Database System Concepts

Top 10 Largest Databases 2013 By 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)

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

Database Landscape Map – June 2013

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

SAP HANA SAP HANA is an in-memory relational database system. Taken from a talk given by Dr. Wen-Syan Li (VP of SAP)

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

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

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

Relational Model Relational model (Chapter 2) Example of tabular data in the relational model Columns Rows

Schemas and Instances Schema – 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.

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

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

SQL Find the name of the instructor with ID 22222 select name from instructor where instructor.ID = ‘22222’ Find all instructor IDs if they are in a department whose budget > 95000 select instructor.ID, department.dept_name from instructor, department where 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

Storage 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

Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation

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

Atomicity of Updates & Concurrent Access 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

Transaction 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.

Database System Internals