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DBMS Fundamentals Dr. E.Grace Mary Kanaga Associate Professor / CSE Karunya University 17-09-2014 Database Management Systems - Placement Training Agenda • • • • • • • Introduction DDL DML DCL TCL ER Design Normalization 17-09-2014 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 17-09-2014 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 17-09-2014 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 firstorder predicate logic. 17-09-2014 Database Management Systems Placement Training Database Management Systems • • • • • MySQL MariaDB PostgreSQL SQLite Microsoft SQL Server • Microsoft Access • Oracle • IBM DB2 17-09-2014 • • • • • • • SAP HANA dBASE, LibreOffice Base FileMaker Pro InterSystems Caché FoxPro Database Management Systems Placement Training Database Objects 17-09-2014 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 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 17-09-2014 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 17-09-2014 Database Management Systems Placement Training The CREATE TABLE Statement • You must have: – CREATE TABLE privilege – A storage area CREATE TABLE [schema.]table (column datatype [DEFAULT expr][, ...]); • You specify: – Table name – Column name, column data type, and column size 17-09-2014 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 17-09-2014 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 Character data up to 4 gigabytes CLOB 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 A 64 base number system representing the unique address of a row in its table. ROWID 17-09-2014 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 – – – – 17-09-2014 INSERT SELECT UPDATE DELETE Database Management Systems Placement Training 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 17-09-2014 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 + 500 where emp_bpay > 5000; 17-09-2014 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; SELECT *|{[DISTINCT] column|expression [alias],...} FROM table [WHERE condition(s)]; A where clause is used to restrict the rows returned. 17-09-2014 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. 17-09-2014 Database Management Systems Placement Training 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 17-09-2014 Database Management Systems Placement Training 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 17-09-2014 Database Management Systems Placement Training 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. 17-09-2014 Database Management Systems Placement Training 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' 17-09-2014 Database Management Systems Placement Training 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 17-09-2014 Database Management Systems Placement Training 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 – – – 17-09-2014 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 17-09-2014 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) 17-09-2014 Database Management Systems Placement Training DCL • Grant • Revoke 17-09-2014 Database Management Systems Placement Training TCL • Save Point • Roll Back • Commit 17-09-2014 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 – – – – 17-09-2014 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 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 – – – – – – – Complexity • Levels of normalization based on the amount of redundancy in the database. Various levels of normalization are: Number of Tables • Most databases should be 3NF or BCNF in order to avoid the database anomalies. 17-09-2014 Database Management Systems Placement Training Levels of Normalization 1NF 2NF 3NF 4NF 5NF DKNF Each higher level is a subset of the lower level 17-09-2014 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 0-321-32132-1 Balloon Sleepy, Snoopy, Grumpy 321-321-1111, 232-234-1234, 665-235-6532 Small House 714-000-0000 $34.00 0-55-123456-9 Main Street Jones, Smith 123-333-3333, 654-223-3455 Small House 714-000-0000 $22.95 0-123-45678-0 Ulysses Joyce 666-666-6666 Alpha Press 999-999-9999 $34.00 1-22-233700-0 Visual Basic Roman 444-444-4444 Big House 123-456-7890 $25.00 Author and AuPhone columns are not scalar 17-09-2014 Database Management Systems Placement Training 1NF - Decomposition 1. 2. 3. 