Lecture 3.PPt.pdf

Chapter 1: Introduction Database System Concepts, 6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use  Database Management System (DBMS) DBMS contains information about a particular enterprise  Colle...

Chapter 1: Introduction Database System Concepts, 6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use  Database Management System (DBMS) DBMS contains information about a particular enterprise  Collection of interrelated data  Set of programs to access the data  An environment that is both convenient and efficient to use Database Applications:  Airlines: reservations, schedules  Universities: registration, grades  Sales: customers, products, purchases, order tracking  Employee records, salaries,  ….. Databases touch all aspects of our lives Database System Concepts - 6th Edition 1.2 ©Silberschatz, Korth and Sudarshan  University Database Example Application program examples  Add new students, instructors, and courses  Register students for courses, and generate class rosters  Assign grades to students, compute grade point averages (GPA) and generate transcripts  Clicker data: record attendance and quiz answers  Quiz Q1: Click 1 now! In the early days, database applications were built directly on top of file systems Database System Concepts - 6th Edition 1.3 ©Silberschatz, Korth and Sudarshan  Purpose of Database Systems Drawbacks of using file systems to store data:  Data redundancy and inconsistency  Multiple file formats, duplication of information in different files  Difficulty in accessing data  Need to write a new program to carry out each new task  Data isolation — multiple files and formats  Integrity problems  Integrity constraints (e.g. “dept_name of student must be a valid department name”) become “buried” in program code rather than being stated explicitly  Hard to add new constraints or change existing ones Database System Concepts - 6th Edition 1.4 ©Silberschatz, Korth and Sudarshan  Purpose of Database Systems (Cont.) Drawbacks of using file systems (cont.) Atomicity of updates   Failures may leave database in an inconsistent state with partial updates carried out  Example: Transfer of funds from one account to another should either complete or not happen at all  Concurrent access by multiple users  Concurrent accessed needed for performance  Uncontrolled concurrent accesses can lead to inconsistencies – Example: Two people reading a balance (say 100) and updating it by withdrawing money (say 50 each) at the same time  Security problems  Hard to provide user access to some, but not all, data Database systems offer solutions to all the above problems Database System Concepts - 6th Edition 1.5 ©Silberschatz, Korth and Sudarshan  Instances and Schemas Similar to types and variables in programming languages Schema – the logical structure of the database  Analogous to type information of a variable in a program  Physical schema: database design at the physical level  E.g. data storage structures, indices for fast access  Logical schema: database design at the logical level Instance – the actual content of the database at a particular point in time  Analogous to the value of a variable Physical Data Independence – the ability to modify the physical schema without changing the logical schema  Applications depend on the logical schema Database System Concepts - 6th Edition 1.6 ©Silberschatz, Korth and Sudarshan  Data Models A collection of tools for describing  Data  Data relationships  Data semantics : is an abstraction that defines how the stored symbols (the instance data) relate to the real world.  Data constraints : constraints are used to limit the type of data that can go into a table. This ensures the accuracy and reliability of the data in the table. Relational model Entity-Relationship data model (mainly for database design) Object-based data models (Object-oriented and Object- relational): focus is on how data is represented. The data is divided into multiple entities each of which have some defining characteristics Semistructured data model (XML) Network model Hierarchical model Database System Concepts - 6th Edition 1.7 ©Silberschatz, Korth and Sudarshan  Relational Model Relational model (Chapter 2) Columns Example of tabular data in the relational model Rows Database System Concepts - 6th Edition 1.8 ©Silberschatz, Korth and Sudarshan  A Sample Relational Database instructor department Database System Concepts - 6th Edition 1.9 ©Silberschatz, Korth and Sudarshan  Data Manipulation Language (DML) Language for accessing and manipulating the data organized by the appropriate data model  DML also known as query language Two classes of languages  Procedural – user specifies what data is required and how to get those data  Declarative (nonprocedural) – user specifies what data is required without specifying how to get those data SQL is the most widely used query language Database System Concepts - 6th Edition 1.10 ©Silberschatz, Korth and Sudarshan  Data Definition Language (DDL) 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)) DDL compiler generates a set of tables Data dictionary contains metadata (i.e., data about data)  Database schema  Which tables are present, what are their attributes, …  Integrity constraints  Which attributes are primary keys, foreign keys, … Database System Concepts - 6th Edition 1.11 ©Silberschatz, Korth and Sudarshan  Data Definition Language (DDL) Foreign key primary key Foreign key is a column that primary key constrain is a column creates a relationship between two or group of columns that uniquely tables identifies every row in the table of the relational database management system Database System Concepts - 6th Edition 1.12 ©Silberschatz, Korth and Sudarshan  Database Design The process of designing the general structure of the database: Logical Design – Deciding on the database schema. Database design requires that we find a “good” collection of relation schemas.  Business decision – What attributes should we record in the database?  Computer Science decision – What relation schemas should we have and how should the attributes be distributed among the various relation schemas? Physical Design – Deciding on the physical layout of the database Database System Concepts - 6th Edition 1.13 ©Silberschatz, Korth and Sudarshan  Database Design? Is there any problem with this design? Quiz Q2: The problem is: (1) missing information (2) repeated information (3) there is no problem (4) these instructor salaries are too low Database System Concepts - 6th Edition 1.14 ©Silberschatz, Korth and Sudarshan  Design Approaches Normalization Theory (Normalization is the process of organizing data in a database. This includes creating tables and establishing relationships between those tables according to rules designed both to protect the data and to make the database more flexible by eliminating redundancy and inconsistent dependency - Chapter 8)  Formalize what designs are bad, and test for them Entity Relationship Model (E–R model is usually the result of systematic analysis to define and describe what data is created and needed by processes in an area of a business –e.g. flow Chart -Chapter 7)  Models used in an enterprise as a collection of entities and relationships  Entity: a “thing” or “object” in the enterprise that is distinguishable from other objects – Described by a set of attributes  Relationship: an association among several entities  Represented diagrammatically by an entity-relationship diagram: Database System Concepts - 6th Edition 1.15 ©Silberschatz, Korth and Sudarshan  Database System Internals Query Processor Storage Manager Storage Database System Concepts - 6th Edition 1.16 ©Silberschatz, Korth and Sudarshan  History of Database Systems 1950s and early 1960s:  Data processing using magnetic tapes for storage  Tapes provide only sequential access  Punched cards for input Late 1960s and 1970s:  Hard disks allow direct access to data  Network and hierarchical data models in widespread use  Ted Codd defines the relational data model  Would win the ACM Turing Award for this work  IBM Research begins System R prototype  UC Berkeley begins Ingres prototype  High-performance (for the era) transaction processing Database System Concepts - 6th Edition 1.17 ©Silberschatz, Korth and Sudarshan  History (cont.) 1980s:  Research relational prototypes evolve into commercial systems  SQL becomes industrial standard  Parallel and distributed database systems  Object-oriented database systems 1990s:  Large decision support and data-mining applications  Large multi-terabyte parallel data warehouses  Emergence of Web commerce Early 2000s:  XML and XQuery standards  Automated database administration Later 2000s: Big Data  massively parallel storage systems  Google BigTable, Yahoo PNuts, Amazon,..  Parallel data analysis, using MapReduce Database System Concepts - 6th Edition 1.18 ©Silberschatz, Korth and Sudarshan  End of Chapter 1 Database System Concepts, 6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Database Users and Administrators Database Database System Concepts, 6th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use