columns and must conform to standard database object-naming conventions. Column definitions can be omitted when using the AS subquery clause. Tables are created without data unless a query is specified. Rows are usually added by using INSERT statements. Database Management Systems - Placement Training

DDL- Data Definition Language
Statement Description CREATE TABLE Creates a table ALTER TABLE Modifies table structures DROP TABLE Removes the rows and table structure RENAME Changes the name of a table, view, sequence, or synonym TRUNCATE Removes all rows from a table and releases the storage space COMMENT Adds comments to a table or view Summary In this lesson, you should have learned how to use DDL commands to create, alter, drop, and rename tables. You also learned how to truncate a table and add comments to a table. CREATE TABLE Create a table. Create a table based on another table by using a subquery. ALTER TABLE Modify table structures. Change column widths, change column data types, and add columns. DROP TABLE Remove rows and a table structure. Once executed, this statement cannot be rolled back. RENAME Rename a table, view, sequence, or synonym. TRUNCATE Remove all rows from a table and release the storage space used by the table. The DELETE statement removes only rows. COMMENT Add a comment to a table or a column. Query the data dictionary to view the comment. Database Management Systems - Placement Training

Naming Rules Table names and column names: Must begin with a letter Must be 1–30 characters long Must contain only A–Z, a–z, 0–9, _, $, and # Must not duplicate the name of another object owned by the same user Must not be an Oracle server reserved word Naming Rules Name database tables and columns according to the standard rules for naming any Oracle database object: Table names and column names must begin with a letter and be 1–30 characters long. Names must contain only the characters A–Z, a–z, 0–9, _ (underscore), $, and # (legal characters, but their use is discouraged). Names must not duplicate the name of another object owned by the same Oracle server user. Names must not be an Oracle server reserved word. Naming Guidelines Use descriptive names for tables and other database objects. Note: Names are case insensitive. For example, EMPLOYEES is treated as the same name as eMPloyees or eMpLOYEES. For more information, see Oracle9i SQL Reference,“Object Names and Qualifiers.” Database Management Systems - Placement Training

The CREATE TABLE Statement
You must have: CREATE TABLE privilege A storage area You specify: Table name Column name, column data type, and column size CREATE TABLE [schema.]table (column datatype [DEFAULT expr][, ...]); The CREATE TABLE Statement Create tables to store data by executing the SQL CREATE TABLE statement. This statement is one of the data definition language (DDL) statements, that are covered in subsequent lessons. DDL statements are a subset of SQL statements used to create, modify, or remove Oracle9i database structures. These statements have an immediate effect on the database, and they also record information in the data dictionary. To create a table, a user must have the CREATE TABLE privilege and a storage area in which to create objects. The database administrator uses data control language (DCL) statements, which are covered in a later lesson, to grant privileges to users. In the syntax: schema is the same as the owner’s name table is the name of the table DEFAULT expr specifies a default value if a value is omitted in the INSERT statement column is the name of the column datatype is the column’s data type and length Instructor Note Please read the Instructor note on page 9-37 Database Management Systems - Placement Training

Tables in the Oracle Database
User Tables: Are a collection of tables created and maintained by the user Contain user information Data Dictionary: Is a collection of tables created and maintained by the Oracle Server Contain database information Tables in the Oracle Database User tables are tables created by the user, such as EMPLOYEES. There is another collection of tables and views in the Oracle database known as the data dictionary. This collection is created and maintained by the Oracle server and contains information about the database. All data dictionary tables are owned by the SYS user. The base tables are rarely accessed by the user because the information in them is not easy to understand. Therefore, users typically access data dictionary views because the information is presented in a format that is easier to understand. Information stored in the data dictionary includes names of the Oracle server users, privileges granted to users, database object names, table constraints, and auditing information. There are four categories of data dictionary views; each category has a distinct prefix that reflects its intended use. Database Management Systems - Placement Training

Data Types Data Type Description VARCHAR2(size) Variable-length character data CHAR(size) Fixed-length character data NUMBER(p,s) Variable-length numeric data DATE Date and time values LONG Variable-length character data up to 2 gigabytes CLOB Character data up to 4 gigabytes RAW and LONG RAW Raw binary data BLOB Binary data up to 4 gigabytes BFILE Binary data stored in an external file; up to 4 gigabytes ROWID A 64 base number system representing the unique address of a row in its table. Data Types Database Management Systems - Placement Training

