lecture plan

Jane Reid, BSc/IT DB, QMUL, 28/1/02

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Lecture plan

• Oracle architecture

• SQL– Data definition– Queries– Insert, delete and update


2

Oracle

• Relational database– Each table column is independent and

identified by name– Ordering of rows is unimportant– All operations should be relational, i.e. generate

new relations from old ones– System supports at least one JOIN operation

• Based on a client-server architecture


3

Oracle architecture

• Oracle server consists of:– Database (raw data)

• Logical structure = database schema

• Physical structure = file structure

– Instance (processes and system memory)


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Logical database structure

• Organised into:– Tablespaces– Schemas– Data blocks– Extents– Segments


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Tablespaces

• Group related logical structures together

• SYSTEM tablespace created automatically– Holds the data dictionary

• Meta-data in machine-readable format

• Includes security information, schema object information, space allocation, etc

• May also have one or more user tablespaces

• Each table belongs to a specific tablespace


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Schemas

• A named collection of schema objects associated with a particular user

• Equivalent to a user’s personal space

• Created automatically when a user account is set up


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Data blocks

• Corresponds to a specific number of bytes of disk space

• Size can be set for each database at creation


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Extents

• Specific number of contiguous data blocks allocated for storing a specific type of information


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Segments

• A set of extents allocated for a certain logical structure

• Oracle dynamically allocates extents to segments as existing extents fill up


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Physical database structure

• Consists of:– Datafiles (e.g. table and index data)

• One or more datafiles form a tablespace

– Redo log files (usually multiplexed)• Record all changes made to the data

• Used in recovery

– Control files (usually multiplexed)• Contain a list of all other files in the database


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Oracle instance

• Consists of:– Processes

• User processes

• Oracle processes

– Shared memory used by processes


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User processes

• Manipulate the user’s input

• Communicate with the Oracle server process

• Display the information requested by the user


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Oracle processes

• Perform functions for users:– Server processes handle requests from

connected user processes– Background processes perform asynchronous

I/O and provide increased parallelism


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Shared memory [1]

• Used for caching data, indexes and storing shared program code

• Organised into memory structures of a fixed size created on instance startup:– System global area (SGA)

• Used to store data and control information for one Oracle instance

• Holds database buffer cache, redo log buffer and shared pool


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Shared memory [2]

– Program global area• Used to store data and control information for the

Oracle server processes


16

SQL

• Standard for commercial relational DBs

• High-level declarative language interface– User specifies what the result should be– Optimisation and query execution decisions left

to DBMS

• Based on tuple relational calculus, with some relational algebra features


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SQL versions

• Standard version accepted by ANSI / ISO

• Current version is SQL3– Not all relational DBMSs support SQL3 (may

support SQL-92, i.e. version 2)– Contains some object-oriented features


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SQL in Oracle

• Oracle’s own version of SQL - SQLPlus– DDL and DML statements– View definition– Security and authorisation specification– Definition of integrity constraints– Transaction control specification– Session and system control statements– Embedding SQL into programming languages


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Data definition

• Objects– Table

• Commands– CREATE– ALTER– DROP


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Tables in SQL [1]

• Created by CREATE TABLE statement

CREATE TABLE EMPLOYEE

• Known as base tables

• Attributes ordered by creation order

• Rows not ordered


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Tables in SQL [2]

• CREATE TABLE specifies new relation by– Relation name– Attributes

• Name

• Data type

• Attribute constraints


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Tables in SQL [3]

• Key/entity/referential integrity constraints– Can be specified in CREATE TABLE– Can be added later using ALTER TABLE

• Table can be deleted by DROP TABLE statement


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Data types [1]

• Numeric– Integer: INTEGER– Real: FLOAT

• Character-string– Fixed length: CHAR(n)– Varying length: VARCHAR(n) / VARCHAR2

(n)


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Data types [2]

• DATE– Has main components YEAR, MONTH, DAY– Also stores century, hour, minute, second– Has format DD-MON-YYYY

E.g. 05-FEB-2001


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Domains

• Like a type declaration

• Advantages– Easier to change data type– Improves schema readability– Can have optional default specification

CREATE DOMAIN SSN_TYPE AS CHAR(9);


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Attribute constraints

• Specified by CONSTRAINT

• Example constraint: NOT NULL– Should always be specified for primary keys

• Constraint may be given optional name– Specified by CONSTRAINT <name>– Must be unique within a schema


