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Chapter 1: Introduction Database System Concepts, 6 th Ed. ©Silberschatz, Korth and Sudarshan See Chapter 1: Introduction Database System Concepts, 6 th Ed. ©Silberschatz, Korth and Sudarshan See www. db-book. com for conditions on re-use

Outline n The Need for Databases n Data Models n Relational Databases n Database Outline n The Need for Databases n Data Models n Relational Databases n Database Design n Storage Manager n Query Processing n Transaction Manager Database System Concepts - 6 th Edition 1. 2 ©Silberschatz, Korth and Sudarshan

Database Management System (DBMS) n DBMS contains information about a particular enterprise l Collection Database Management System (DBMS) n DBMS contains information about a particular enterprise l Collection of interrelated data l Set of programs to access the data l An environment that is both convenient and efficient to use n Database Applications: l Banking: transactions l Airlines: reservations, schedules l Universities: registration, grades l Sales: customers, products, purchases l Online retailers: order tracking, customized recommendations l Manufacturing: production, inventory, orders, supply chain l Human resources: employee records, salaries, tax deductions n Databases can be very large. n Databases touch all aspects of our lives Database System Concepts - 6 th Edition 1. 3 ©Silberschatz, Korth and Sudarshan

University Database Example n Application program examples l Add new students, instructors, and courses University Database Example n Application program examples l Add new students, instructors, and courses l Register students for courses, and generate class rosters l Assign grades to students, compute grade point averages (GPA) and generate transcripts n In the early days, database applications were built directly on top of file systems Database System Concepts - 6 th Edition 1. 4 ©Silberschatz, Korth and Sudarshan

Drawbacks of using file systems to store data n Data redundancy and inconsistency l Drawbacks of using file systems to store data n Data redundancy and inconsistency l Multiple file formats, duplication of information in different files n Difficulty in accessing data l Need to write a new program to carry out each new task n Data isolation l Multiple files and formats n Integrity problems l Integrity constraints (e. g. , account balance > 0) become “buried” in program code rather than being stated explicitly l Hard to add new constraints or change existing ones Database System Concepts - 6 th Edition 1. 5 ©Silberschatz, Korth and Sudarshan

Drawbacks of using file systems to store data (Cont. ) n Atomicity of updates Drawbacks of using file systems to store data (Cont. ) n Atomicity of updates l Failures may leave database in an inconsistent state with partial updates carried out l Example: Transfer of funds from one account to another should either complete or not happen at all n Concurrent access by multiple users l Concurrent access needed for performance l Uncontrolled concurrent accesses can lead to inconsistencies 4 Example: Two people reading a balance (say 100) and updating it by withdrawing money (say 50 each) at the same time n Security problems l Hard to provide user access to some, but not all, data Database systems offer solutions to all the above problems Database System Concepts - 6 th Edition 1. 6 ©Silberschatz, Korth and Sudarshan

Levels of Abstraction n Physical level: describes how a record (e. g. , instructor) Levels of Abstraction n Physical level: describes how a record (e. g. , instructor) is stored. n Logical level: describes data stored in database, and the relationships among the data. type instructor = record ID : string; name : string; dept_name : string; salary : integer; end; n View level: application programs hide details of data types. Views can also hide information (such as an employee’s salary) for security purposes. Database System Concepts - 6 th Edition 1. 7 ©Silberschatz, Korth and Sudarshan

View of Data An architecture for a database system Database System Concepts - 6 View of Data An architecture for a database system Database System Concepts - 6 th Edition 1. 8 ©Silberschatz, Korth and Sudarshan

Instances and Schemas n Similar to types and variables in programming languages n Logical Instances and Schemas n Similar to types and variables in programming languages n Logical Schema – the overall logical structure of the database l Example: The database consists of information about a set of customers and accounts in a bank and the relationship between them 4 Analogous to type information of a variable in a program n Physical schema– the overall physical structure of the database schema n Instance – the actual content of the database at a particular point in time l Analogous to the value of a variable n Physical Data Independence – the ability to modify the physical schema without changing the logical schema l Applications depend on the logical schema l In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others. Database System Concepts - 6 th Edition 1. 9 ©Silberschatz, Korth and Sudarshan

