CSC220 Database Management Systems

--D. Thiebaut 12:08, 6 October 2010 (UTC)

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Main Reference

• The information here is taken from Chapter 1 (required reading) of Garcia-Molina, Ullman and Widom's Database Systems: the Complete Book. Their Chapter 2, which is also online, is great reading.

Important Concepts

• DBMS = database management system

Definition

A DBMS is a tool for creating and managing large amounts of data efficiently and allowing it to persist over long periods of time, safely.

• 1970: seminal paper by Ted Codd, where proposition is that DBMS users should see the data as tables, called relations

• ==> Relational database systems

• SQL = Structured Query Language

• 1990: relational database systems are the norm

• today: DBMS have evolved to new forms (cloud).

• example of large databases:
  • Google
  • Satellite data
  • Social Networks (Facebook)
  • YouTube videos

• Two kinds of users of a DBMS: Admin and Users

• • Admin create/modify organization of the data (table size, data size, constraints on the data values) = Schema of the database.
  • Users query the DB to lookup, search, insert new data, or delete new data. The result (SQL) is presented in the form of temporary tables.

Concepts of Transcation and Query

A transaction is a group of queries (possibly just one) that should operate atomically and in isolation from one another. A complete transaction should be durable. This means that logging and recovery processes are an integral part of a DBMS.

• DBMS = { data, metadata, logs, statistics, indexes + data-structures }

• Measure of Goodness: ACID properties of a transaction

A

atomicity = all-or-nothing

C

consistency: some data cannot be negative, for example ==> The DBMS must ensure data consistency after the execution of a transaction.

I

Isolation: the transactions should appear to operate as if no other transactions are/were operating at the same time.

D

durability: Once the transaction has exected, the effect of this transaction on the data must never be lost.

• MySql is in partial compliance of ACID when using the default myIsam storage engine. InnoDB, BDB, and cluster storage engines, which are also available with MySql provide ACID compliance, but with performance degredation.

Example

• Users, purchasing items from a store.
• 3 tables: users, orders, items

Create Tables

CREATE TABLE `users` (
 `userId` INT(1) NOT NULL AUTO_INCREMENT,
 `userName` VARCHAR(100) DEFAULT NULL,
 PRIMARY KEY  (`userId`)
) ENGINE=MYISAM DEFAULT CHARSET=utf8;


CREATE TABLE `orders` (
 `orderId` INT(1) NOT NULL AUTO_INCREMENT,
 `userId` INT(1) DEFAULT NULL,
 `itemId` INT(1) DEFAULT NULL,
 PRIMARY KEY  (`orderId`)
) ENGINE=MYISAM DEFAULT CHARSET=utf8;


CREATE TABLE `items` (
 `itemId` INT(1) NOT NULL AUTO_INCREMENT,
 `itemName` VARCHAR(100) DEFAULT NULL,
 `price` FLOAT DEFAULT NULL,
 PRIMARY KEY  (`itemId`)
) ENGINE=MYISAM DEFAULT CHARSET=utf8;

Insert Data

• Add 5 users to the database (Marie, John, Manon, Rob, Elaine)

INSERT INTO `users`(`userId`,`userName`) VALUES ( NULL,'Marie');
INSERT INTO `users`(`userId`,`userName`) VALUES ( NULL,'John');
INSERT INTO `users`(`userId`,`userName`) VALUES ( NULL,'Manon');
INSERT INTO `users`(`userId`,`userName`) VALUES ( NULL,'Rob');
INSERT INTO `users`(`userId`,`userName`) VALUES ( NULL,'Elaine');

• Add 6 items and their price (pencil, eraser, paper, ink, ruler, markers)

INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'pencil','1');
INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'erase','0.5');
UPDATE `items` SET `itemId`='2',`itemName`='eraser',`price`='0.5' WHERE `itemId`='2';
INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'paper','5');
INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'ink','30');
INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'ruler','1.5');
INSERT INTO `items`(`itemId`,`itemName`,`price`) VALUES ( NULL,'markers','2.5');

• Create some user orders of items. e.g. Marie buys a pencil, an eraser, paper, and ink.

INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'1','1');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'1','2');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'1','3');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'1','4');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'2','1');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'3','1');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'3','4');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'5','4');
INSERT INTO `orders`(`orderId`,`userId`,`itemId`) VALUES ( NULL,'5','3');

Table-related operations

• to delete a table: "DROP TABLE"
• to erase a table without deleting it: "TRUNCATE TABLE"

Some queries

SELECT * FROM `items`;

SELECT `itemName` FROM `items`;

SELECT `itemName` FROM `items`WHERE `itemId`=2;

SELECT * FROM `users` ORDER BY `userName` ASC;

SELECT * FROM `orders` WHERE `userId`=1;

SELECT `itemName` FROM `items` WHERE `itemId` IN ( 1, 2, 3 );

SELECT `itemName` FROM `items` WHERE `itemId` IN ( SELECT `itemId` FROM `orders` WHERE `userId`=1 );

SELECT `itemName` FROM `items` WHERE `itemId` IN ( 
            SELECT `itemId` FROM `orders` WHERE `userId` IN  ( 
                         SELECT `userId` FROM `users` WHERE `userName`='Marie') );

