Data_base.pptx
- 1. Relational Databases and SQLite Charles Severance Python for Everybody www.py4e.com/lectures3/
- 4. Random Access • When you can randomly access data... • How can you layout data to be most efficient? • Sorting might not be the best idea https://en.wikipedia.org/wiki/Hard_disk_drive_platter
- 5. Relational Databases http://en.wikipedia.org/wiki/Relational_database Relational databases model data by storing rows and columns in tables. The power of the relational database lies in its ability to efficiently retrieve data from those tables and in particular where there are multiple tables and the relationships between those tables involved in the query.
- 6. Terminology • Database - contains many tables • Relation (or table) - contains tuples and attributes • Tuple (or row) - a set of fields that generally represents an “object” like a person or a music track • Attribute (also column or field) - one of possibly many elements of data corresponding to the object represented by the row
- 7. A relation is defined as a set of tuples that have the same attributes. A tuple usually represents an object and information about that object. Objects are typically physical objects or concepts. A relation is usually described as a table, which is organized into rows and columns. All the data referenced by an attribute are in the same domain and conform to the same constraints. (Wikipedia)
- 8. Tables / Relations Columns / Attributes Rows / Tuples
- 9. SQL Structured Query Language is the language we use to issue commands to the database - Create data (a.k.a Insert) - Retrieve data - Update data - Delete data http://en.wikipedia.org/wiki/SQL
- 11. Web Applications w/ Databases • Application Developer - Builds the logic for the application, the look and feel of the application - monitors the application for problems • Database Administrator - Monitors and adjusts the database as the program runs in production • Often both people participate in the building of the “Data model”
- 13. Database Administrator http://en.wikipedia.org/wiki/Database_administrator A database administrator (DBA) is a person responsible for the design, implementation, maintenance, and repair of an organization’s database. The role includes the development and design of database strategies, monitoring and improving database performance and capacity, and planning for future expansion requirements. They may also plan, coordinate, and implement security measures to safeguard the database.
- 14. Database Model http://en.wikipedia.org/wiki/Database_model A database model or database schema is the structure or format of a database, described in a formal language supported by the database management system. In other words, a “database model” is the application of a data model when used in conjunction with a database management system.
- 15. Common Database Systems • Three major Database Management Systems in wide use - Oracle - Large, commercial, enterprise-scale, very very tweakable - MySql - Simpler but very fast and scalable - commercial open source - SqlServer - Very nice - from Microsoft (also Access) • Many other smaller projects, free and open source - HSQL, SQLite, Postgres, ...
- 16. SQLite is in Lots of Software... http://www.sqlite.org/famous.html
- 17. SQLite Browser • SQLite is a very popular database - it is free and fast and small • SQLite Browser allows us to directly manipulate SQLite files • http://sqlitebrowser.org/ • SQLite is embedded in Python and a number of other languages
- 19. Lets Make a Database https://www.py4e.com/lectures3/Pythonlearn-15-Database-Handout.txt
- 20. Start Simple - A Single Table CREATE TABLE Users( name VARCHAR(128), email VARCHAR(128) )
- 22. Our table with four rows
- 23. SQL http://en.wikipedia.org/wiki/SQL Structured Query Language is the language we use to issue commands to the database - Create data (a.k.a Insert) - Retrieve data - Update data - Delete data
- 24. SQL: Insert The Insert statement inserts a row into a table INSERT INTO Users (name, email) VALUES ('Kristin', 'kf@umich.edu')
- 27. SQL: Delete Deletes a row in a table based on selection criteria DELETE FROM Users WHERE email='ted@umich.edu'
- 30. SQL: Update Allows the updating of a field with a where clause UPDATE Users SET name='Charles' WHERE email='csev@umich.edu'
- 33. Retrieving Records: Select The select statement retrieves a group of records - you can either retrieve all the records or a subset of the records with a WHERE clause SELECT * FROM Users SELECT * FROM Users WHERE email='csev@umich.edu'
- 36. Sorting with ORDER BY You can add an ORDER BY clause to SELECT statements to get the results sorted in ascending or descending order SELECT * FROM Users ORDER BY email SELECT * FROM Users ORDER BY name DESC
- 38. SQL Summary SELECT * FROM Users SELECT * FROM Users WHERE email='csev@umich.edu' UPDATE Users SET name="Charles" WHERE email='csev@umich.edu' INSERT INTO Users (name, email) VALUES ('Kristin', 'kf@umich.edu') DELETE FROM Users WHERE email='ted@umich.edu' SELECT * FROM Users ORDER BY email
- 39. This is not too exciting (so far) • Tables pretty much look like big fast programmable spreadsheets with rows, columns, and commands • The power comes when we have more than one table and we can exploit the relationships between the tables
- 40. Complex Data Models and Relationships http://en.wikipedia.org/wiki/Relational_model
- 41. Database Design • Database design is an art form of its own with particular skills and experience • Our goal is to avoid the really bad mistakes and design clean and easily understood databases • Others may performance tune things later • Database design starts with a picture...