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 0-321-32132-1 Sleepy 321-321-1111 ISBN Title PubName PubPhone Price 0-321-32132-1 Snoopy 232-234-1234 0-321-32132-1 Balloon Small House 714-000-0000 $34.00 0-321-32132-1 Grumpy 665-235-6532 0-55-123456-9 Main Street Small House 714-000-0000 $22.95 0-55-123456-9 Jones 123-333-3333 0-123-45678-0 Ulysses Alpha Press 999-999-9999 $34.00 0-55-123456-9 Smith 654-223-3455 1-22-233700-0 Visual Basic Big House 123-456-7890 $25.00 0-123-45678-0 Joyce 666-666-6666 1-22-233700-0 Roman 444-444-4444 17-09-2014 Database Management Systems Placement Training Functional Dependencies 1. 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 ISBN Title Price 0-321-32132-1 Balloon $34.00 0-55-123456-9 Main Street $22.95 0-123-45678-0 Ulysses $34.00 1-22-233700-0 Visual Basic $25.00 17-09-2014 Table Scheme: {ISBN, Title, Price} Functional Dependencies: {ISBN} {Title} {ISBN} {Price} Database Management Systems Placement Training Functional Dependencies Example 2 PubID PubName PubPhone 1 Big House 999-999-9999 2 Small House 123-456-7890 3 Alpha Press 111-111-1111 Table Scheme: {PubID, PubName, PubPhone} Functional Dependencies: {PubId} {PubPhone} {PubId} {PubName} {PubName, PubPhone} {PubID} Example 3 AuID AuName AuPhone 1 Sleepy 321-321-1111 2 Snoopy 232-234-1234 3 Grumpy 665-235-6532 4 Jones 123-333-3333 5 Smith 654-223-3455 6 Joyce 666-666-6666 7 Roman 444-444-4444 17-09-2014 Table Scheme: {AuID, AuName, AuPhone} Functional Dependencies: {AuId} {AuPhone} {AuId} {AuName} {AuName, AuPhone} {AuID} 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) email 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) email 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) 17-09-2014 Database Management Systems Placement Training FD – Example Functional Dependencies – – – – – – 17-09-2014 AuthNo AuthName, AuthEmail, AuthAddress AuthEmail AuthNo PaperNo Primary-AuthNo, Title, Abstract, Status RevNo RevName, RevEmail, RevAddress RevEmail 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} 1. 2. 3. 4. 5. 17-09-2014 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} 1. 2. 3. 4. 5. 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} 1. 2. 3. 4. 5. 17-09-2014 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 Database Management Systems Placement Training 2NF - Decomposition 1. 2. 3. 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} 17-09-2014 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} 17-09-2014 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 } 1. 2. 3. 4. 5. 17-09-2014 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 Database Management Systems Placement Training Third Normal Form (3NF) Example 2 (Not in 3NF) Scheme {Studio, StudioCity, CityTemp} 1. 2. 3. 4. 5. 6. 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) BuildingID Scheme {BuildingID, Contractor, Fee} 1. 2. 3. 4. 5. 6. 17-09-2014 100 Primary Key {BuildingID} 150 {BuildingID} {Contractor} 200 {Contractor} {Fee} 250 {BuildingID} {Fee} 300 Fee transitively depends on the BuildingID Both Contractor and Fee depend on the entire key hence 2NF Database Management Systems Placement Training Contractor Fee Randolph 1200 Ingersoll 1100 Randolph 1200 Pitkin 1100 Randolph 1200 3NF - Decomposition 1. 2. 3. 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} 17-09-2014 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} 17-09-2014 BuildingID Fee Contractor Contractor 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 nonkey 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 } 1. Key1 {City, Street } 2. Key2 {ZipCode, Street} 3. No non-key attribute hence 3NF 4. {City, Street} {ZipCode} 5. {ZipCode} {City} 6. Dependency between attributes belonging to a key 17-09-2014 Database Management Systems Placement Training Boyce Codd Normal Form (BCNF) Example 2 - Movie (Not in BCNF) Scheme {MovieTitle, MovieID, PersonName, Role, Payment } 1. 2. 3. 4. 5. 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} 1. 2. 3. 4. 5. 6. 17-09-2014 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 Database Management Systems Placement Training BCNF - Decomposition 1. 2. 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} 17-09-2014 Database Management Systems Placement Training Decomposition – Loss of Information 1. 2. 3. 4. 