Data Models n A collection of tools for describing Data l Data relationships l Data Models n A collection of tools for describing Data l Data relationships l Data semantics l Data constraints l n Relational model n Entity-Relationship data model (mainly for database design) n Object-based data models (Object-oriented and Object-relational) n Semistructured data model (XML) n Other older models: l l Network model Hierarchical model Database System Concepts - 6 th Edition 1. 10 ©Silberschatz, Korth and Sudarshan

Relational Model n All the data is stored in various tables. n Example of Relational Model n All the data is stored in various tables. n Example of tabular data in the relational model Columns Rows Database System Concepts - 6 th Edition 1. 11 ©Silberschatz, Korth and Sudarshan

A Sample Relational Database System Concepts - 6 th Edition 1. 12 ©Silberschatz, Korth A Sample Relational Database System Concepts - 6 th Edition 1. 12 ©Silberschatz, Korth and Sudarshan

Data Definition Language (DDL) n Specification notation for defining the database schema Example: create Data Definition Language (DDL) n Specification notation for defining the database schema Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8, 2)) n DDL compiler generates a set of table templates stored in a data dictionary n Data dictionary contains metadata (i. e. , data about data) l Database schema l Integrity constraints 4 l Primary key (ID uniquely identifies instructors) Authorization 4 Who can access what Database System Concepts - 6 th Edition 1. 13 ©Silberschatz, Korth and Sudarshan

Data Manipulation Language (DML) n Language for accessing and manipulating the data organized by Data Manipulation Language (DML) n Language for accessing and manipulating the data organized by the appropriate data model l DML also known as query language n Two classes of languages l Pure – used for proving properties about computational power and for optimization 4 Relational 4 Tuple relational calculus 4 Domain l Algebra relational calculus Commercial – used in commercial systems 4 SQL Database System Concepts - 6 th Edition is the most widely used commercial language 1. 14 ©Silberschatz, Korth and Sudarshan

SQL n The most widely used commercial language n SQL is NOT a Turing SQL n The most widely used commercial language n SQL is NOT a Turing machine equivalent language n To be able to compute complex functions SQL is usually embedded in some higher-level language n Application programs generally access databases through one of l Language extensions to allow embedded SQL l Application program interface (e. g. , ODBC/JDBC) which allow SQL queries to be sent to a database Database System Concepts - 6 th Edition 1. 15 ©Silberschatz, Korth and Sudarshan

Database Design The process of designing the general structure of the database: n Logical Database Design The process of designing the general structure of the database: n Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas. l Business decision – What attributes should we record in the database? l Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas? n Physical Design – Deciding on the physical layout of the database Database System Concepts - 6 th Edition 1. 16 ©Silberschatz, Korth and Sudarshan

Database Design (Cont. ) n Is there any problem with this relation? Database System Database Design (Cont. ) n Is there any problem with this relation? Database System Concepts - 6 th Edition 1. 17 ©Silberschatz, Korth and Sudarshan

Design Approaches n Need to come up with a methodology to ensure that each Design Approaches n Need to come up with a methodology to ensure that each of the relations in the database is “good” n Two ways of doing so: l Entity Relationship Model (Chapter 7) 4 Models an enterprise as a collection of entities and relationships 4 Represented diagrammatically by an entity-relationship diagram: l Normalization Theory (Chapter 8) 4 Formalize Database System Concepts - 6 th Edition what designs are bad, and test for them 1. 18 ©Silberschatz, Korth and Sudarshan

Object-Relational Data Models n Relational model: flat, “atomic” values n Object Relational Data Models Object-Relational Data Models n Relational model: flat, “atomic” values n Object Relational Data Models l Extend the relational data model by including object orientation and constructs to deal with added data types. l Allow attributes of tuples to have complex types, including nonatomic values such as nested relations. l Preserve relational foundations, in particular the declarative access to data, while extending modeling power. l Provide upward compatibility with existing relational languages. Database System Concepts - 6 th Edition 1. 19 ©Silberschatz, Korth and Sudarshan