- 44. Building a Data Model • Drawing a picture of the data objects for our application and then figuring out how to represent the objects and their relationships • Basic Rule: Don’t put the same string data in twice - use a relationship instead • When there is one thing in the “real world” there should be one copy of that thing in the database
- 45. Track Len Artist Album Genre Rating Count
- 46. For each “piece of info”... • Is the column an object or an attribute of another object? • Once we define objects, we need to define the relationships between objects Track Len Artist Album Genre Rating Count
- 50. Representing Relationships in a Database
- 51. Database Normalization (3NF) • There is *tons* of database theory - way too much to understand without excessive predicate calculus • Do not replicate data - reference data - point at data • Use integers for keys and for references • Add a special “key” column to each table which we will make references to. By convention, many programmers call this column “id” http://en.wikipedia.org/wiki/Database_normalization
- 52. We want to keep track of which band is the “creator” of each music track... What album does this song “belong to”?? Which album is this song related to?
- 53. Integer Reference Pattern We use integers to reference rows in another table Album Artist
- 54. Three Kinds of Keys • Primary key - generally an integer auto- increment field • Logical key - What the outside world uses for lookup • Foreign key - generally an integer key pointing to a row in another table Album id title artist_id ...
- 55. Key Rules Best practices • Never use your logical key as the primary key • Logical keys can and do change, albeit slowly • Relationships that are based on matching string fields are less efficient than integers User id login password name email created_at modified_at login_at
- 56. Foreign Keys • A foreign key is when a table has a column that contains a key which points to the primary key of another table. • When all primary keys are integers, then all foreign keys are integers - this is good - very good Artist id name ... Album id title artist_id ...
- 57. Relationship Building (in tables)
- 59. Album belongs-to Album id title Track id title rating len count album_id Table Primary key Logical key Foreign key Track Len Rating Count Title
- 60. Album id title Track id title rating len count album_id Table Primary key Logical key Foreign key Artist id name artist_id Genre id name genre_id Naming FK artist_id is a convention
- 62. CREATE TABLE Genre ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, name TEXT )
- 63. CREATE TABLE Track ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, title TEXT, album_id INTEGER, genre_id INTEGER, len INTEGER, rating INTEGER, count INTEGER ) CREATE TABLE Album ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, artist_id INTEGER, title TEXT )
- 65. insert into Artist (name) values ('Led Zepplin') insert into Artist (name) values ('AC/DC')
- 66. insert into Artist (name) values ('Led Zepplin') insert into Artist (name) values ('AC/DC')
- 67. insert into Genre (name) values ('Rock') insert into Genre (name) values ('Metal')
- 68. insert into Album (title, artist_id) values ('Who Made Who', 2) insert into Album (title, artist_id) values ('IV', 1)
- 69. insert into Track (title, rating, len, count, album_id, genre_id) values ('Black Dog', 5, 297, 0, 2, 1) insert into Track (title, rating, len, count, album_id, genre_id) values ('Stairway', 5, 482, 0, 2, 1) insert into Track (title, rating, len, count, album_id, genre_id) values ('About to Rock', 5, 313, 0, 1, 2) insert into Track (title, rating, len, count, album_id, genre_id) values ('Who Made Who', 5, 207, 0, 1, 2)
- 71. Using Join Across Tables http://en.wikipedia.org/wiki/Join_(SQL)
- 72. Relational Power • By removing the replicated data and replacing it with references to a single copy of each bit of data we build a “web” of information that the relational database can read through very quickly - even for very large amounts of data • Often when you want some data it comes from a number of tables linked by these foreign keys
- 73. The JOIN Operation • The JOIN operation links across several tables as part of a select operation • You must tell the JOIN how to use the keys that make the connection between the tables using an ON clause
- 74. select Album.title, Artist.name from Album join Artist on Album.artist_id = Artist.id What we want to see The tables that hold the data How the tables are linked Artist Album
- 75. select Album.title, Album.artist_id, Artist.id,Artist.name from Album join Artist on Album.artist_id = Artist.id
- 76. SELECT Track.title, Track.genre_id, Genre.id, Genre.name FROM Track JOIN Genre Joining two tables without an ON clause gives all possible combinations of rows.
