OODBS

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Chapter III

Object-Oriented DatabaseSystems

Nguyen Kim AnhDept. of Information Systems, SoICT, HUT

Outline

Object-Oriented Data Model Object-Oriented Database System(OODBS) Object-Oriented Data Definition Language Object-Oriented Query Language Index organizations for OODBS Query Optimization in OODBS

Object-Oriented Data Model

Definition of an object Object Identity Object Structure Object-Oriented Concepts Graphical representation of a complex object Comparisons of the states of two objects for equality Class Schema

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Definition of an object

Objects User defined complex data typesAn object has structure or state (variables) and methods(behavior/operations)

An object is described by four characteristicsIdentifier: a system-wide unique id for an objectName: an object may also have a unique name in DB (optional)Lifetime: determines if the object is persistent or transientStructure: Construction of objects using type constructors

Object Identity

unique identity for each independentobject stored in the database

created by a unique, system-generatedobject identifier, or OID

Object Identity

properties of OID

immutable: the OID value of a particular objectshould not change

Each OID is used only once.

OID should not depend on any physical addressattribute values of the object

Most OO database systems allow for the representation ofboth objects and values (having no OIDs)

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Object Structure

The state (current value) of a complex object may beconstructed from other objects (or other values) byusing certain type constructors

Can be represented by (i,c,v)i is an unique idc is a type constructorv is the object state

Type constructorsBasic types: atom (integer,real,string,Boolean,)Structured type: tupleCollection type: array vs. list (order), set vs.bag (unorder)

Object Structure

Object statesc=atom ::: an atomic value from the domainc=set ::: a set of object identifiers {i1, i2, , in}c=tuple ::: a tuple of c=list ::: an ordered list [i1, i2, , in]c=array ::: a single-dimensional array of objectidentifiersc=bag

Object-Oriented Concepts

Abstract Data TypesClass definition provides extension to complexattribute types

EncapsulationImplementation of operations and objectstructure hidden

InheritanceSharing of data within hierarchy scope, supportscode reusability

Polymorphism Operator overloading

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o8=(i8, tuple, ) :::department 5

o9=(i9, tuple, )

o10=(i10 ,set,{i 12 , i13 , i14}) o11 =(i11 ,set,{i 15 , i16 , i17})

Example 1: Complex Object

Graphical representation ofa complex object

LEGEND: object

tuple

set

NAME NUMBER MANAGER LOCATIONS MEMBERS CONTROL

MANAGER MANAGERSTRATDATE

O5 O4 O9 O7 O10 O11

O8

O1 O2 O3

Houston Bellaire Sugarland

i8:tuple

i5:atom

i4:atom

i9:tuple

i7:set

i10:set

i11:set

i15: .....tuple

i16: .....tuple

i17: .....tuple

i12: .....tuple

i13: .....tuple

i14: .....tuple

i6:atom

O6

1988-05-22

V4V9

V5V7

V10V11

V1 V2 V3

V6

Research 5

Object instance of department type

Comparisons of the states oftwo objects for equality

identical states (deep equality) the graphs representing their states are

identical in every respect, including the OIDs atevery level

equal states (shallow equality) the graph structures must be the same all the corresponding atomic values in the

graphs should be the same allow some corresponding internal nodes in

the two graphs to have objects with different OIDs

(Current Values)

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Example 2:Identical vs. Equal Object States

o1=(i1, tuple, )o2=(i2, tuple, )o3=(i3, tuple, )o4=(i4, atom, 10)o5=(i5, atom, 10)o6=(i6, atom, 20)

o1 and o 2 have equal states o1 and o 3 have identical states o4 and o 5 have identical states o4 and o 5 are equal but not identical

Class Schema

Outline


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Object-Oriented DatabaseSystem (OODBS)

A database system that incorporates allthe important object-oriented concepts

Some additional featuresUnique Object identifiersPersistent object handling

Advantages of OODBS

Designer can specify the structure ofobjects and their behavior (methods)

Better interaction with object-orientedlanguages such as Java and C++

Definition of complex and user-definedtypes

Encapsulation of operations and user-

defined methods

Outline


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Object-Oriented Data DefinitionLanguage(OODDL)