Anatomy of a Query

Command	Description
CREATE DATABASE	Creates a new database
CREATE INDEX	Creates a new index on a table column
CREATE SEQUENCE	Creates a new sequence in an existing database
CREATE TABLE	Creates a new table in an existing database
CREATE TRIGGER	Creates a new trigger definition
CREATE VIEW	Creates a new view on an existing table
SELECT	Retrieves records from a table
INSERT	Adds one or more new records into a table
UPDATE	Modifies the data in existing table records
DELETE	Removes existing records from a table
DROP DATABASE	Destroys an existing database
DROP INDEX	Removes a column index from an existing table
DROP SEQUENCE	Destroys an existing sequence generator
DROP TABLE	Destroys an existing table
DROP TRIGGER	Destroys an existing trigger definition
DROP VIEW	Destroys an existing table view
CREATE USER	Adds a new PostgreSQL user account to the system
ALTER USER	Modifies an existing PostgreSQL user account
DROP USER	Removes an existing PostgreSQL user account
GRANT	Grant rights on a database object to a user
REVOKE	Deny rights on a database object from a user
CREATE FUNCTION	Creates a new SQL function within a database
CREATE LANGUAGE	Creates a new language definition within a database
CREATE OPERATOR	Creates a new SQL operator within a database
CREATE TYPE	Creates a new SQL data type within a database

MySQL Server

• Each client is associated a thread per connection
• Each thread runs on 1 core only
• Cache contains SELECT queries and their result
• Parser generates a parse tree
• Storage engines include MyIsam and InnoDB

File System for myIsam Engine

• 1 database = 1 folder
• 1 table = 2 files: data + index
• located on /usr/local/mysql/data on xgridmac

• DEMO
  • Show where files are located.
  • show index files
  • show log files
  • Show how to export databases

• largest database table limited by file size: unlimited on Linux. http://en.wikipedia.org/wiki/Comparison_of_file_systems#Limits
• files are platform independent (can be copied!)
• tables can be compressed (for read-only operations, s.a. CD-ROM)

Transactions

• Under MyIsam, a query is a transaction.

Exercises

• Exercise Page

Views

• Use the Dept, Class, Enrollment tables (in 220a_example4 db) as example
• Create a view that shows all dept classes and their enrollment

Step 1

  create view totalEnroll as select * from `Dept` join `Course` on `Dept`.`Id`=`Course`.`deptId` 
           join Enrollment on `Course`.`Id`=`Enrollment`.`Id`

Generates an error on duplicate Id... ==> replace * with the actual list of fields wanted:

Step 2

specify fields

  create view totalEnroll as select `Course`.`Id`, `Dept`.`Name`, `Course`.`Name`, 
         `Enrollment`.`Count` from `Dept` join `Course` on `Dept`.`Id`=`Course`.`deptId` 
         join Enrollment on `Course`.`Id`=`Enrollment`.`Id`

Generates another error on duplicate field name `Name` (it keeps the name of the field, not the name of the table) ==> use aliases

Step 3

use aliases

  create view totalEnroll as select `Course`.`Id`, `Dept`.`Name` as `DName`, `Course`.`Name` as `CName`, 
         `Enrollment`.`Count` from `Dept` join `Course` on `Dept`.`Id`=`Course`.`deptId` 
         join Enrollment on `Course`.`Id`=`Enrollment`.`Id`

Step 4

create new aggregate fields:

  create view totalEnroll as select `Course`.`Id`, `Dept`.`Name` as `DName`, `Course`.`Name` as `CName`, 
         concat( `Dept`.`Name`, `Course`.`Name` ) as `DCName`, `Enrollment`.`Count` from `Dept` 
         join `Course` on `Dept`.`Id`=`Course`.`deptId` 
         join Enrollment on `Course`.`Id`=`Enrollment`.`Id`

 

Rules on Views

• Technically, Create View statements may not contain "ORDER BY" clause (although MySQL ignores it). If one selects from a view that contains an ORDER BY with a query that contains its own ORDER BY, the view's ORDER BY is ignored.

• The select query used to create a view cannot contain subqueries in its FROM clause

• The table used in a view must exist when the view is created

Index

• First difference between PRIMARY KEY and INDEX. A primary key is a logical entity regarding records in a table. It usually is implemented as a UNIQUE INDEX. An INDEX can be unique or not and speeds up access to a specific field in the table.

• Indexes are implemented as B-Trees, see http://www.bluerwhite.org/btree/ for review

Example

• Use database 220a_example5
• Use this program to create it table user with a million entries: fillTable.php
• Look at the table `users` (verify it doesn't have any indexes)
• Record its size
• Perform some queries and check the execution time

SELECT * FROM `users` order by `Name` limit 10         (0.69 sec)

SELECT * FROM `users` order by `Qty` limit 10            (twice as fast as previous one, why?)

SELECT * FROM `users` where 100 < `Qty` and `Qty`<10000        (0.3sec)

SELECT COUNT(*) FROM `users` where "2" < `Name` and `Name`< "3"     

• Now create an Index on `Name` and on `Qty`
  • Look at Structure, add index (non unique)
  • Why is it spending so long?
• Check size of table
• Redo same queries as above and check e

References

• Anatomy of a SQL query
• Joins
  • Joining tables
• Indexes
  • Creating an Index
  • How MySQL uses Indexes
  • B-Trees (used for indexes)
• Views
  • Creating a View
  • Using a View