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Chapter 1: Introduction and Basic concepts ( [S] chp. 1) • • • • • • • • • • Purpose of Database Systems View of Data Data Models Data Definition Language Data Manipulation Language Transaction Management Storage Management Database Administrator Database Users Overall System Structure Database System Concepts 1.1 ©Silberschatz, Korth and Sudarshan • A database represents some aspect of the real world, sometimes called the mini-world or the Universe of Discourse (UoD). • A database is a logically coherent collection of data with some inherit meaning. A random assortment of data cannot correctly be referred to as a database. • A database is designed, built, and populated with data for a specific purpose. It has an intended group of users and some preconceived applications in which these users are interested Database System Concepts 1.2 ©Silberschatz, Korth and Sudarshan What Is a Database? • • • A very large, integrated collection of data. Models real-world enterprise. Entities (e.g., students, courses) Relationships (e.g., Madonna is taking CS564) A Database Management System (DBMS) is a software package designed to store and manage databases. Database System Concepts 1.3 ©Silberschatz, Korth and Sudarshan Database Management System (DBMS) Collection of interrelated data Set of programs to access the data DBMS provides an environment that is both convenient and efficient to use. Database Applications: • Banking: all transactions • • • • • Airlines: reservations, schedules Universities: registration, grades Sales: customers, products, purchases Manufacturing: production, inventory, orders, supply chain Human resources: employee records, salaries, tax deductions Databases touch all aspects of our lives Database System Concepts 1.4 ©Silberschatz, Korth and Sudarshan Purpose of Database System • • In the early days, database applications were built on top of file 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. account balance > 0) become part of program code Hard to add new constraints or change existing ones Database System Concepts 1.5 ©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 E.g. 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 E.g. two people reading a balance and updating it at the same time • Security problems Database systems offer solutions to all the above problems Database System Concepts 1.6 ©Silberschatz, Korth and Sudarshan Why Use a DBMS? • • • • • • • • Separation of the Data definition and the Program Abstraction into a simple model Data independence and efficient access. Reduced application development time – ad-hoc queries Data integrity and security. Uniform data administration. Concurrent access, recovery from crashes. Support for multiple different views Database System Concepts 1.7 ©Silberschatz, Korth and Sudarshan Why Study Databases?? • • • ? Shift from computation to information at the “low end”: scramble to webspace (a mess!) at the “high end”: scientific applications Datasets increasing in diversity and volume. Digital libraries, interactive video, Human Genome project, EOS project ... need for DBMS exploding DBMS encompasses most of CS OS, languages, theory, “AI”, multimedia, logic Database System Concepts 1.8 ©Silberschatz, Korth and Sudarshan Levels of Abstraction • Many views, single conceptual (logical) schema and physical schema. View 1 Views describe how users see the data. Conceptual schema defines logical structure. Sometime we separate between conceptual level and logical level Physical schema describes the files and indexes used. View 2 View 3 Conceptual Schema Physical Schema * Schemas are defined using DDL (Data Definition Language) *data is modified/queried using DML (Data Manipulation Language) Database System Concepts 1.9 ©Silberschatz, Korth and Sudarshan Levels of Abstraction • • • Physical level describes how a record (e.g., customer) is stored. Logical level: describes data stored in database, and the relationships among the data. type customer = record name : string; street : string; city : integer; end; View level: application programs hide details of data types. Views can also hide information (e.g., salary) for security purposes. Database System Concepts 1.10 ©Silberschatz, Korth and Sudarshan Instances and Schemas • • Similar to types and variables in programming languages Schema – the logical structure of the database e.g., the database consists of information about a set of customers and accounts and the relationship between them) Analogous to type information of a variable in a program Physical schema: database design at the physical level • 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 Database System Concepts 1.11 ©Silberschatz, Korth