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EuphoricCuboFuturism4388

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Silberschatz, Korth and Sudarshan

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database systems database design database concepts computer science

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This document is an introduction to database concepts. It covers various aspects of database systems, including their purpose, application examples, and design considerations. The different components of a database system and various database architectures are explored in detail.

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Chapter 1: Introduction Database System Concepts, 7th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Outline ▪ Database-System Applications ▪ Purpose of Database Systems ▪ V...

Chapter 1: Introduction Database System Concepts, 7th Ed. ©Silberschatz, Korth and Sudarshan See www.db-book.com for conditions on re-use Outline ▪ Database-System Applications ▪ Purpose of Database Systems ▪ View of Data ▪ Database Languages ▪ Database Design ▪ Database Engine ▪ Database Architecture ▪ Database Users and Administrators ▪ History of Database Systems Database System Concepts - 7th 1.2 ©Silberschatz, Korth and Sudarshan Database Systems ▪ 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 systems are used to manage collections of data that are: Highly valuable Relatively large Accessed by multiple users and applications, often at the same time. ▪ A modern database system is a complex software system whose task is to manage a large, complex collection of data. ▪ Databases touch all aspects of our lives Database System Concepts - 7th 1.3 ©Silberschatz, Korth and Sudarshan Database Applications Examples ▪ Enterprise Information Sales: customers, products, purchases Accounting: payments, receipts, assets Human Resources: Information about employees, salaries, payroll taxes. ▪ Manufacturing: management of production, inventory, orders, supply chain. ▪ Banking and finance customer information, accounts, loans, and banking transactions. Credit card transactions Finance: sales and purchases of financial instruments (e.g., stocks and bonds; storing real-time market data ▪ Universities: registration, grades Database System Concepts - 7th 1.4 ©Silberschatz, Korth and Sudarshan Database Applications Examples (Cont.) ▪ Airlines: reservations, schedules ▪ Telecommunication: records of calls, texts, and data usage, generating monthly bills, maintaining balances on prepaid calling cards ▪ Web-based services Online retailers: order tracking, customized recommendations Online advertisements ▪ Document databases ▪ Navigation systems: For maintaining the locations of varies places of interest along with the exact routes of roads, train systems, buses, etc. Database System Concepts - 7th 1.5 ©Silberschatz, Korth and Sudarshan Purpose of Database Systems/Drawbacks of using file systems to store data In the early days, database applications were built directly on top of file systems, which leads to: ▪ Data redundancy and inconsistency: data is stored in multiple file formats resulting in 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., account balance > 5000) become “buried” in program code rather than being stated explicitly Hard to add new constraints or change existing ones Database System Concepts - 7th 1.6 ©Silberschatz, Korth and Sudarshan Purpose of Database 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 access needed for performance Uncontrolled concurrent accesses can lead to inconsistencies ▪ Ex: 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 - 7th 1.7 ©Silberschatz, Korth and Sudarshan University Database Example ▪ In this text we will be using a university database to illustrate all the concepts ▪ Data consists of information about: Students Instructors Classes ▪ 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 Teacher evaluation !!!!! Database System Concepts - 7th 1.8 ©Silberschatz, Korth and Sudarshan View of Data ▪ A database system is a collection of interrelated data and a set of programs that allow users to access and modify these data. ▪ A major purpose of a database system is to provide users with an abstract view of the data. Data models ▪ A collection of conceptual tools for describing data, data relationships, data semantics, and consistency constraints. Data abstraction ▪ Hide the complexity of data structures to represent data in the database from users through several levels of data abstraction. Database System Concepts - 7th 1.9 ©Silberschatz, Korth and Sudarshan Data Models ▪ A collection of tools for describing Data Data relationships Data semantics Data constraints ▪ Relational model ▪ Entity-Relationship data model (mainly for database design) ▪ Object-based data models (Object-oriented and