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Default values

• Specified by DEFAULT <value>

• Used if no explicit value assigned to attribute

• NULL unless otherwise stated


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Table constraints [1]

• PRIMARY KEY

• UNIQUE (secondary key)

• FOREIGN KEY (referential integrity)– Referential integrity constraints can be violated

by• Insertion or deletion of tuples

• Foreign key value modified


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Table constraints [2]

– Referential triggered action• Can be added to foreign key constraint to cause

automatic update ON DELETE

• Options are SET NULL, CASCADE and SET DEFAULT


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DROP TABLE

• Option– CASCADE CONSTRAINTS

DROP TABLE DEPENDENT CASCADE CONSTRAINTS;


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ALTER TABLE [1]

• Command which allows– Adding column

ALTER TABLE EMPLOYEE ADD JOB VARCHAR(12);

– Dropping column

ALTER TABLE EMPLOYEE DROP ADDRESS CASCADE;


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ALTER TABLE [2]

– Changing column definition (add/drop default)

ALTER TABLE DEPARTMENT ALTER MGRSSN

DROP DEFAULT;

ALTER TABLE DEPARTMENT ALTER MGRSSN

SET DEFAULT ‘11111111’;


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ALTER TABLE [3]

– Adding / dropping table constraints

ALTER TABLE EMPLOYEE DROP CONSTRAINT EMPSUPERFK CASCADE;

ALTER TABLE EMPLOYEE ADD CONSTRAINT EMPSUPERFK;

FOREIGN KEY(SUPERSSN) REFERENCES EMPLOYEE(SSN)

ON DELETE SET NULL;


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Queries

• SQL allows two or more identical tuples in a relation

• Table is thus a multi-set / bag of tuples

• Table can be constrained to be a set by– Use of a key constraint– DISTINCT option


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SELECT statement [1]

• Basic syntax is

SELECT <attribute list>

FROM <table list>

WHERE <condition>


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• Example - query 0

• Similar effect to relational algebra SELECT-PROJECT combination– SELECT clause specifies projection attributes– WHERE clause specifies selection condition– SQL may retrieve duplicate tuples, however


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• Similar effect to relational algebra SELECT-PROJECT-JOIN combination– SELECT clause specifies projection attributes– WHERE clause specifies selection condition– Condition DNUMBER = DNO is join condition


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• Multiple select and join conditions possible


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Ambiguous attribute names

• Attributes with same name in different relations– Names must be qualified with relation name

• Example - query 1A


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Aliasing [1]

• Queries can refer to same relation twice– One-level recursive query– Not possible to have infinitely recursive query

• Aliases / tuple variables can be declared



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Aliasing [2]

• Also possible to rename relation attributes

EMPLOYEE AS E (FN, MI, LN, SSN, BD, ADDR, SEX, SAL, SSSN, DNO)

• This ‘shorthand’ can be used in any query

• Example - query 1B


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No WHERE clause

• No condition on tuple selection


• More than one relation in FROM clause means cross product


• Similar to relational algebra cross product - PROJECT combination


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Use of asterisk

• Used to retrieve all attribute values in SELECT clause

• Examples - queries 1C, 1D, 10A


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Tables as sets [1]

• Duplicate elimination not automatic– Expensive– Sometimes unnecessary or unwise– Not suitable for use with aggregate functions– Can be achieved by DISTINCT in SELECT

clause

• Example - queries 11, 11A


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Tables as sets [2]

• Set union (UNION) and other set operations sometimes available, e.g. EXCEPT, CONTAINS, but are non-standard

• Example - queries 3, 4


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Substring comparison

• Uses LIKE comparison operator

• % replaces any number of characters

• _ replaces a single character

• Examples - queries 12, 12A


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Arithmetic operators

• Standard arithmetic operators can be applied



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Other operators

• String concatenation ||

• Numeric value range BETWEEN


• Ordering by value of one or more attributes



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Nested queries [1]

• Complete SELECT-FROM-WHERE block inside WHERE of outer query

• Ambiguity among attributes of same name– Assumed they belong to relation in innermost

nested query

• Correlated queries– Condition in inner WHERE references “outer”

attribute


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Nested queries [2]

• Queries with nested SELECT-FROM-WHERE blocks using IN can usually be expressed as single block query

• Example - query 4A


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Set comparison [1]