DML COMMANDS The acronym DML represents Data Manipulation Language Data Manipulation Language (DML) statements are used to define the data in the database The Data Manipulation Language (DML) is used to retrieve, insert and modify database information. These commands will be used by all database users during the routine operation of the database INSERT SELECT UPDATE DELETE Database Management Systems - Placement Training 2

DML: Insert The INSERT command in SQL is used to add records to an existing table. Syntax: INSERT INTO table name(field name1 data type, field name2 data type ……. field name n data type); EXAMPLE SQL> insert into stud1(st_name,st_num,st_dob,sub1,sub2,tot) values ('&st_name',&st_num,&st_dob,&sub1,&sub2,&tot); SQL> / Enter value for st_name: charles Enter value for st_num: 1 Enter value for st_dob: '20 may 2000' Enter value for sub1: 90 Enter value for sub2: 80 Enter value for tot: 170 Database Management Systems - Placement Training

Update The UPDATE command can be used to modify information contained within a table, either in bulk or individually. Syntax 1.UPDATE tablename SET fieldname=new value; 2. UPDATE table name SET fieldname=new value where condition; EXAMPLE update emp1 set emp_sal = emp_sal where emp_bpay > 5000; Database Management Systems - Placement Training

DELETE : To delete data from the database. DELETE [FROM] table [WHERE condition]; SELECT: To retrieve the data from the database. SELECT *|{[DISTINCT] column|expression [alias],...} FROM table; FROM table [WHERE condition(s)]; A where clause is used to restrict the rows returned. Database Management Systems - Placement Training

The select Clause The select clause list the attributes desired in the result of a query corresponds to the projection operation of the relational algebra Example: find the names of all branches in the loan relation: select branch_name from loan In the relational algebra, the query would be: branch_name (loan) NOTE: SQL names are case insensitive (i.e., you may use upper- or lower-case letters.) E.g. Branch_Name ≡ BRANCH_NAME ≡ branch_name Some people use upper case wherever we use bold font. Database Management Systems - Placement Training 3

The select Clause (Cont.)
SQL allows duplicates in relations as well as in query results. To force the elimination of duplicates, insert the keyword distinct after select. Find the names of all branches in the loan relations, and remove duplicates select distinct branch_name from loan The keyword all specifies that duplicates not be removed. select all branch_name from loan Database Management Systems - Placement Training 4

The select Clause (Cont.)
An asterisk in the select clause denotes “all attributes” select * from loan The select clause can contain arithmetic expressions involving the operation, +, –, , and /, and operating on constants or attributes of tuples. E.g.: select loan_number, branch_name, from loan Database Management Systems - Placement Training 5

The where Clause The where clause specifies conditions that the result must satisfy Corresponds to the selection predicate of the relational algebra. To find all loan number for loans made at the Perryridge branch with loan amounts greater than $1200. select loan_number from loan where branch_name = 'Perryridge' and amount > 1200 Comparison results can be combined using the logical connectives and, or, and not. Database Management Systems - Placement Training 6

The from Clause The from clause lists the relations involved in the query Corresponds to the Cartesian product operation of the relational algebra. Find the Cartesian product borrower X loan select  from borrower, loan Find the name, loan number and loan amount of all customers having a loan at the Perryridge branch. select customer_name, borrower.loan_number, amount from borrower, loan where borrower.loan_number = loan.loan_number and branch_name = 'Perryridge' Database Management Systems - Placement Training 8

The Rename Operation SQL allows renaming relations and attributes using the as clause: old-name as new-name E.g. Find the name, loan number and loan amount of all customers; rename the column name loan_number as loan_id. select customer_name, borrower.loan_number as loan_id, amount from borrower, loan where borrower.loan_number = loan.loan_number Database Management Systems - Placement Training 9

String Operations SQL includes a string-matching operator for comparisons on character strings. The operator “like” uses patterns that are described using two special characters: percent (%). The % character matches any substring. underscore (_). The _ character matches any character. Find the names of all customers whose street includes the substring “Main”. select customer_name from customer where customer_street like '% Main%' Match the name “Main%” like 'Main\%' escape '\' SQL supports a variety of string operations such as concatenation (using “||”) converting from upper to lower case (and vice versa) finding string length, extracting substrings, etc. Database Management Systems - Placement Training