Object-relational) ▪ Semi-structured data model (XML) ▪ Other older models: Network model Hierarchical model Database System Concepts - 7th 1.10 ©Silberschatz, Korth and Sudarshan Relational Model ▪ All the data is stored in various tables. ▪ Example of tabular data in the relational model Columns Rows Ted Codd Turing Award 1981 Database System Concepts - 7th 1.11 ©Silberschatz, Korth and Sudarshan A Sample Relational Database Database System Concepts - 7th 1.12 ©Silberschatz, Korth and Sudarshan Levels of Abstraction ▪ Physical level: describes how a record (e.g., instructor) is stored. ▪ 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; ▪ 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 - 7th 1.13 ©Silberschatz, Korth and Sudarshan View of Data An architecture for a database system Database System Concepts - 7th 1.14 ©Silberschatz, Korth and Sudarshan Instances and Schemas ▪ Similar to types and variables in programming languages ▪ Logical Schema – the overall logical structure of the database Example: The database consists of information about a set of customers and accounts in a bank and the relationship between them ▪ Analogous to type information of a variable in a program ▪ Physical schema – the overall physical structure of the database ▪ Instance – the actual content of the database at a particular point in time Analogous to the value of a variable Database System Concepts - 7th 1.15 ©Silberschatz, Korth and Sudarshan Physical Data Independence ▪ Physical Data Independence – the ability to modify the physical schema without changing the logical schema Applications depend on the logical schema 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 - 7th 1.16 ©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 table templates stored in a data dictionary ▪ Data dictionary contains metadata (i.e., data about data) Database schema Integrity constraints ▪ Primary key (ID uniquely identifies instructors) Authorization ▪ Who can access what Database System Concepts - 7th 1.17 ©Silberschatz, Korth and Sudarshan Data Manipulation Language (DML) ▪ Language for accessing and updating the data organized by the appropriate data model DML also known as query language ▪ There are basically two types of data-manipulation language Procedural DML -- require a user to specify what data are needed and how to get those data. Declarative DML -- require a user to specify what data are needed without specifying how to get those data. ▪ Declarative DMLs are usually easier to learn and use than are procedural DMLs. ▪ Declarative DMLs are also referred to as non-procedural DMLs ▪ The portion of a DML that involves information retrieval is called a query language. Database System Concepts - 7th 1.18 ©Silberschatz, Korth and Sudarshan SQL Query Language ▪ SQL query language is nonprocedural. A query takes as input several tables (possibly only one) and always returns a single table. ▪ Example to find all instructors in Comp. Sci. dept select name from instructor where dept_name = 'Comp. Sci.' ▪ SQL is NOT a Turing machine equivalent language ▪ To be able to compute complex functions SQL is usually embedded in some higher-level language ▪ Application programs generally access databases through one of Language extensions to allow embedded SQL Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database Database System Concepts - 7th 1.19 ©Silberschatz, Korth and Sudarshan Database Access from Application Program ▪ Non-procedural query languages such as SQL are not as powerful as a universal Turing machine. ▪ SQL does not support actions such as input from users, output to displays, or communication over the network. ▪ Such computations and actions must be written in a host language, such as C/C++, Java or Python, with embedded SQL queries that access the data in the database. ▪ Application programs -- are programs that are used to interact with the database in this fashion. Database System Concepts - 7th 1.20 ©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 - 7th 1.21 ©Silberschatz, Korth and Sudarshan Database Engine ▪ A database system is partitioned into modules that deal with each of the responsibilities of the overall system. ▪ The functional components of a database system can be divided into The storage manager, The query processor component, The transaction management component. Database System Concepts - 7th 1.22 ©Silberschatz, Korth and Sudarshan Storage Manager ▪ 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. ▪ The storage manager is responsible to the following tasks: Interaction with the OS file manager Efficient storing, retrieving and updating of data ▪ The storage manager components include: Authorization and integrity manager Transaction manager File manager Buffer manager Database System Concepts - 7th 1.23 ©Silberschatz, Korth and Sudarshan Storage Manager (Cont.) ▪ The storage manager implements several data structures as part of the physical system implementation: Data files -- store the database itself Data dictionary -- stores metadata about the structure of the database, in particular the schema of the database. Indices -- can provide fast access to data items. A database index provides pointers to those data items that hold a particular value. Database System Concepts - 7th 1.24 ©Silberschatz, Korth and Sudarshan Query Processor ▪ The query processor components include: DDL interpreter -- interprets DDL statements and records the definitions in the data dictionary. DML compiler -- translates DML statements in a query language into an evaluation plan consisting of low-level instructions that the query evaluation engine understands. ▪ The DML compiler performs query optimization; that is, it picks the lowest cost evaluation plan from among the various alternatives. Query evaluation engine -- executes low-level instructions generated by the DML compiler. Database System Concepts - 7th 1.25 ©Silberschatz, Korth and Sudarshan Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation Database System Concepts - 7th 1.26 ©Silberschatz, Korth and Sudarshan Transaction Management ▪ A transaction is a collection of operations that performs a single logical function in a database application ▪ 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. ▪ Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. Database System Concepts - 7th 1.27 ©Silberschatz, Korth and Sudarshan Database Architecture ▪ Centralized databases One to a few cores, shared memory ▪ Client-server, One server machine executes work on behalf of multiple client machines. ▪ Parallel databases Many core shared memory Shared disk Shared nothing ▪ Distributed databases Geographical distribution Schema/data heterogeneity Database System Concepts - 7th 1.28 ©Silberschatz, Korth and Sudarshan Database Architecture (Centralized/Shared-Memory) Database System Concepts - 7th 1.29 ©Silberschatz, Korth and Sudarshan Database Applications Database applications are usually partitioned into two or three parts ▪ Two-tier architecture -- the application resides at the client machine, where it invokes database system functionality at the server machine ▪ Three-tier architecture -- the client machine acts as a front end and does not contain any direct database calls. The client end communicates with an application server, usually through a forms interface. The application server in turn communicates with a database system to access data. Database System Concepts - 7th 1.30 ©Silberschatz, Korth and Sudarshan Two-tier and three-tier architectures Database System Concepts - 7th 1.31 ©Silberschatz, Korth and Sudarshan Database Users Database System Concepts - 7th 1.32 ©Silberschatz, Korth and Sudarshan Database Administrator A person who has central control over the system is called a database administrator (DBA). Functions of a DBA include: ▪ Schema definition ▪ Storage structure and access-method definition ▪ Schema and physical-organization modification ▪ Granting of authorization for data access ▪ Routine maintenance ▪ Periodically backing up the database ▪ Ensuring that enough free disk space is available for normal operations, and upgrading disk space as required ▪ Monitoring jobs running on the database Database System Concepts - 7th 1.33 ©Silberschatz, Korth and Sudarshan History of Database Systems ▪ 1950s and early 1960s: Data processing using magnetic tapes for storage ▪ Tapes provided only sequential access Punched cards for input ▪ Late 1960s and 1970s: Hard disks allowed 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 (Michael Stonebraker) begins Ingres prototype ▪ Oracle releases first commercial relational database High-performance (for the era) transaction processing Database System Concepts - 7th 1.34 ©Silberschatz, Korth and Sudarshan History of Database Systems (Cont.) ▪ 1980s: Research relational prototypes evolve into commercial systems ▪ SQL becomes industrial standard Parallel and distributed database systems ▪ Wisconsin, IBM, Teradata Object-oriented database systems ▪ 1990s: Large decision support and data-mining applications Large multi-terabyte data warehouses Emergence of Web commerce Database System Concepts - 7th 1.35 ©Silberschatz, Korth and Sudarshan History of Database Systems (Cont.) ▪ 2000s Big data storage systems ▪ Google BigTable, Yahoo PNuts, Amazon, ▪ “NoSQL” systems. Big data analysis: beyond SQL ▪ Map reduce and friends ▪ 2010s SQL reloaded ▪ SQL front end to Map Reduce systems ▪ Massively parallel database systems ▪ Multi-core main-memory databases Database System Concepts - 7th 1.36 ©Silberschatz, Korth and Sudarshan End of Chapter 1 Database System Concepts - 7th 1.37 ©Silberschatz, Korth and Sudarshan

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