XML: Extensible Markup Language n Defined by the WWW Consortium (W 3 C) n XML: Extensible Markup Language n Defined by the WWW Consortium (W 3 C) n Originally intended as a document markup language not a database language n The ability to specify new tags, and to create nested tag structures made XML a great way to exchange data, not just documents n XML has become the basis for all new generation data interchange formats. n A wide variety of tools is available for parsing, browsing and querying XML documents/data Database System Concepts - 6 th Edition 1. 20 ©Silberschatz, Korth and Sudarshan

Database Engine n Storage manager n Query processing n Transaction manager Database System Concepts Database Engine n Storage manager n Query processing n Transaction manager Database System Concepts - 6 th Edition 1. 21 ©Silberschatz, Korth and Sudarshan

Storage Management n Storage manager is a program module that provides the interface between Storage Management n Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system. n The storage manager is responsible to the following tasks: l Interaction with the OS file manager l Efficient storing, retrieving and updating of data n Issues: l Storage access l File organization l Indexing and hashing Database System Concepts - 6 th Edition 1. 22 ©Silberschatz, Korth and Sudarshan

Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation Database System Concepts - Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation Database System Concepts - 6 th Edition 1. 23 ©Silberschatz, Korth and Sudarshan

Query Processing (Cont. ) n Alternative ways of evaluating a given query l Equivalent Query Processing (Cont. ) n Alternative ways of evaluating a given query l Equivalent expressions l Different algorithms for each operation n Cost difference between a good and a bad way of evaluating a query can be enormous n Need to estimate the cost of operations l Depends critically on statistical information about relations which the database must maintain l Need to estimate statistics for intermediate results to compute cost of complex expressions Database System Concepts - 6 th Edition 1. 24 ©Silberschatz, Korth and Sudarshan

Transaction Management n What if the system fails? n What if more than one Transaction Management n What if the system fails? n What if more than one user is concurrently updating the same data? n A transaction is a collection of operations that performs a single logical function in a database application n Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e. g. , power failures and operating system crashes) and transaction failures. n Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. Database System Concepts - 6 th Edition 1. 25 ©Silberschatz, Korth and Sudarshan

Database Users and Administrators Database System Concepts - 6 th Edition 1. 26 ©Silberschatz, Database Users and Administrators Database System Concepts - 6 th Edition 1. 26 ©Silberschatz, Korth and Sudarshan

Database System Internals Database System Concepts - 6 th Edition 1. 27 ©Silberschatz, Korth Database System Internals Database System Concepts - 6 th Edition 1. 27 ©Silberschatz, Korth and Sudarshan

Database Architecture The architecture of a database systems is greatly influenced by the underlying Database Architecture The architecture of a database systems is greatly influenced by the underlying computer system on which the database is running: n Centralized n Client-server n Parallel (multi-processor) n Distributed Database System Concepts - 6 th Edition 1. 28 ©Silberschatz, Korth and Sudarshan

History of Database Systems n 1950 s and early 1960 s: l Data processing History of Database Systems n 1950 s and early 1960 s: l Data processing using magnetic tapes for storage 4 Tapes l provided only sequential access Punched cards for input n Late 1960 s and 1970 s: l Hard disks allowed direct access to data l Network and hierarchical data models in widespread use l Ted Codd defines the relational data model 4 Would 4 IBM 4 UC l win the ACM Turing Award for this work Research begins System R prototype Berkeley begins Ingres prototype High-performance (for the era) transaction processing Database System Concepts - 6 th Edition 1. 29 ©Silberschatz, Korth and Sudarshan

History (cont. ) n 1980 s: Research relational prototypes evolve into commercial systems 4 History (cont. ) n 1980 s: Research relational prototypes evolve into commercial systems 4 SQL becomes industrial standard l Parallel and distributed database systems l Object-oriented database systems n 1990 s: l Large decision support and data-mining applications l Large multi-terabyte data warehouses l Emergence of Web commerce l n Early 2000 s: XML and XQuery standards l Automated database administration n Later 2000 s: l Giant data storage systems 4 Google Big. Table, Yahoo PNuts, Amazon, . . l Database System Concepts - 6 th Edition 1. 30 ©Silberschatz, Korth and Sudarshan

End of Chapter 1 Database System Concepts - 6 th Edition 1. 31 ©Silberschatz, End of Chapter 1 Database System Concepts - 6 th Edition 1. 31 ©Silberschatz, Korth and Sudarshan