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 17-09-2014 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, PersonName, Role, Payment} 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} 17-09-2014 Database Management Systems Placement Training Fourth Normal Form (4NF) • Fourth normal form eliminates relationships between columns. • To be in Fourth Normal Form, – – independent many-to-one 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) 1. All columns are a part of the only candidate key, hence BCNF 2. Many Movies can have the same Genre 3. Many Cities can have the same movie Movie ScreeningCity Hard Code Los Angles 4. Violates 4NF 17-09-2014 Genre Comedy Hard Code New York Comedy Bill Durham Santa Cruz Drama Bill Durham Durham Drama New York Horror Database Management Systems The Code Warrier Placement Training Fourth Normal Form (4NF) Example 2 (Not in 4NF) Scheme {Manager, Child, Employee} 1. 2. 3. 4. Primary Key {Manager, Child, Employee} Each manager can have more than one child Each manager can supervise more than one employee 4NF Violated Manager Child Employee Jim Beth Alice Mary Bob Jane Mary NULL Adam Example 3 (Not in 4NF) Scheme {Employee, Skill, ForeignLanguage} 1. 2. 3. 4. 17-09-2014 Primary Key {Employee, Skill, Language } Each employee can speak multiple languages Each employee can have multiple skills Thus violates 4NF Database Management Systems Placement Training Employee Skill Language 1234 Cooking French 1234 Cooking German 1453 Carpentry Spanish 1453 Cooking Spanish 2345 Cooking Spanish 4NF - Decomposition 1. 2. 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 17-09-2014 Database Management Systems Placement Training 4NF - Decomposition Example 2 (Convert to 4NF) Manager Child Manager Employee Old Scheme {Manager, Child, Employee} Jim Beth Jim Alice New Scheme {Manager, Child} Mary Bob Mary Jane Mary Adam New Scheme {Manager, Employee} Example 3 (Convert to 4NF) Old Scheme {Employee, Skill, ForeignLanguage} New Scheme {Employee, Skill} New Scheme {Employee, ForeignLanguage} 17-09-2014 Employee Skill Employee Language 1234 Cooking 1234 French 1453 Carpentry 1234 German 1453 Cooking 1453 Spanish 2345 Cooking 2345 Spanish 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. 17-09-2014 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. 17-09-2014 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 17-09-2014 Transaction - Example E.g. transaction to transfer ₹ 50 from account A to account B: Ti: 1. 2. 3. 4. 5. 6. read(A) A := A – 50 write(A) read(B) B := B + 50 write(B) Granularity of data - a field, a record , or a whole disk block (Concepts are independent of granularity) 17-09-2014 Database Management Systems Placement Training Two Basic Operations of Transaction Processing •Read (X) Read •Write (X) Write 17-09-2014 Database Management Systems Placement Training Properties of transaction 17-09-2014 A •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. 17-09-2014 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 17-09-2014 Database Management Systems Placement Training Transaction States 17-09-2014 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. 17-09-2014 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 17-09-2014 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 17-09-2014 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 : 17-09-2014 Database Management Systems Placement Training Schedule 2 A serial schedule where T2 is followed by T1 17-09-2014 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. 17-09-2014 Database Management Systems Placement Training Schedule 4 The following concurrent schedule does not preserve the value of (A + B ). 17-09-2014 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. 17-09-2014 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. 2. li = read(Q), lj = write(Q). They conflict. 3. li = write(Q), lj = read(Q). They conflict 4. 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 Database Management Systems 17-09-2014 had been interchanged inTraining the schedule. Placement 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 17-09-2014 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. 17-09-2014 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, 1. 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. 2. 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 . 3. 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. 17-09-2014 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 Database Management Systems 17-09-2014 Placement Training serializable has blind writes. 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. 17-09-2014 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. 17-09-2014 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. 17-09-2014 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. 17-09-2014 Database Management Systems Placement Training THANK YOU 17-09-2014 Database Management Systems Placement Training