Ordering the Display of Tuples
List in alphabetic order the names of all customers having a loan in Perryridge branch select distinct customer_name from borrower, loan where borrower loan_number = loan.loan_number and branch_name = 'Perryridge' order by customer_name We may specify desc for descending order or asc for ascending order, for each attribute; ascending order is the default. Example: order by customer_name desc Database Management Systems - Placement Training

Set Operations Find all customers who have a loan, an account, or both: (select customer_name from depositor) union (select customer_name from borrower) Find all customers who have both a loan and an account. (select customer_name from depositor) intersect (select customer_name from borrower) Find all customers who have an account but no loan. (select customer_name from depositor) except (select customer_name from borrower) Database Management Systems - Placement Training

DCL Grant Revoke Database Management Systems - Placement Training

TCL Save Point Roll Back Commit Database Management Systems - Placement Training

Normalization This is the process which allows you to winnow out redundant data within your database. This involves restructuring the tables to successively meeting higher forms of Normalization. A properly normalized database should have the following characteristics Scalar values in each fields Absence of redundancy. Minimal use of null values. Minimal loss of information. Database Management Systems - Placement Training

Levels of Normalization
Levels of normalization based on the amount of redundancy in the database. Various levels of normalization are: First Normal Form (1NF) Second Normal Form (2NF) Third Normal Form (3NF) Boyce-Codd Normal Form (BCNF) Fourth Normal Form (4NF) Fifth Normal Form (5NF) Domain Key Normal Form (DKNF) Redundancy Number of Tables Complexity Most databases should be 3NF or BCNF in order to avoid the database anomalies. Database Management Systems - Placement Training

Levels of Normalization
DKNF 1NF 2NF 3NF 4NF 5NF Each higher level is a subset of the lower level Database Management Systems - Placement Training

First Normal Form (1NF) A table is considered to be in 1NF if all the fields contain only scalar values (as opposed to list of values). Example (Not 1NF) ISBN Title AuName AuPhone PubName PubPhone Price Balloon Sleepy, Snoopy, Grumpy , , Small House $34.00 Main Street Jones, Smith , Small House $22.95 Having scalar values also means that all instances of a record type must contain the same number of fields. A table not in first normal form is called un normalized Ulysses Joyce Alpha Press $34.00 Visual Basic Roman Big House $25.00 Author and AuPhone columns are not scalar Database Management Systems - Placement Training

1NF - Decomposition Place all items that appear in the repeating group in a new table Designate a primary key for each new table produced. Duplicate in the new table the primary key of the table from which the repeating group was extracted or vice versa. Example (1NF) ISBN AuName AuPhone Sleepy ISBN 1. The designated key will be the primary key of the original table concatenated with one or more data items from the new table. For the first table the primary key is ISBN For the second table the primary key is ISBN + Author Name Title PubName PubPhone Price Snoopy Balloon Small House $34.00 Grumpy Main Street Small House $22.95 Jones Ulysses Alpha Press $34.00 Smith Visual Basic Big House $25.00 Joyce Roman Database Management Systems - Placement Training

Functional Dependencies
If one set of attributes in a table determines another set of attributes in the table, then the second set of attributes is said to be functionally dependent on the first set of attributes. Example 1 Table Scheme: {ISBN, Title, Price} Functional Dependencies: {ISBN}  {Title} {ISBN}  {Price} ISBN Title Price Balloon $34.00 Notes to Instructor: Need more rigor in the functional dependencies. With a few examples. May be create a class assignment for functional dependencies. Main Street $22.95 Ulysses $34.00 Visual Basic $25.00 Database Management Systems - Placement Training

Functional Dependencies
Example 2 Table Scheme: {PubID, PubName, PubPhone} Functional Dependencies: {PubId}  {PubPhone} {PubId}  {PubName} {PubName, PubPhone}  {PubID} PubID PubName PubPhone 1 Big House 2 Small House 3 Alpha Press Example 3 AuID AuName AuPhone Table Scheme: {AuID, AuName, AuPhone} Functional Dependencies: {AuId}  {AuPhone} {AuId}  {AuName} {AuName, AuPhone}  {AuID} 1 Sleepy 2 Snoopy 3 Grumpy 4 Jones 5 Smith 6 Joyce 7 Roman Database Management Systems - Placement Training

