Extending Relational Databases

Extending Relational Databases

Toon Calders

[email protected]

Last Lectures

• Relational query languages are limited• Transitive closure cannot be expressed

• Gaifman-locality

• Also w.r.t. data storage relational model is limited• Simple data

• No set types, arrays, …

This lecture

• Extending SQL• Recursion

• Nested relations

• Object-oriented and object-relational database systems

Recursion in SQL

• SQL:1999 permits recursive view definition• Example: find all employee-manager pairs, where

the employee reports to the manager directly or indirectly (that is manager’s manager, manager’s manager’s manager, etc.)

This example view, empl, is called the transitive closure of the manager relation

Recursion in SQL

with recursive empl (employee_name, manager_name ) as (select employee_name, manager_name from manager union select manager.employee_name,

empl.manager_name from manager, empl where manager.manager_name =

empl.employee_name ) select * from empl

This lecture

• Extending SQL• Recursion



Nested Relations

• Very simple example:• Class book

− set of authors

− title

− set of keywords

Extremely simple to model in any programming language

Hard in relational database!

Nested Relations

• Either we ignore the multivalued dependencies

• This table is in 3NF, BCNF

Title Author Keyword

Database System Concepts Silberschatz Database

Database System Concepts Korth Database

Database System Concepts Sudarshan Database

Database System Concepts Silberschatz Storage

Database System Concepts Korth Storage

Database System Concepts Sudarshan Storage

Nested Relations

• Or we go to 4NF

Title Author

Database System Concepts Silberschatz

Database System Concepts Korth

Database System Concepts Sudarshan

Title Keyword

Database System Concepts Database

Database System Concepts Storage

Nested Relations

• 4NF design requires users to include joins in their queries.

• 1NF relational view• eliminates the need for users to perform joins,

• but loses the one-to-one correspondence between tuples and objects.

• has a large amount of redundancy

Nested Relational Algebra

• Types:• Set of constants C = {c1,c2, …}

• If T1, …, Tk are types, then also {(T1,…,Tk)}

• Domain:• Dom(C) = {c1,c2, …}

• Dom ( {(T1,…,Tk)} ) = P( { (x1,…,xk) | xi Ti, 1 ≤ i ≤ k} )


• Example:• C = {1,2,3,…}

• Type { (C, { ( C, { (C) } ) } ) } has domain:

− {(C)} { {}, {(1)}, {(2)}, {(1),(2)}, ... } Set of natural numbers

− { ( C, { (C) } ) } Set of pairs (c,S), c is a number,

S a set of numbers

− All Set of pairs (c,T), T is set of pairs

(c,S)


• Nested relation of type (T1,…,Tn)

• Subset of Dom( {(T1,…,Tn)} ).

• Nested relational algebra• The usual operators , , , -, ,• Also Nest and Unnest:

− U$i (R): remove nesting from ith column of R

− N$i1, …$ik (R): nest columns $i1 … $ik


R = { ( a, b ),

( a, c ),

( d, b ),

( d, c ) }

N$2 R ={ ( a, {b,c} ),

( d, {b,c} ) }

U$2 (N$2 R) produces again original R

Flat-Flat Theorem

• Let Q be a nested-relational algebra expression• Q takes a non-nested relation as input• Q produced a non-nested relation as output• Type (C,…,C) (C,…,C)

• Then:• Q can be rewritten as a normal relational algebra

expression; (i.e., one without nesting)

• Result is actually stronger:• Nested d deep nested d’ deep: no need for intermediate

results having depth > d, d’

Flat-Flat Theorem

• Importance?• Can be used by query optimizers

No need to introduce intermediate nesting Standard techniques can be used

Nesting in SQL

• Nesting is the opposite of unnesting, creating a collection-valued attribute

• Many commercial database systems support nesting in one way or another• NOTE: SQL:1999 does not support nesting

• Nesting can be done in a manner similar to aggregation, but using the function set() in place of an aggregation operation, to create a set

Nesting in SQL

select title, author, pub_name, pub_branch, set(keyword) as keyword-list

from flat-booksgroupby title, author, pub_name, pub_branch

select title, set(author) as author-list, pub_name, pub_branch, set(keyword) as keyword-listfrom flat-booksgroupby title, pub_name, pub_branch,

Nesting (Cont.)