• Comparison operator IN / NOT IN can compare– Value with multi-set of values– Tuple of values with multi-set of union-

compatible tuples


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Set comparison [2]

SELECT DISTINCT ESSN

FROM WORKS_ON

WHERE (PNO, HOURS) IN (SELECT PNO, HOURS

FROM WORKS_ON

WHERE SSN = ‘123456789’);


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Other comparison operators

• >, >=, <, <=, <>

• Can be used with ANY, SOME, ALL

SELECT LNAME, FNAME

FROM EMPLOYEE

WHERE SALARY > ALL (SELECT SALARY

FROM EMPLOYEEWHERE DNO = 5);


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Functions in SQL

• EXISTS / NOT EXISTS– Evaluates to Boolean value– Indicates if result of a correlated, nested query

is empty– Example - queries 16B, 6, 7

• UNIQUE– Evaluates to Boolean value– Indicates if there are duplicate tuples


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WHERE clause variations

• Explicit set of values


• Use of NULL– Used with IS / IS NOT– Equality comparison (=) not appropriate



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Aggregate functions

• Built-in functions– COUNT– SUM– MAX– MIN– AVG

• Example - queries 19, 20, 21, 22, 23, 5


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GROUP BY clause

• Group tuples with same value for an attribute– E.g. for averaging across categories of tuples

(rather than across all tuples)

• Example - query 24, 25


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HAVING clause

• Places condition on selection of tuple groups specified by GROUP BY clause

• Example - queries 26, 28


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Summary of SQL queries [1]

SELECT <attribute and function list>

FROM <table list>

[WHERE <condition>]

[GROUP BY <grouping attribute(s)>]

[HAVING <group condition>]

[ORDER BY <attribute list>]


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Summary of SQL queries [2]

• Order of conceptual evaluation– FROM clause– WHERE clause– GROUP BY clause– HAVING clause– ORDER BY clause– SELECT clause


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INSERT [1]

• Possible to insert– Single tuple– Multiple tuples

• Specify– Relation name– List of values for the tuple

• In same order as attributes specified

• Example - update 1


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INSERT [2]

• Can specify limited subset of attributes– Must include all NOT NULL / non-default ones

• Example - update 1A

• DBMS may not enforce all integrity constraints– User must enforce the others

• Examples - updates 2, 2A


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DELETE

• Possible to delete– Single tuple– Multiple tuples

• Tuples in other tables may be deleted by referential triggered action

• Includes WHERE clause

• Examples - updates 4A, 4B, 4C


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UPDATE [1]

• Possible to modify attribute values of– Single tuple– Multiple tuples

• Tuples in other tables may be modified by referential triggered action


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UPDATE [2]

• Includes– WHERE clause– SET clause, which specifies

• Attributes to be modified

• New attribute values (NULL / DEFAULT possible)

• Example - updates 6, 5


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Views

• Simplifies query specification

• Always up-to-date

• Virtual tables derived from defining tables– Other virtual table(s)– Base tables(s)


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Creating views

• View definition includes– Name– List of attribute names– Query to specify contents

• Created using CREATE VIEW

• Examples - view 1, 2


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Querying and deleting views

• SQL queries can be specified on views

• Example - query view 1

• Deleted using DROP VIEW

• Example - view 1A


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Updating views [1]

• View update often ambiguous– DBMS may choose best option– User may be asked to specify preferred options

during view definition

• Example - update view 1


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Updating views [2]

• View with single defining table is updatable if view attributes contain primary key

• Not possible to update– View defined on multiple queries using joins– View defined using grouping / aggregate

functions


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Assertions [1]

• More general constraints can be specified via declarative assertions

• Created using CREATE ASSERTION

• Deleted using DROP ASSERTION


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Assertions [2]

CREATE ASSERTION SALARY_CONSTRAINT

CHECK (NOT EXISTS (SELECT * FROM EMPLOYEE E, EMPLOYEE M, DEPARTMENT D

WHERE E.SALARY > M.SALARY AND

E.DNO = D.DNUMBER AND

D.MGRSSN = M.SSN) );

• CHECK clause can be used with CREATE DOMAIN statement

CREATE DOMAIN D_NUM AS INTEGER

CHECK (D_NUM > 0 AND D_NUM < 21);

lecture plan

Documents

control information

data dictionarymetadata

caching data

memory structures

version of sql

schema object information

oracle server processdisplay

system control statementsem