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UNIT-1 PPT.pptCS 3492 DBMS UNIT 1 to 5 overview Unit 1 slides including purpose of DBMS, Views of data
1.
©Silberschatz, Korth and
Sudarshan 1.1 Database System Concepts - 6th Edition CS3492- DATABASE MANAGEMENT SYSTEMS
2.
©Silberschatz, Korth and
Sudarshan 1.2 Database System Concepts - 6th Edition TEXT BOOKS & REFERENCES Abraham Silberschatz, Henry F.Korth, S.Sudharsan, “Database System Concepts”, Seventh Edition, McGrawHill,2020 Ramez Elmasri, Shamkant B,Navathe, “Fundamentals of Database Systems”, Seventh Edition, Pearson Education,2017 References: 1. C.J.Date, A.Kannan, S.Swamynathan, “An Introduction to Database Systems”, Eighth Edition, Pearson Education, 2006
3.
©Silberschatz, Korth and
Sudarshan 1.3 Database System Concepts - 6th Edition UNIT 1-RELATIONAL DATABASES Purpose of Database System Views of data Data Models Database System Architecture Introduction to relational databases Relational Model Keys Relational algebra SQL fundamentals Advanced SQL features Embedded SQL Dynamic SQL
4.
©Silberschatz, Korth and
Sudarshan 1.4 Database System Concepts - 6th Edition UNIT 2- DATABASE DESIGN Entity-Relationship model E-R Diagrams Enhanced-ER Model ER-to-Relational Mapping Functional Dependencies Non-loss Decomposition-First, Second, Third Normal Forms Dependency Preservation Boyce/Codd Normal Form Multivalued Dependencies Advanced SQL features and Fourth Normal Form Join Dependencies and Fifth Normal Form
5.
©Silberschatz, Korth and
Sudarshan 1.5 Database System Concepts - 6th Edition UNIT 3- TRANSACTIONS Transaction Concepts ACID Properties Schedules Serializability Transaction support in SQL Need for Concurrency-Concurrency Control Two Phase Locking Timestamp Multiversion-Validation and Snapshot Isolation Multiple Granularity Locking Deadlock Handling Recovery Concepts Recovery based on deffered and immediate Shadow Paging-ARIES Algorithm
6.
©Silberschatz, Korth and
Sudarshan 1.6 Database System Concepts - 6th Edition UNIT 4- IMPLEMENTATION TECHNIQUES RAID File Organization Organization of Records in Files Data dictionary storage Column Oriented Storage Indexing and Hashing-Ordered Indices B+ tree index Files B tree index Files Static Hashing-Dynamic Hashing Query Processing overview Algorithms for Selection, Sorting and join operations Query optimization using Heuristics Cost Estimation
7.
©Silberschatz, Korth and
Sudarshan 1.7 Database System Concepts - 6th Edition UNIT 5- ADVANCED TOPICS Distributed Databases: Architecture Data Storage Transaction Processing Query Processing and Optimization NOSQL Databases Introduction-CAP Theorem Document Based Systems Key value stores Column Based Systems-Graph Databases Database Security: Security issues Access control based on privileges-Role based access control SQL Injection-Statistical Database security-Flow control Encryption and Public Key infrastructures-Challenges
8.
©Silberschatz, Korth and
Sudarshan 1.8 Database System Concepts - 6th Edition Outline What is Data? -Known facts -Data especially refer to numbers, but can mean words, sounds and images -the quantities, characters or symbols on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical or mechanical recording media. -Data is raw, unprocessed, unorganized facts and do not carry any significance or meaning. What is information? Information refers to processed data that has been organized, interpreted and contextualized by a human or machine so that it possess relevance and purpose. What is database? A Database is an organized collection of related data
9.