FD – Example Database to track reviews of papers submitted to an academic conference. Prospective authors submit papers for review and possible acceptance in the published conference proceedings. Details of the entities Author information includes a unique author number, a name, a mailing address, and a unique (optional) address. Paper information includes the primary author, the paper number, the title, the abstract, and review status (pending, accepted,rejected) Reviewer information includes the reviewer number, the name, the mailing address, and a unique (optional) address A completed review includes the reviewer number, the date, the paper number, comments to the authors, comments to the program chairperson, and ratings (overall, originality, correctness, style, clarity) Database Management Systems - Placement Training

FD – Example Functional Dependencies AuthNo  AuthName, Auth , AuthAddress Auth  AuthNo PaperNo  Primary-AuthNo, Title, Abstract, Status RevNo  RevName, Rev , RevAddress Rev  RevNo RevNo, PaperNo  AuthComm, Prog-Comm, Date, Rating1, Rating2, Rating3, Rating4, Rating5 Database Management Systems - Placement Training

Second Normal Form (2NF)
For a table to be in 2NF, there are two requirements The database is in first normal form All nonkey attributes in the table must be functionally dependent on the entire primary key Note: Remember that we are dealing with non-key attributes Example 1 (Not 2NF) Scheme  {Title, PubId, AuId, Price, AuAddress} Key  {Title, PubId, AuId} {Title, PubId, AuID}  {Price} {AuID}  {AuAddress} AuAddress does not belong to a key AuAddress functionally depends on AuId which is a subset of a key Database Management Systems - Placement Training

Second Normal Form (2NF)
Example 2 (Not 2NF) Scheme  {City, Street, HouseNumber, HouseColor, CityPopulation} key  {City, Street, HouseNumber} {City, Street, HouseNumber}  {HouseColor} {City}  {CityPopulation} CityPopulation does not belong to any key. CityPopulation is functionally dependent on the City which is a proper subset of the key Example 3 (Not 2NF) Scheme  {studio, movie, budget, studio_city} Key  {studio, movie} {studio, movie}  {budget} {studio}  {studio_city} studio_city is not a part of a key studio_city functionally depends on studio which is a proper subset of the key Let us consider the problems with the movie studio database: Redundancy – City Population is repeated many times Insertion anomaly – Whenever we add a new record we have to add unnecessary information. We can not add record until we know information about the city population Deletion anomaly – Whenever we delete a record, useful information is deleted. Update anomaly – The City Population needs to be updated in more than one location if it changes. Database Management Systems - Placement Training

2NF - Decomposition If a data item is fully functionally dependent on only a part of the primary key, move that data item and that part of the primary key to a new table. If other data items are functionally dependent on the same part of the key, place them in the new table also Make the partial primary key copied from the original table the primary key for the new table. Place all items that appear in the repeating group in a new table Example 1 (Convert to 2NF) Old Scheme  {Title, PubId, AuId, Price, AuAddress} New Scheme  {Title, PubId, AuId, Price} New Scheme  {AuId, AuAddress} If there is a table with columns A,B,C,D with Primary Key (A,B) & D is dependant on A (alone) then to be 2NF, you should reduce (split) tables as: Table with columns A,D with Primary Key (A) Table with columns A,B,C with Primary Key (A,B) Database Management Systems - Placement Training

2NF - Decomposition Example 2 (Convert to 2NF) Old Scheme  {Studio, Movie, Budget, StudioCity} New Scheme  {Movie, Studio, Budget} New Scheme  {Studio, City} Example 3 (Convert to 2NF) Old Scheme  {City, Street, HouseNumber, HouseColor, CityPopulation} New Scheme  {City, Street, HouseNumber, HouseColor} New Scheme  {City, CityPopulation} Database Management Systems - Placement Training