and Sudarshan Database System Concepts 1.12 ©Silberschatz, Korth and Sudarshan student name smith brown student number 17 8 class 1 2 course courseName major cosc cosc coursenumber Cradit hours depertment cosc1310 4 cosc cosc3320 4 cosc math2410 3 math cosc3380 3 cosc intro to com duts s cie nce data s tructure s dis database prerequisite coursenumber cosc3380 cosc3330 cosc3320 section sectionldentifier 85 92 102 112 119 135 grade_report student number 17 17 8 8 8 8 Database System Concepts sectionldentifier 112 119 85 92 102 135 rerequisite number cosc3320 math2410 cosc1310 coursenumber math2410 cosc1310 cosc3320 math2410 cosc1310 cosc3380 semester fall fall spring fall fall fall year 86 86 87 87 87 87 instructor king anderson kuuth chang anderson stone grade B C A A B A 1.13 ©Silberschatz, Korth and Sudarshan Data Models • • • • A collection of modeling tools for describing data data relationships data semantics data constraints Entity-Relationship model Relational model Other models: object-oriented model semi-structured data models (XML) Older models: network model and hierarchical model Database System Concepts 1.14 ©Silberschatz, Korth and Sudarshan Entity-Relationship Model Example of schema in the entity-relationship model Database System Concepts 1.15 ©Silberschatz, Korth and Sudarshan Entity Relationship Model (Cont.) • E-R model of real world Entities (objects) E.g. customers, accounts, bank branch Relationships between entities E.g. Account A-101 is held by customer Johnson • Relationship set depositor associates customers with accounts Widely used for database design Database design in E-R model usually converted to design in the relational model (coming up later) which is used for storage and processing Database System Concepts 1.16 ©Silberschatz, Korth and Sudarshan Relational Model • Attributes Example of tabular data in the relational model Customerid customername 192-83-7465 Johnson 019-28-3746 Smith 192-83-7465 Johnson 321-12-3123 Jones 019-28-3746 Smith Database System Concepts customerstreet customercity accountnumber Alma Palo Alto A-101 North Rye A-215 Alma Palo Alto A-201 Main Harrison A-217 North Rye A-201 1.17 ©Silberschatz, Korth and Sudarshan A Sample Relational Database Database System Concepts 1.18 ©Silberschatz, Korth and Sudarshan Physical (Storage) schema decisions • Mapping of entities to files (OS files) • Data representation and encoding (compression) • Access methods (Direct, Hashing, Indexed) • Which indexes to maintain • Clustering of records • OS/DBMS issues (buffer management) Database System Concepts 1.19 ©Silberschatz, Korth and Sudarshan External (View) schema decisions • Which entities to present/filter • Data representation and encoding (compression) • Programming language dependent issues • Changes to names, order of attributes • Derived (computed) fields and joined tables Database System Concepts 1.20 ©Silberschatz, Korth and Sudarshan student name smith brown student number 17 8 class 1 2 course courseName major cosc cosc coursenumber Cradit hours depertment cosc1310 4 cosc cosc3320 4 cosc math2410 3 math cosc3380 3 cosc intro to com duts s cie nce data s tructure s dis database prerequisite coursenumber cosc3380 cosc3330 cosc3320 section sectionldentifier 85 92 102 112 119 135 grade_report student number 17 17 8 8 8 8 Database System Concepts sectionldentifier 112 119 85 92 102 135 rerequisite number cosc3320 math2410 cosc1310 coursenumber math2410 cosc1310 cosc3320 math2410 cosc1310 cosc3380 semester fall fall spring fall fall fall year 86 86 87 87 87 87 instructor king anderson kuuth chang anderson stone grade B C A A B A 1.21 ©Silberschatz, Korth and Sudarshan (*) Not relational… Database System Concepts 1.22 ©Silberschatz, Korth and Sudarshan Data Independence • Physical Data Independence – the ability to modify the physical schema without changing the application programs Applications depend on the logical schema DBA may change physical level (tuning) without affecting applications • The DBMS automatically make the required adjustments, and application programs are not changed (queries may need to be recompiled and optimized…) Logical Data Independence – the ability to modify the logical schema without changing the application programs Applications depend on the logical schema via the Views Can be supported on a limited basis only (if view is not affected) Database System Concepts 1.23 ©Silberschatz, Korth and Sudarshan Data Definition Language (DDL) • • • Specification notation for defining the database schema E.g. create table account ( account-number balance char(10), integer) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata (i.e., data about data) database schema Data storage and definition language