©Silberschatz, Korth and Sudarshan1.1Database System Concepts - 6th Edition

Database System ConceptsDatabase System Concepts

©Silberschatz, Korth and Sudarshan1.2Database System Concepts - 6th Edition

Top 10 Largest Databases 2013Top 10 Largest Databases 2013By Siliconindia NewsBy Siliconindia News

The World Data Centre for Climate (WDCC): 220 terabytes of data, plus 110 terabytes of data for climate simulation, and 6 petabytes of extra data stored in magnetic tapes.

National Energy Research Scientific Computing Center (NERSC) 2.8 petabytes

AT&T: It has the largest volume of data in one unique database, with the most number of rows, 1.9 trillion.

Google: Google accounts every single search that makes each day into its database which is around 91 million searches per day.

Sprint (Telecom company)

LexisNexis

Youtube

Amazon

Central Intelligence Agency (CIA)

Library of Congress (USA)

©Silberschatz, Korth and Sudarshan1.3Database System Concepts - 6th Edition

Database Management System (DBMS)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:

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 touch all aspects of our lives

©Silberschatz, Korth and Sudarshan1.4Database System Concepts - 6th Edition

Database Landscape Map – June 2013Database Landscape Map – June 2013

©Silberschatz, Korth and Sudarshan1.5Database System Concepts - 6th Edition

Google Data CenterGoogle Data Center

Google Cloud SQL allows users to use relational database in Google’s Cloud.

©Silberschatz, Korth and Sudarshan1.6Database System Concepts - 6th Edition

Taken from a talk given by Dr. Wen-Syan Li (VP of SAP)

SAP HANASAP HANA

SAP HANA is an in-memory relational database system.

©Silberschatz, Korth and Sudarshan1.7Database System Concepts - 6th Edition

Taken from a talk given by Dr. Wen-Syan Li (VP of SAP)

©Silberschatz, Korth and Sudarshan1.8Database System Concepts - 6th Edition

Taken from a talk given by Dr. Wen-Syan Li (VP of SAP)

©Silberschatz, Korth and Sudarshan1.9Database System Concepts - 6th Edition

Amazon Web Services (AWS)Amazon Web Services (AWS)

Amazon RDS: a relational database server with minimal administration, using MySQL, Oracle, or SQL Server.

Amazon DynamoDB: a fast highly scalable NoSQL database service.

Amazon SimpleDB: A NoSQL database service for smaller dataasets

Amazon EC2 and EBS: A relational database you can manage on your own.

EC2: Amazon Elastic Compute Cloud

EBS: Amazon Elastic Block Storage

©Silberschatz, Korth and Sudarshan1.10Database System Concepts - 6th Edition

Relational ModelRelational Model

Relational model (Chapter 2)

Example of tabular data in the relational modelColumns

Rows

©Silberschatz, Korth and Sudarshan1.11Database System Concepts - 6th Edition

Schemas and InstancesSchemas and Instances

SchemaSchema – the logical structure of the database (like variables)

Example: The database consists of information about a set of customers and accounts and the relationship between them

Physical schema: database design at the physical level (how we store data on disk for system to fast access data)

Logical schema: database design at the logical level (how users see the data format in order to access data)

Instance – the actual content of the database (like values)

Physical Data Independence – the ability to modify the physical schema without changing the logical schema

Applications depend on the logical schema

Changes in some parts do not seriously influence others.

©Silberschatz, Korth and Sudarshan1.12Database System Concepts - 6th Edition

Data Definition Language (DDL)Data Definition Language (DDL)

Specification notation for defining the database schema

Example: create table instructor ( ID char(5), name char(20), dept_name char(20), salary numeric(8,2))

DDL compiler generates a set of tables stored in a data dictionary

©Silberschatz, Korth and Sudarshan1.13Database System Concepts - 6th Edition

Data Manipulation Language (DML)Data Manipulation Language (DML)

Language for accessing and manipulating the data organized by the appropriate data model

DML also known as query language

SQL is the most widely used query language

Users specifies what data is required and how to get those data

©Silberschatz, Korth and Sudarshan1.14Database System Concepts - 6th Edition

SQLSQL

Find the name of the instructor with ID 22222select namefrom instructorwhere instructor.ID = ‘22222’

Find all instructor IDs if they are in a department whose budget > 95000select instructor.ID, department.dept_namefrom instructor, departmentwhere instructor.dept_name= department.dept_name and department.budget > 95000

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

©Silberschatz, Korth and Sudarshan1.15Database System Concepts - 6th Edition

Storage ManagementStorage Management

Storage manager 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 efficient storing, retrieving and updating of data

Issues:

Storage access

File organization

Indexing and hashing

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Query ProcessingQuery Processing

1. Parsing and translation

2. Optimization

3. Evaluation

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Query Processing (Cont.)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

©Silberschatz, Korth and Sudarshan1.18Database System Concepts - 6th Edition

Atomicity of Updates & Concurrent Atomicity of Updates & Concurrent AccessAccess

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

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 Concurrent access needed for performance

©Silberschatz, Korth and Sudarshan1.19Database System Concepts - 6th Edition

Transaction ManagementTransaction Management

To deal with the system fails.

To control when many users concurrently update 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.

©Silberschatz, Korth and Sudarshan1.20Database System Concepts - 6th Edition

Database System InternalsDatabase System Internals