Third Normal Form (3NF) This form dictates that all non-key attributes of a table must be functionally dependent on a candidate key i.e. there can be no interdependencies among non-key attributes. For a table to be in 3NF, there are two requirements The table should be second normal form No attribute is transitively dependent on the primary key Example (Not in 3NF) Scheme  {Title, PubID, PageCount, Price } Key  {Title, PubId} {Title, PubId}  {PageCount} {PageCount}  {Price} Both Price and PageCount depend on a key hence 2NF Transitively {Title, PubID}  {Price} hence not in 3NF In the Book Schema Third Normal Form is violated since a non-key field is dependent on another non-key field and is transitively dependent on the primary key. Database Management Systems - Placement Training

Third Normal Form (3NF) Example 2 (Not in 3NF) Scheme  {Studio, StudioCity, CityTemp} Primary Key  {Studio} {Studio}  {StudioCity} {StudioCity}  {CityTemp} {Studio}  {CityTemp} Both StudioCity and CityTemp depend on the entire key hence 2NF CityTemp transitively depends on Studio hence violates 3NF Example 3 (Not in 3NF) Scheme  {BuildingID, Contractor, Fee} Primary Key  {BuildingID} {BuildingID}  {Contractor} {Contractor}  {Fee} {BuildingID}  {Fee} Fee transitively depends on the BuildingID Both Contractor and Fee depend on the entire key hence 2NF BuildingID Contractor Fee 100 Randolph 1200 150 Ingersoll 1100 Let us consider the problems with the movie studio database: Redundancy – City Population is repeated many times Insertion anomaly – Whenever we add a new record we have to add unnecessary information. We can not add record until we know information about the city population Deletion anomaly – Whenever we delete a record, useful information is deleted. Update anomaly – The City Population needs to be updated in more than one location if it changes. 200 Randolph 1200 250 Pitkin 1100 300 Randolph 1200 Database Management Systems - Placement Training

3NF - Decomposition Move all items involved in transitive dependencies to a new entity. Identify a primary key for the new entity. Place the primary key for the new entity as a foreign key on the original entity. Example 1 (Convert to 3NF) Old Scheme  {Title, PubID, PageCount, Price } New Scheme  {PubID, PageCount, Price} New Scheme  {Title, PubID, PageCount} If there is a table with columns A,B,C with Primary Key (A) and C is dependant on B (B  C) then to be 3NF, the tables become Table with columns B,C with Primary Key (B) Table with fields A,B with Primary Key ( A), and Foreign Key (B) Database Management Systems - Placement Training

3NF - Decomposition Example 2 (Convert to 3NF) Old Scheme  {Studio, StudioCity, CityTemp} New Scheme  {Studio, StudioCity} New Scheme  {StudioCity, CityTemp} Example 3 (Convert to 3NF) Old Scheme  {BuildingID, Contractor, Fee} New Scheme  {BuildingID, Contractor} New Scheme  {Contractor, Fee} BuildingID Contractor Contractor Fee 100 Randolph Randolph 1200 150 Ingersoll Ingersoll 1100 200 Randolph Pitkin 1100 250 Pitkin 300 Randolph Database Management Systems - Placement Training

Boyce-Codd Normal Form (BCNF)
BCNF does not allow dependencies between attributes that belong to candidate keys. BCNF is a refinement of the third normal form in which it drops the restriction of a non-key attribute from the 3rd normal form. Third normal form and BCNF are not same if the following conditions are true: The table has two or more candidate keys At least two of the candidate keys are composed of more than one attribute The keys are not disjoint i.e. The composite candidate keys share some attributes Example 1 - Address (Not in BCNF) Scheme  {City, Street, ZipCode } Key1  {City, Street } Key2  {ZipCode, Street} No non-key attribute hence 3NF {City, Street}  {ZipCode} {ZipCode}  {City} Dependency between attributes belonging to a key The second and third normal forms assume that all attributes not part of the candidate keys depend on the candidate keys but does not deal with dependencies within the keys. BCNF deals with such dependencies. Under third normal form all non-key columns must be functionally dependent on a candidate key. Under BCNF, even columns that are part of a candidate key must be dependent on another candidate key, if they have a dependency at all. For most tables third normal form and BCNF are the same. Third normal form does not cover some specific cases for which BCNF was created. Third normal form and BCNF are not same if the following conditions are true: The table has two or more candidate keys At least two of the candidate keys are composed of more than one attribute The keys are not disjoint i.e. The composite candidate keys share some attributes Database Management Systems - Placement Training