©Silberschatz, Korth and
Sudarshan 1.9 Database System Concepts - 6th Edition Purpose of Database Management System (DBMS) Database Management System is a collection of interrelated data and a set of programs to access those data. The collection of data usually referred to as the database, contains information relevant to enterprise. The primary goal of a DBMS is to provide a way to store and retrieve database information that is both convenient and efficient. Database Applications: Banking: transactions Airlines: reservations, schedules Universities: registration, grades Sales: customers, products, purchases Online retailers: order tracking, customized recommendations Manufacturing: production, inventory, orders, supply chain Human resources: employee records, salaries, tax deductions Databases can be very large. Databases touch all aspects of our lives
10.
©Silberschatz, Korth and
Sudarshan 1.10 Database System Concepts - 6th Edition 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 In the early days, database applications were built directly on top of file systems
11.
©Silberschatz, Korth and
Sudarshan 1.11 Database System Concepts - 6th Edition Drawbacks of using file systems to store data Data redundancy and inconsistency For example, if a student has a double major (say, music and mathematics), the address and telephone number of that student may appear in a file that consists of student records of students in the Music department and in a file that consists of student records of students in the Mathematics department. This redundancy leads to higher storage and access cost. In addition, it may lead to data inconsistency; that is, the various copies of the same data may no longer agree. For example, a changed student address may be reflected in the Music department records but not elsewhere in the system
12.
©Silberschatz, Korth and
Sudarshan 1.12 Database System Concepts - 6th Edition Drawbacks of using file systems to store data 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 “buried” in program code rather than being stated explicitly Hard to add new constraints or change existing ones
13.
©Silberschatz, Korth and
Sudarshan 1.13 Database System Concepts - 6th Edition Drawbacks of using file systems to store data (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 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
14.
©Silberschatz, Korth and
Sudarshan 1.14 Database System Concepts - 6th Edition Advantages of Database Systems Providing backup and recovery services Providing multiple interfaces to different classes of users Representing complex relationship among data. Enforcing integrity constraints on the database Controlling redundancy in data storage and in development and maintenance efforts. Sharing of data among multiple users Restricting unauthorized access to data Providing persistent storage for program objects. Providing Storage Structures for efficient Query Processing.
15.
©Silberschatz, Korth and
Sudarshan 1.15 Database System Concepts - 6th Edition Views of data A major purpose of database system is to provide users with an abstract view of the data. That is, the system hides certain details of how the data are stored and maintained. Physical level: describes how a record (e.g., instructor) is stored. Logical level: describes what 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
16.
©Silberschatz, Korth and
Sudarshan 1.16 Database System Concepts - 6th Edition Levels of Abstraction Physical level: Lowest level of abstraction describes how datas are actually stored. (e.g., instructor) Logical level: describes what data stored in database, and what relationship exist among those data. type instructor = record ID : string; name : string; dept_name : string; salary : integer; end; View level: View level of abstraction simplifies user interaction with the system. The system may provide many views for the same database.
17.
©Silberschatz, Korth and
Sudarshan 1.17 Database System Concepts - 6th Edition View of Data An architecture for a database system
18.
©Silberschatz, Korth and
Sudarshan 1.18 Database System Concepts - 6th Edition 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 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.
19.
©Silberschatz, Korth and
Sudarshan 1.19 Database System Concepts - 6th Edition 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) Semistructured data model (XML) Other older models: Network model Hierarchical model
20.
©Silberschatz, Korth and
Sudarshan 1.20 Database System Concepts - 6th Edition Relational Model All the data is stored in various tables. Example of tabular data in the relational model Columns Rows
21.
©Silberschatz, Korth and
Sudarshan 1.21 Database System Concepts - 6th Edition A Sample Relational Database
22.
©Silberschatz, Korth and
Sudarshan 1.22 Database System Concepts - 6th Edition 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
23.
©Silberschatz, Korth and
Sudarshan 1.23 Database System Concepts - 6th Edition 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 Pure – used for proving properties about computational power and for optimization Relational Algebra Tuple relational calculus Domain relational calculus Commercial – used in commercial systems SQL is the most widely used commercial language
24.