- 77. select Track.title, Genre.name from Track join Genre on Track.genre_id = Genre.id What we want to see The tables that hold the data How the tables are linked
- 78. select Track.title, Artist.name, Album.title, Genre.name from Track join Genre join Album join Artist on Track.genre_id = Genre.id and Track.album_id = Album.id and Album.artist_id = Artist.id What we want to see The tables which hold the data How the tables are linked
- 80. Many-To-Many Relationships https://en.wikipedia.org/wiki/Many-to-many_(data_model)
- 81. Album belongs-to Album id title Track id title rating len count album_id Table Primary key Logical key Foreign key Track Len Rating Count Title Many One https://en.wikipedia.org/wiki/One-to-many_(data_model) Review: One to Many Many One
- 83. Many to Many • Sometimes we need to model a relationship that is many-to-many • We need to add a "connection" table with two foreign keys • There is usually no separate primary key https://en.wikipedia.org/wiki/Many-to-many_(data_model)
- 85. Start with a Fresh Database CREATE TABLE User ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, name TEXT UNIQUE, email TEXT ) CREATE TABLE Course ( id INTEGER NOT NULL PRIMARY KEY AUTOINCREMENT UNIQUE, title TEXT UNIQUE ) CREATE TABLE Member ( user_id INTEGER, course_id INTEGER, role INTEGER, PRIMARY KEY (user_id, course_id) )
- 87. Insert Users and Courses INSERT INTO User (name, email) VALUES ('Jane', 'jane@tsugi.org'); INSERT INTO User (name, email) VALUES ('Ed', 'ed@tsugi.org'); INSERT INTO User (name, email) VALUES ('Sue', 'sue@tsugi.org'); INSERT INTO Course (title) VALUES ('Python'); INSERT INTO Course (title) VALUES ('SQL'); INSERT INTO Course (title) VALUES ('PHP');
- 89. INSERT INTO Member (user_id, course_id, role) VALUES (1, 1, 1); INSERT INTO Member (user_id, course_id, role) VALUES (2, 1, 0); INSERT INTO Member (user_id, course_id, role) VALUES (3, 1, 0); INSERT INTO Member (user_id, course_id, role) VALUES (1, 2, 0); INSERT INTO Member (user_id, course_id, role) VALUES (2, 2, 1); INSERT INTO Member (user_id, course_id, role) VALUES (2, 3, 1); INSERT INTO Member (user_id, course_id, role) VALUES (3, 3, 0);
- 91. SELECT User.name, Member.role, Course.title FROM User JOIN Member JOIN Course ON Member.user_id = User.id AND Member.course_id = Course.id ORDER BY Course.title, Member.role DESC, User.name
- 92. www.tsugi.org
- 93. Complexity Enables Speed • Complexity makes speed possible and allows you to get very fast results as the data size grows • By normalizing the data and linking it with integer keys, the overall amount of data which the relational database must scan is far lower than if the data were simply flattened out • It might seem like a tradeoff - spend some time designing your database so it continues to be fast when your application is a success
- 94. Additional SQL Topics • Indexes improve access performance for things like string fields • Constraints on data - (cannot be NULL, etc..) • Transactions - allow SQL operations to be grouped and done as a unit
- 95. Summary • Relational databases allow us to scale to very large amounts of data • The key is to have one copy of any data element and use relations and joins to link the data to multiple places • This greatly reduces the amount of data which much be scanned when doing complex operations across large amounts of data • Database and SQL design is a bit of an art form
- 96. Acknowledgements / Contributions These slides are Copyright 2010- Charles R. Severance (www.dr- chuck.com) of the University of Michigan School of Information and open.umich.edu and made available under a Creative Commons Attribution 4.0 License. Please maintain this last slide in all copies of the document to comply with the attribution requirements of the license. If you make a change, feel free to add your name and organization to the list of contributors on this page as you republish the materials. Initial Development: Charles Severance, University of Michigan School of Information … Insert new Contributors here ...