• Another approach to creating nested relations is to use subqueries in the select clause.

select title, ( select author from flat-books as M where M.title=O.title) as author-set, pub-name, pub-branch, (select keyword from flat-books as N where N.title = O.title) as keyword-set

from flat-books as O

This lecture

• Extensions to SQL• Recursion

• Enumeration types



Motivation for OO Databases

• Many applications require the storage and manipulation of complex data• design databases

• geometric databases

• …

• Object-Oriented programming languages manipulate complex objects• classes, methods, inheritance, polymorphism


• In many applications persistency of the data is nevertheless required• protection against system failure

• consistency of the data

• Mapping: object in OO language tuples of atomic values in relational database is often problematic

• Impedance mismatch


• Need for object-oriented features in databases• Object-Oriented Databases

• Object-Relational Databases

• Need for more powerful data manipulation• Extend expressive power of SQL; include functions,

recursion


• Often we want to manipulate the data in the database itself• no data transmission costs

• client has limited computation power

• Expressive power of SQL is quite limited• allows for efficient query optimization

• disallows complex data operations


• Whole spectrum:

Relational Object Persistent OO

Database Relational Programming

Database Language

Complex Types and SQL:1999

• Extensions to SQL to support complex types include:• Collection and large object types

− Nested relations are an example of collection types

• Structured types− Nested record structures like composite

attributes • Inheritance• Object orientation

− Including object identifiers and references

Structured Types and Inheritance in SQL

• Structured types can be declared and used in SQL

create type Name as (firstname varchar(20), lastname varchar(20))

finalcreate type Address as (street varchar(20), city varchar(20), zipcode varchar(20))

not final

• Note: final and not final indicate whether subtypes can be created

Structured Types and Inheritance in SQL

• Structured types can be used to create tables with composite attributes

create table customer (name Name,address Address,dateOfBirth date

)

• Dot notation used to reference components: Name.firstname

Methods

• Can add a method declaration with a structured type.

method ageOnDate (onDate date)

returns interval year

• Method body is given separately.create instance method ageOnDate (onDate date)

returns interval year

for CustomerType

begin

return onDate - self.dateOfBirth;

end

Inheritance

• Suppose that we have the following type definition for people:

create type Person (name varchar(20),

address varchar(20))• Using inheritance to define the student and

teacher types create type Student under Person (degree varchar(20), department varchar(20)) create type Teacher under Person (salary integer, department varchar(20))

Object-Identity and Reference Types

• Define a type Department with a field name and a field head which is a reference to the type Person, with table people as scope:

create type Department ( name varchar (20), head ref (Person) scope people)

• We can then create a table departments as follows

create table departments of Department

Persistent Programming Languages

• Languages extended with constructs to handle persistent data

• Programmer can manipulate persistent data directly• no need to fetch it into memory and store it back to disk

(unlike embedded SQL)

• Persistent objects:• by class - explicit declaration of persistence• by creation - special syntax to create persistent objects• by marking - make objects persistent after creation • by reachability - object is persistent if it is declared explicitly

to be so or is reachable from a persistent object

Object Identity and Pointers

• Degrees of permanence of object identity• Intraprocedure: only during execution of a single

procedure

• Intraprogram: only during execution of a single program or query

• Interprogram: across program executions, but not if data-storage format on disk changes

• Persistent: interprogram, plus persistent across data reorganizations

Object Identity and Pointers

• Persistent versions of C++ and Java have been implemented• C++

− ODMG C++

− ObjectStore

• Java

− Java Database Objects (JDO)

Comparison of O-O and O-R Databases

• Relational systems• simple data types, powerful query languages, high

protection.

• Persistent-programming-language-based OODBs• complex data types, integration with programming

language, high performance.

• Object-relational systems• complex data types, powerful query languages, high

protection.

• Note: Many real systems blur these boundaries• E.g. persistent programming language built as a wrapper on

a relational database offers first two benefits, but may have poor performance.

Self-Study

• Read Chapter 9 of the book “Database System Concepts, 5th edition”.• Corresponds roughly to Chapters 8 and 9 of the 4th

edition, except the parts on ODMG (sections 8.5.1 and 8.5.2) which are not present in the 5th edition anymore.

• During the lecture of next Friday 20/02/09 there will be time for questions and answers regarding the topics covered in this book chapter.

Extending Relational Databases

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