©Silberschatz, Korth and
Sudarshan 1.24 Database System Concepts - 6th Edition SQL The most widely used commercial language SQL is NOT a Turing machine equivalent language 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
25.
©Silberschatz, Korth and
Sudarshan 1.25 Database System Concepts - 6th Edition Database Design 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 The process of designing the general structure of the database:
26.
©Silberschatz, Korth and
Sudarshan 1.26 Database System Concepts - 6th Edition Database Design (Cont.) Is there any problem with this relation?
27.
©Silberschatz, Korth and
Sudarshan 1.27 Database System Concepts - 6th Edition Design Approaches Need to come up with a methodology to ensure that each of the relations in the database is “good” Two ways of doing so: Entity Relationship Model (Chapter 7) Models an enterprise as a collection of entities and relationships Represented diagrammatically by an entity-relationship diagram: Normalization Theory (Chapter 8) Formalize what designs are bad, and test for them
28.
©Silberschatz, Korth and
Sudarshan 1.28 Database System Concepts - 6th Edition Object-Relational Data Models Relational model: flat, “atomic” values Object Relational Data Models Extend the relational data model by including object orientation and constructs to deal with added data types. Allow attributes of tuples to have complex types, including non- atomic values such as nested relations. Preserve relational foundations, in particular the declarative access to data, while extending modeling power. Provide upward compatibility with existing relational languages.
29.
©Silberschatz, Korth and
Sudarshan 1.29 Database System Concepts - 6th Edition XML: Extensible Markup Language Defined by the WWW Consortium (W3C) Originally intended as a document markup language not a database language The ability to specify new tags, and to create nested tag structures made XML a great way to exchange data, not just documents XML has become the basis for all new generation data interchange formats. A wide variety of tools is available for parsing, browsing and querying XML documents/data
30.
©Silberschatz, Korth and
Sudarshan 1.30 Database System Concepts - 6th Edition Database Engine Storage manager Query processing Transaction manager
31.
©Silberschatz, Korth and
Sudarshan 1.31 Database System Concepts - 6th Edition 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 OS file manager Efficient storing, retrieving and updating of data Issues: Storage access File organization Indexing and hashing
32.
©Silberschatz, Korth and
Sudarshan 1.32 Database System Concepts - 6th Edition Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation
33.
©Silberschatz, Korth and
Sudarshan 1.33 Database System Concepts - 6th Edition Query Processing (Cont.) Alternative ways of evaluating a given query Equivalent expressions Different algorithms for each operation Cost difference between a good and a bad way of evaluating a query can be enormous Need to estimate the cost of operations Depends critically on statistical information about relations which the database must maintain Need to estimate statistics for intermediate results to compute cost of complex expressions
34.
©Silberschatz, Korth and
Sudarshan 1.34 Database System Concepts - 6th Edition Transaction Management What if the system fails? What if more than one user is concurrently updating the same data? 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.
35.
©Silberschatz, Korth and
Sudarshan 1.35 Database System Concepts - 6th Edition Database Users and Administrators Database
36.
©Silberschatz, Korth and
Sudarshan 1.36 Database System Concepts - 6th Edition Database System Internals
37.
©Silberschatz, Korth and
Sudarshan 1.37 Database System Concepts - 6th Edition Database Architecture The architecture of a database systems is greatly influenced by the underlying computer system on which the database is running: Centralized Client-server Parallel (multi-processor) Distributed
38.
©Silberschatz, Korth and
Sudarshan 1.38 Database System Concepts - 6th Edition 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 begins Ingres prototype High-performance (for the era) transaction processing
39.
©Silberschatz, Korth and
Sudarshan 1.39 Database System Concepts - 6th Edition 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 data warehouses Emergence of Web commerce Early 2000s: XML and XQuery standards Automated database administration Later 2000s: Giant data storage systems Google BigTable, Yahoo PNuts, Amazon, ..
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