Boyce Codd Normal Form (BCNF)
Example 2 - Movie (Not in BCNF) Scheme  {MovieTitle, MovieID, PersonName, Role, Payment } Key1  {MovieTitle, PersonName} Key2  {MovieID, PersonName} Both role and payment functionally depend on both candidate keys thus 3NF {MovieID}  {MovieTitle} Dependency between MovieID & MovieTitle Violates BCNF Example 3 - Consulting (Not in BCNF) Scheme  {Client, Problem, Consultant} Key1  {Client, Problem} Key2  {Client, Consultant} No non-key attribute hence 3NF {Client, Problem}  {Consultant} {Client, Consultant}  {Problem} Dependency between attributess belonging to keys violates BCNF A management consulting firm has several clients and consultants. A client can have several problems and the same problem can be an issue for several clients. Each consultant specializes in only one problem type (e. g marketing, production) but several consultants could advise on one problem. For each problem, the client is advised by only one consultant. Database Management Systems - Placement Training

BCNF - Decomposition Place the two candidate primary keys in separate entities Place each of the remaining data items in one of the resulting entities according to its dependency on the primary key. Example 1 (Convert to BCNF) Old Scheme  {City, Street, ZipCode } New Scheme1  {ZipCode, Street} New Scheme2  {City, Street} Loss of relation {ZipCode}  {City} Alternate New Scheme1  {ZipCode, Street } Alternate New Scheme2  {ZipCode, City} If there is a table with columns A,B,C with Primary Key (A) and C is dependant on B (B  C) then to be 3NF, the tables become Table with columns B,C with Primary Key (B) Table with fields A,B with Primary Key ( A), and Foreign Key (B) Database Management Systems - Placement Training

Decomposition – Loss of Information
If decomposition does not cause any loss of information it is called a lossless decomposition. If a decomposition does not cause any dependencies to be lost it is called a dependency-preserving decomposition. Any table scheme can be decomposed in a lossless way into a collection of smaller schemas that are in BCNF form. However the dependency preservation is not guaranteed. Any table can be decomposed in a lossless way into 3rd normal form that also preserves the dependencies. 3NF may be better than BCNF in some cases Use your own judgment when decomposing schemas Database Management Systems - Placement Training

BCNF - Decomposition Example 2 (Convert to BCNF) Old Scheme  {MovieTitle, MovieID, PersonName, Role, Payment } New Scheme  {MovieID, PersonName, Role, Payment} New Scheme  {MovieTitle, PersonName} Loss of relation {MovieID}  {MovieTitle} New Scheme  {MovieID, MovieTitle} We got the {MovieID}  {MovieTitle} relationship back Example 3 (Convert to BCNF) Old Scheme  {Client, Problem, Consultant} New Scheme  {Client, Consultant} New Scheme  {Client, Problem} Database Management Systems - Placement Training

Fourth Normal Form (4NF)
Fourth normal form eliminates independent many-to-one relationships between columns. To be in Fourth Normal Form, a relation must first be in Boyce-Codd Normal Form. a given relation may not contain more than one multi-valued attribute. Example (Not in 4NF) Scheme  {MovieName, ScreeningCity, Genre) Primary Key: {MovieName, ScreeningCity, Genre) All columns are a part of the only candidate key, hence BCNF Many Movies can have the same Genre Many Cities can have the same movie Violates 4NF Movie ScreeningCity Genre Hard Code Los Angles Comedy New York Bill Durham Santa Cruz Drama Durham The Code Warrier Horror Database Management Systems - Placement Training

Fourth Normal Form (4NF)
Example 2 (Not in 4NF) Scheme  {Manager, Child, Employee} Primary Key  {Manager, Child, Employee} Each manager can have more than one child Each manager can supervise more than one employee 4NF Violated Example 3 (Not in 4NF) Scheme  {Employee, Skill, ForeignLanguage} Primary Key  {Employee, Skill, Language } Each employee can speak multiple languages Each employee can have multiple skills Thus violates 4NF Manager Child Employee Jim Beth Alice Mary Bob Jane NULL Adam These cause update, addition and deletion anomalies. Insertion anomaly is that entity integrity would be violated if you tried to add a new employee who did not speak a foreign language. Update anomalies would occur if you tried to change Cooking to Chef. Employee Skill Language 1234 Cooking French German 1453 Carpentry Spanish 2345 Database Management Systems - Placement Training