language in which the storage structure and access methods used by the database system are specified Usually an extension of the data definition language Database System Concepts 1.24 ©Silberschatz, Korth and Sudarshan Data Manipulation Language (DML) • • Language for accessing and manipulating the data organized by the appropriate data model A declarative DML is also known as query language Two classes of languages Procedural – user specifies what data is required and how to get those data (DML) • Nonprocedural – user specifies what data is required without specifying how to get those data (Query language) SQL is the most widely used query language Database System Concepts 1.25 ©Silberschatz, Korth and Sudarshan SQL • SQL: widely used non-procedural language E.g. find the name of the customer with customer-id 192-83-7465 select customer.customer-name from customer where customer.customer-id = ‘192-83-7465’ • E.g. find the balances of all accounts held by the customer with customer-id 192-83-7465 select account.balance from depositor, account where depositor.customer-id = ‘192-83-7465’ and depositor.account-number = account.account-number 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 1.26 ©Silberschatz, Korth and Sudarshan Database Users • • • • • Users are differentiated by the way they expect to interact with the system Application programmers – interact with system through DML calls Sophisticated users – form requests in a database query language Specialized users – write specialized database applications that do not fit into the traditional data processing framework Naïve users – invoke one of the permanent application programs that have been written previously E.g. people accessing database over the web, bank tellers, clerical staff Database System Concepts 1.27 ©Silberschatz, Korth and Sudarshan Database Administrator • • Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs. Database administrator's duties include: Schema definition Storage structure and access method definition Schema and physical organization modification Granting user authority to access the database Specifying integrity constraints Acting as liaison with users Monitoring performance and responding to changes in requirements Database System Concepts 1.28 ©Silberschatz, Korth and Sudarshan Structure of a DBMS • • • These layers must consider concurrency control and recovery A typical DBMS has a layered architecture. The figure does not show the concurrency control and recovery components. Query Optimization and Execution This is one of several possible architectures; each system has its own variations. Relational Operators Files and Access Methods Buffer Management Disk Space Management DB Database System Concepts 1.29 ©Silberschatz, Korth and Sudarshan Transfer money from: account A to: account B Begin Transaction CRASH! SUBTRACT 100 FROM A ADD 100 TO B End Transaction Abort, Commit, Rollback Database System Concepts 1.30 ©Silberschatz, Korth and Sudarshan READ # SEATS READ # SEATS # SEATS = SEATS –1 # SEATS = #SEATS – 1 WRITE # SEATS WRITE # SEATS Solution: Two-Phase locking Database System Concepts 1.31 ©Silberschatz, Korth and Sudarshan Overall System Structure Database System Concepts 1.32 ©Silberschatz, Korth and Sudarshan Storage Management • • 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. The storage manager is responsible to the following tasks: interaction with the file manager efficient storing, retrieving and updating of data Database System Concepts 1.33 ©Silberschatz, Korth and Sudarshan Concurrency Control • Concurrent execution of user programs good DBMS performance. • • is essential for Because disk accesses are frequent, and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently. Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed. DBMS ensures such problems don’t arise: users can pretend they are using a single-user system. Database System Concepts 1.34 ©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 1.35 ©Silberschatz, Korth and Sudarshan Transaction: An Execution of a DB Program • • Key concept is transaction, which is an atomic sequence of database actions (reads/writes). Each transaction, executed completely, must leave the DB in a consistent state if DB is consistent when the transaction begins. Users can specify some simple integrity constraints on the data, and the DBMS will enforce these constraints. Beyond this, the DBMS does not really understand the semantics of the data. (e.g., it does not understand how the interest on a bank account is computed). Thus, ensuring that a transaction (run alone) preserves consistency is ultimately the user’s responsibility! Database System Concepts 1.36 ©Silberschatz, Korth and Sudarshan Scheduling