Principles of Data Management Syllabus & Intro Welcome! Course website: Spr16/teaching.htmImportant Pre-ReqSpr16/teaching.htmImportant Pre-Req Text Book(s) Workload Intended Schedule Projects Grading Reading List What Is a DBMS? 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 data. Files vs. DBMS Application must stage large datasets between main memory and secondary storage (e.g., buffering, page-oriented access, 32-bit addressing, etc.) Special code for different queries Must protect data from inconsistency due to multiple concurrent users Crash recovery Security and access control Why Use a DBMS? Data independence and efficient access. Reduced application development time. Data integrity and security. Uniform data administration. Concurrent access, recovery from crashes. 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 ? A Brief DB History Early 1970s Many database systems Incompatible, exposing many implementation details Then Ted Codd came along Relational model Structured Query Language (SQL) Implementation differences became irrelevant A few major DB systems dominated the market Then Web 2.0 & 3.0, Big Data Happen What do you think happen? Semi-structured data happen. A lot of it and in many forms Some Facts about Web x.0 and Big Data Twitter: 255 million monthly active users and 500 million Tweets are sent per day, Facebook: over 1 billion monthly users and faces 3 million message per 20 minute Instagram: 200 Million Monthly Active Users and 1.6 Billion Likes and 60 Million Photos shared every day Database Systems Landscape Nowadays Somebody, Please, Bring Some Order to This Madness Contd NoSQL Databases Somebody, Please, Bring Some Order to This Madness Different Interfaces Different hardware support Different application support Lack of Uniformity Source: Database Evolution Timeline Additional Resources Tutorial by C. Mohan, An In-Depth Look at Modern Database Systems https://docs.google.com/file/d/0B7lNUaak 0bK1encwYnBVUWZSWjA/edit Relational Data Tables or Relations Relational Database: Schemas Relational Database: Query Language SQL - Structured Query Language a declarative language designed for managing data held in a relational database management system Tell what you want and from where Do not tell: how to get the data Key-Value Store Implemented as an associative array, map, symbol table, or dictionary abstract data type composed of a collection of ( key, value ) pairs such that each possible key appears at most once in the collection. A simple put / get interface Great properties: scalability, availability, reliability Key-Value Store Usage Scenarios Increasingly popular within data centers and in P2P Data center P2P Dynamo amazon.com Voldemort LinkedIn Cassandra Facebook Vuze DHT Vuze uTorrent DHT uTorrent Row Store and Column Store In row store data are stored in the disk tuple by tuple. Where in column store data are stored in the disk column by column. Column-stores are more I/O efficient for read-only queries as they read, only those attributes which are accessed by a query. Source: Column-Oriented Database Systems, VLDB Tutorial; S. Harizopoulos, D. Abadi, P. Boncz Row Store and Column Store So column stores are suitable for read-mostly, read-intensive, large data repositories Row StoreColumn Store (+) Easy to add/modify a record (+) Only need to read in relevant data (-) Might read in unnecessary data (-) Tuple writes require multiple accesses Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke24 Program Flow Ecological Network Biological Network Social Network Chemical Network Web Graph Graph Databases Graph Databases: Query Find all the restaurants my friends (in Facebook) like So, Why Study Relational DBs? Jack Clark, The Register, 30 August 2013 : The tech world is turning back toward SQL, bringing to a close a possibly misspent half-decade in which startups courted developers with promises of infinite scalability and the finest imitation-Google tools available, and companies found themselves exposed to unstable data and poor guarantees. Google Spanner paper, October 2012 : We believe it is better to have application programmers deal with performance problems due to overuse of transactions as bottlenecks arise, rather than always coding around the lack of transactions. Sean Doherty in Wired, September 2013 : But dont become unnecessarily distracted by the shiny, new-fangled, NoSQL red buttons just yet. Relational databases may not be hot or sexy but for your important data there is no substitute. And, The Key Reason of All Gartner estimates RDBMS market at $26B with about 9% annual growth, whereas Market Research Media Ltd expects NoSQL market to be at $3.5B by Source: C Mohans tutorial 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 Management Systems 3ed, R. Ramakrishnan and J. Gehrke29 Structure of a DBMS A typical DBMS has a layered architecture. The figure does not show the concurrency control and recovery components. This is one of several possible architectures; each system has its own variations. Query Optimization and Execution Relational Operators Files and Access Methods Buffer Management Disk Space Management DB These layers must consider concurrency control and recovery 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.