4NF - Decomposition Move the two multi-valued relations to separate tables Identify a primary key for each of the new entity. Example 1 (Convert to 3NF) Old Scheme  {MovieName, ScreeningCity, Genre} New Scheme  {MovieName, ScreeningCity} New Scheme  {MovieName, Genre} Movie Genre Movie ScreeningCity Hard Code Comedy Hard Code Los Angles Bill Durham Drama Hard Code New York The Code Warrier Horror Bill Durham Santa Cruz Bill Durham Durham The Code Warrier New York Database Management Systems - Placement Training

4NF - Decomposition Example 2 (Convert to 4NF) Old Scheme  {Manager, Child, Employee} New Scheme  {Manager, Child} New Scheme  {Manager, Employee} Example 3 (Convert to 4NF) Old Scheme  {Employee, Skill, ForeignLanguage} New Scheme  {Employee, Skill} New Scheme  {Employee, ForeignLanguage} Manager Child Jim Beth Mary Bob Manager Employee Jim Alice Mary Jane Adam Employee Skill 1234 Cooking 1453 Carpentry 2345 Employee Language 1234 French German 1453 Spanish 2345 Database Management Systems - Placement Training

Fifth Normal Form (5NF) Fifth normal form is satisfied when all tables are broken into as many tables as possible in order to avoid redundancy. Once it is in fifth normal form it cannot be broken into smaller relations without changing the facts or the meaning. Database Management Systems - Placement Training

Domain Key Normal Form (DKNF)
The relation is in DKNF when there can be no insertion or deletion anomalies in the database. Database Management Systems - Placement Training

Transaction The term transaction refers to a collection of operations that form a single logical unit of work. Logical unit of database processing that includes one or more access operations (read -retrieval, write - insert or update, delete). Eg., Transfer of money from one account to another is a transaction consisting of two updates, one to each account. Transaction consists of all operations executed between the begin transaction and end transaction. Database Management Systems - Placement Training

Transaction - Example E.g. transaction to transfer ₹ 50 from account A to account B: Ti: 1. read(A) 2. A := A – 50 3. write(A) 4. read(B) 5. B := B + 50 6. write(B) Granularity of data - a field, a record , or a whole disk block (Concepts are independent of granularity) Database Management Systems - Placement Training

Two Basic Operations of Transaction Processing
Read Read (X) Write Write (X) Database Management Systems - Placement Training

Properties of transaction
Atomicity C Consistency I Isolation D Durability Database Management Systems - Placement Training

ACID Properties Atomicity Ensures whether all actions of the transaction are done or incase of failure, partially done transactions will be undone. Consistency Execution of a transaction in isolation preserves the consistency of the database. Database Management Systems - Placement Training

ACID Properties (cont…)
Isolation Isolate the transaction from the effect of other concurrent executing transaction. Durability Once a transaction is successfully executed, its effect must persist in the database Database Management Systems - Placement Training

Transaction States Database Management Systems - Placement Training

Transaction States Active – the initial state; the transaction stays in this state while it is executing Partially committed – after the final statement has been executed. Failed -- after the discovery that normal execution can no longer proceed. Aborted – after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted: restart the transaction can be done only if no internal logical error kill the transaction Committed – after successful completion. Database Management Systems - Placement Training

Concurrent Executions
Multiple transactions are allowed to run concurrently in the system. Advantages are: increased processor and disk utilization, leading to better transaction throughput E.g. one transaction can be using the CPU while another is reading from or writing to the disk reduced average response time for transactions: short transactions need not wait behind long ones. Concurrency control schemes – mechanisms to achieve isolation that is, to control the interaction among the concurrent transactions in order to prevent them from destroying the consistency of the database Database Management Systems - Placement Training

Schedules Schedule – a sequences of instructions that specify the chronological order in which instructions of concurrent transactions are executed When transactions are executing concurrently in an interleaved fashion, the order of execution of operations from the various transactions forms what is known as a transaction schedule (or history). A transaction that successfully completes its execution will have a commit instructions as the last statement A transaction that fails to successfully complete its execution will have an abort instruction as the last statement Database Management Systems - Placement Training