Using OODDL to define Employee, Date, and Department typesdefine type

tuple (Employee:

name:birthday:address:

sex:salary:

workfor:supervisor:supervisee:

manage:workon

string;date;string;stringint;Department;Employee;set(Employee);Department;set(Project); )

Attributes refer to Employee,Department , Project objects relationship among objects

define typetuple (

define typetuple (

Date:year:

month:day:

Departmentname:

number:manager:

locations:members:

control:

integer ;integer ;integer ; );

string ;integer ;tuple (manager:

startdate:set (string );set (Employee);set (Project); );

Employee;Date; );

Using OODDL to define Employee, Date, andDepartment types ( Cont .)

Inverse reference: dept. of employee

employee of dept.

set of references

Specifying Object Behaviorvia Class Operations

Define the behavior of a type of object based onthe operations that can be externally applied toobject of that type create (insert) or destroy (delete) objects update the object state retrieve parts of the object state apply some calculations combination of retrieval, calculation, and update

In relational model, selecting, inserting, deletingand modifying tuples are generic .

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Specifying Object Behaviorvia Class Operations ( Continued )

interface define the name and arguments (parameters)of each operation

signature (included in the class definition) implementation

method (defined using programminglanguages)

it is invoked by sending a message to theobject to execute the corresponding method

Operations 1. object constructors2. object destructor3. object modifier4. retrieval

Using OODDL to define Employeeand Department classes

operationsagecreate_emp:destroy_emp :

end Employee;

integer;Employee;

boolean ;

define classtype tuple (

Employee:name:

birthday:address:

sex:salary:

workfor:supervisor:supervisee:

manage:workon:

string;date;string;stringint;Department;Employee;set(Employee);Department;set(Project);

typedefinition

definitionof

operations

Using OODDL to define Employeeand Department classes (Continued)

define class

type tuple (

Department

name:number:

manager:

locations:members:

control:

string ;integer ;tuple (manager:

startdate:set (string );set (Employee);set (Project); );

Employee;Date; );

operationsnumber_of_emps : integer ;create_dept: Department,destroy_dept: boolean ;assign_emp (e: Employee): boolean ;

(* adds a new employee to the department *)remove_emp (e: Employee): boolean ;

(* removes an employee from the department *)end Department;

typedefinition

definitionof

operations

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Class Operations

object constructor create a new object

destructor destroy an object

object modifier modify various attribute of an object

dot notation d.no_of_emps where d is a reference to a

department object and no_of_emps is anoperation

refer to attributes of an object: d.dnumber, d.mgr.startdate

Specifying Object Persistencevia Naming and Reachability

transient object exist in the executing program and disappear

once the program terminates

persistent object stored in the database and persist after

program termination

naming mechanism give an object a unique persistent name

through which it can be retrieved by this andother program

Reachability reachability mechanism

make the object reachable from some persistentobject an object B is said to be reachable from an

object A if a sequence of references in theobject graph lead from object A to object B

e.g., if o 8 is persistent, then all other objects alsobecome persistent (next slide)

N defines a persistent collection of objects ofclass C

create a named persistent object N, whosestate is a set or list of objects of some class C

add objects of C to the set or list and makethem reachable from N

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Graphical representation ofa complex object

LEGEND: object

tuple

set

NAME NUMBER MANAGER LOCATIONS MEMBERS CONTROL

MANAGER MANAGERSTRATDATE

O5 O4 O9 O7 O10 O11

O8

O1 O2 O3

Houston Bellaire Sugarland

i8:tuple

i5:atom

i4:atom

i9:tuple

i7:set

i10:set

i11:set

i15: .....tuple

i16: .....tuple

i17: .....tuple

i12: .....tuple

i13: .....tuple

i14: .....tuple

i6:atom

O6

1988-05-22

V4V9

V5V7

V10V11

V1 V2 V3

V6

Research 5

Object instance of department type

Creating persistent objects bynaming and reachability

define class DepartmentSet:type set (Department);operations

add_dept(d: Department): boolean ;remove_dept (d: Department): boolean ,create_dept_set: DepartmentSet;destroy_dept_set: boolean ;

end DepartmentSet;

persistent name AllDepartments: DepartmentSet ;(* AllDepartments is a persistent named object of type set DepartmentSet*)