Concurrent Transactions • DBMS ensures that execution of {T1, ... , Tn} is equivalent to some serial execution T1’ ... Tn’. Before reading/writing an object, a transaction requests a lock on the object, and waits till the DBMS gives it the lock. All locks are released at the end of the transaction. (Strict 2PL locking protocol.) Idea: If an action of Ti (say, writing X) affects Tj (which perhaps reads X), one of them, say Ti, will obtain the lock on X first and Tj is forced to wait until Ti completes; this effectively orders the transactions. What if Tj already has a lock on Y and Ti later requests a lock on Y? (Deadlock!) Ti or Tj is aborted and restarted! Database System Concepts 1.37 ©Silberschatz, Korth and Sudarshan The importance of the Data Dictionary • • • • Contains all definitions: DDL (logical schema), Views definition, Physical schema definitions including Indexing and clustering information, Integrity constraints, security rules, stored procedures (SQL) Essential for query parsing and optimization Contains other important documentation and programs (regulations, standards, codes, etc.) There are companies who sell Data Dictionary tools as a separate product! Database System Concepts 1.38 ©Silberschatz, Korth and Sudarshan •Logical Design and Data-Dictionary Tools •Loading •Physical Design and File reorganization •Backup / Restore / Recovery •Performance Monitoring and Tuning Database System Concepts 1.39 ©Silberschatz, Korth and Sudarshan Application Architectures Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database Three-tier architecture: E.g. web-based applications, and applications built using “middleware” Database System Concepts 1.40 ©Silberschatz, Korth and Sudarshan •Hierarchical – Pre-historic – IMS •Network – Historic –IDMS, ADABAS, lead to Object- Oriented •RELATIONAL- current – 95% of the market – Oracle, Informix, SQL/ Server, Progress, IBM DB2, etc. •Object- ORIENTED Current – lot of HuHa but very narrow market, mainly CAD AND Engineering – Objectivity, Versant, Jasmine •Object – Relational- Current / Future – SQL3, Informix UDO , Oracle-9, IBM DB2. •XML – not much commercial success as a Database, in-spite of much research •Cloud and NOSQL databases Database System Concepts 1.41 ©Silberschatz, Korth and Sudarshan PRE-1960S 1945-magnetic tapes developed (the first medium to allow searching). 1957- First commercial computer installed. 1959- McGee proposed the notion of generalized access to electronically stored data. THE 60s 1961- The first generalized DBMS-GEs Integrated Data Store (IDS) designed by Bachman. THE 70s – database technology experienced rapid growth. 1970- The relational model is developed by Ted Codd, an IBM research fellow. 1971- CODASYL Database Task Group Report. 1975- ACM Special Interest Group on Management of data organized first SIGMOD international conference. 1976- Entity- relationship (ER)model introduced by chen. THE 80s- DBMSs developed for personal computers (DBASE, PARADOX, etc). 1983- ANSI/SPARC survey revealed>100 relational systems had been implemented by the beginning of the 80s. Database System Concepts 1.42 ©Silberschatz, Korth and Sudarshan 1985- Preliminary SQL standard published. Business world influenced by “Fourth Generation Languages”. *Trends in the ‘80s: extendable database systems:object- oriented DBMSs, client server architecture for distributed database. The ’90s * Demand for extending DBMS capabilities to meet new applications. * Emergence of commercial object- oriented DBMSs. * Demand for exploiting massively parallel processors (MPPs). •Total victory by the relational model •SQL 3 •Object relational systems. The ’00s •The emergence of XML and the integration of XML and Relational databases •Web databases, Search engines, Semantic web •Cloud and NOSQL Databases Database System Concepts 1.43 ©Silberschatz, Korth and Sudarshan Databases make these folks happy ... • • • End users and DBMS vendors DB application programmers E.g. smart webmasters Database administrator (DBA) Designs logical /physical schemas Handles security and authorization Data availability, crash recovery Database tuning as needs evolve Must understand how a DBMS works! Database System Concepts 1.44 ©Silberschatz, Korth and Sudarshan Summary • • • • • • • DBMS used to maintain, query large datasets. Benefits include recovery from system crashes, concurrent access, quick application development, data integrity and security. Levels of abstraction give data independence. A DBMS typically has a layered architecture. DBAs hold responsible jobs and are well-paid! DBMS R&D is one of the broadest, most exciting areas in CS. Advanced databases course at the graduate level Database System Concepts 1.45 ©Silberschatz, Korth and Sudarshan