Schedule 1 Let T1 transfer ₹ 50 from A to B, and T2 transfer 10% of the balance from A to B. A serial schedule in which T1 is followed by T2 : Database Management Systems - Placement Training

Schedule 2 A serial schedule where T2 is followed by T1 Database Management Systems - Placement Training

Schedule 3 Let T1 and T2 be the transactions defined previously. The following schedule is not a serial schedule, but it is equivalent to Schedule 1. In Schedules 1, 2 and 3, the sum A + B is preserved. Database Management Systems - Placement Training

Schedule 4 The following concurrent schedule does not preserve the value of (A + B ). Database Management Systems - Placement Training

Serializability Basic Assumption – Each transaction preserves database consistency. Thus serial execution of a set of transactions preserves database consistency. A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule. Different forms of schedule equivalence give rise to the notions of: 1. conflict serializability 2. view serializability Simplified view of transactions We ignore operations other than read and write instructions We assume that transactions may perform arbitrary computations on data in local buffers in between reads and writes. Our simplified schedules consist of only read and write instructions. Database Management Systems - Placement Training

Conflicting Instructions
Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q. 1. li = read(Q), lj = read(Q). li and lj don’t conflict li = read(Q), lj = write(Q). They conflict li = write(Q), lj = read(Q). They conflict li = write(Q), lj = write(Q). They conflict Intuitively, a conflict between li and lj forces a (logical) temporal order between them. If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule. Database Management Systems - Placement Training

Conflict Serializability
If a schedule S can be transformed into a schedule S´ by a series of swaps of non-conflicting instructions, we say that S and S´ are conflict equivalent. We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule Database Management Systems - Placement Training

Conflict Serializability (Cont.)
Schedule 3 can be transformed into Schedule 6, a serial schedule where T2 follows T1, by series of swaps of non-conflicting instructions. Therefore Schedule 3 is conflict serializable. Database Management Systems - Placement Training Schedule 3 Schedule 6

View Serializability Let S and S´ be two schedules with the same set of transactions. S and S´ are view equivalent if the following three conditions are met, for each data item Q, If in schedule S, transaction Ti reads the initial value of Q, then in schedule S’ also transaction Ti must read the initial value of Q. If in schedule S transaction Ti executes read(Q), and that value was produced by transaction Tj (if any), then in schedule S’ also transaction Ti must read the value of Q that was produced by the same write(Q) operation of transaction Tj . The transaction (if any) that performs the final write(Q) operation in schedule S must also perform the final write(Q) operation in schedule S’. As can be seen, view equivalence is also based purely on reads and writes alone. Database Management Systems - Placement Training

View Serializability (Cont.)
A schedule S is view serializable if it is view equivalent to a serial schedule. Every conflict serializable schedule is also view serializable. Below is a schedule which is view-serializable but not conflict serializable. Every view serializable schedule that is not conflict serializable has blind writes. Database Management Systems - Placement Training

Concurrency Control Need for Concurrency Control The Lost Update Problem This occurs when two transactions that access the same database items have their operations interleaved in a way that makes the value of some database item incorrect. The Temporary Update (or Dirty Read) Problem This occurs when one transaction updates a database item and then the transaction fails for some reason The updated item is accessed by another transaction before it is changed back to its original value. Database Management Systems - Placement Training

Concurrency Control The Incorrect Summary Problem If one transaction is calculating an aggregate summary function on a number of records while other transactions are updating some of these records, the aggregate function may calculate some values before they are updated and others after they are updated. Database Management Systems - Placement Training

Concurrency Control A database must provide a mechanism that will ensure that all possible schedules are either conflict or view serializable, and are recoverable and preferably cascadeless A policy in which only one transaction can execute at a time generates serial schedules, but provides a poor degree of concurrency Testing a schedule for serializability after it has executed is a little too late! Goal – to develop concurrency control protocols that will assure serializability. Database Management Systems - Placement Training

Levels of Consistency in SQL
Serializable — default Repeatable read — only committed records to be read, repeated reads of same record must return same value. However, a transaction may not be serializable – it may find some records inserted by a transaction but not find others. Read committed — only committed records can be read, but successive reads of record may return different (but committed) values. Read uncommitted — even uncommitted records may be read. Database Management Systems - Placement Training

Thank you Database Management Systems - Placement Training

Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University

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Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University

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