.....d := create_dept ;

..... (* creates a new department object in the variable d *)b := AllDepartments.add_dept (d) ;

(* make d persistent by adding it to the persistent named ob ject AllDepartments *)

AllDepartments object: extent of the class Department

Differences between traditionaldatabases and OO databases

traditional database models when an entity type or class is defined in EER,

it represents both type declaration andpersistent set

OO approaches a class declaration specifies only the type and

operations for a class of objects user must define a persistent object whose

value is the collection of references to allpersistent

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Type Hierarchies and Inheritance type (or class) hierarchy

define new types based on other predefined types (orclasses)

type type name a number of attributes (instance variables) operations (methods)

TYPE_NAME: function, function, , function PERSON: Name, Address, Birthdate, Age, SSN

EMPLOYEE subtype-of PERSON: Salary,HireDate, Seniority

STUDENT subtype-of PERSON: Major, GPA

functions with zero arguments

functions

Inheritance

multiple inheritance when T is a subtype of two (or more) types, T

inherits the functions (attributes and methods) ofboth supertypes

type lattice instead of type hierarchy if a function is inherited from some common

supertype , it is inherited only once ambiguity resolution

alarm users

system default disallow multiple inheritance

Inheritance ( Continued )

Selective Inheritance a subtype inherits only some of the functions

of a supertype an EXCEPT clause may be used to list the

functions in a super type that are not to beinherited by the subtype

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Outline


Object-Oriented Query Language

Declarative query language Not computationally complete

Syntax based on SQL (select, from,where)

Additional flexibility (queries with userdefined operators and types)

SQL3 Object -oriented SQL

Foundation for several OO database managementsystems ORACLE8, DB2, etc New features relational & Object oriented Relational Features new data types, new

predicates, enhanced semantics, additional securityand an active database

Object Oriented Features support for functions andprocedures

Set-oriented query language

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Object Query Language (OQL) Syntax based on SQL (select, from, where) :

select

from [,.] where

Path-oriented query languagePath : C 1.A1.A2... . A n-1 .An

C2 C3... .C nPath expression : C 1.A1.A2... . A n-1 .An = v

Example of OQL query

The following is a sample querywhat are the names of the black product?

Select distinct p.nameFrom products pWhere p.color = black

Valid in both SQL and OQL, but results aredifferent.

Result of the query (SQL)

Product no Name ColorP1 Ford Mustang BlackP2 Toyota Celica GreenP3 Mercedes SLK Black

- The statement queries a relationaldatabase.

=> Returns a table with rows.

Name

Ford MustangMercedes SLK

Result

Original table

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Result of the query (OQL)

Product no Name Color

P1 Ford Mustang Black

P2 Toyota Celica Green

P3 Mercedes SLK Black

- The statementqueries a object-oriented database

=> Returns acollection of objects.

String

Ford Mustang

Result

Original table

String

Mercedes SLK

Comparison

Queries look very similar in SQL and OQL,sometimes they are the sameIn fact, the results they give are verydifferent

Query returns:

OQL SQLObjectCollection of objects

TupleTable

Outline


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Index organizations for OODBS

Path index (PX):a path P = C 1.A1.A2... . A n-1 .Ana path index (PX) on P with C i, 1 i n :

{(v,S)/ v DOM(An )and S = {O i.O i+1..O n / O1.O 2..O n.v is a instantiation of P}}


Nested index (NX): a path P = C 1.A1.A2... . A n-1 .Ana nested index (NX) on P:

{(v,S)/ v DOM(An )and S = {O / O 1.O 2..O n.v isa instantiation of P, O i=O, 1i n }}


Multi-index (MX):

a path P = C 1.A1.A2... . A n-1 .Ana multi-index (MX) on P:1i n {Ii,1, Ii,2,..., Ii,ni} where I i,j, 1 in , 1 jn i, is asingle index on path C ij.Ai and n i is the number ofsubclasses rooted by C ia single index for C ij.Ai is

{(O,S)/ O DOM(Ai )and S = {O / O. Ai=O} Indexes I i,j, 1i

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Inherited multi-index (IMX): a path P = C 1.A1.A2... . A n-1 .An

a inherited multi-index (IMX) on P:1i n {Ii} where I i is s class-hierarchy index on pathC i.Ai.a class-hierarchy index associates with each valueof an attribute A i the OIDs of instances of a class C iand of all its subclasses.an inherited multi-index differs from the multi-indexin that it maintains a single index for all classesbelonging to same inheritance hierarchy.this technique always requires a number of indexesequal to the path length.

Outline


Query Optimization in OODBS

Algebraic Transformation-based queryoptimization

Graph-based query optimization(using path indexes)

Method Materialisation

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Algebraic Transformation-basedquery optimization

The object algebra is a many-sorted

algebra Algebraic operators are defined for thevarious kinds of value sets.

Operators can be classified asconstructors, projection operatorsperforming access to components of acomplex value, selection, and iteration.

Object algebra

Algebraic optimization rules

algebraic optimization rules: validate the defined operators represent semantically equivalent query

transformations. allow algebraic expressions to be

transformed into semantically equivalent, butmore efficiently executable ones.

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Example of algebraic queryThe following is a sample OQL query

what are the names of employees who work for CS

department?Select distinct p.nameFrom employee pWhere p.workfor.name = CS

Algebraic query:iS[S .name .v(s)]( P[Pname (V(D(workfor (V(p)))))=CS](employee))

Graph-based query optimizationusing path indexes

Access Path Selection Generalized Index Intersection Query Graph Reductions Generation of Least-Cost Evaluation Plan

Access Path Selection Eligible indexes for Q, denoted by EI(Q), are the

indexes that are useful in query processing; Eligible indexses, for the condition path i value,

are the indexes constructed on `any subpath' ofthe path i.

Predicates that can (cannot) be processed byindexes are called index processiblepredicates(IP) (residual predicates(RP))

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Access Path SelectionQuery Graph

a i/j the link (i.e., the attribute) that connects the classes C i and C j ---- the path index constructed on the corresponding path expression

Access Path Selection

The problem of determining eligibleindexes in the query optimization hasexponential time complexity.

use a simple index selection heuristic: select all eligible indexes and pointers take full advantage of the path indexes not compromised by the proposed index selection

heuristic.

Generalized Index Intersection(for simple indexes)

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Generalized Index Intersection(for path indexes)

Query Graph Reductions

Objective of Reductions:determine the classes that are replaced by

the index scans and removes them from thequery graph.

use Higraph for modeling the process of thequery graph reduction.

Higraph has one extra element called supernode that contains one or more subnodes (classes).

Query Graph ReductionsThe query graph reduction algorithm consists of the following

three steps:1. For query graph QG, determine the set of eligible indexesEI(QG).2. For each IDX(path i) EI(Q)

1) remove all primitive classes and edges in path i.2) create a new supernode that contains all user-defined classes

in path i; the supernode denotes OID tuples of its subnodesthat satisfy the predicates matched with IDX(path i).

(Note: not remove the user-defined classes on path i sinceresidual predicates may exist for them.

3. If two supernodes (relations) T1 and T2 have a commonsubnode, perform natural join for them. The join result is denotedby another supernode T12 and the nodes T1 and T2 areremoved. We repeat this step until no more supernodes exist inthe query graph that share a subnode.

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Generation of Least-CostEvaluation Plan

The search algorithm generates all possible join orders (or alternative plans) from the RQG, and then estimates evaluation cost for each join order, and finally chooses the least-cost join order based on the cost model.(1) Generation of Search Tree(2) Cost Estimation and The Least-costEvaluation Plan Generation


Generation of Search Tree

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Cost EstimationThe joins of the branch < C 1, C 2, ...,C n >can be processed by the sequence of binary

joinsThe cost formula for the binary join of C i and C i+1 (using pointer-based sort-merge

join algorithm):cost(C i JN ai C i+1) = cost(C i) + sort(C i, a i) +cost(C i+1)


A method materialisation consists:compute the result of a method once,store the method's result persistently in adatabase,use the persistent result value when themethod is invoked.maintain the materialised results: update the

values of materialised methods when objectsused for computing them change (baseobjects)


reduce applications response time for accessing a method's result, especiallywhen its execution takes long time.

add methods maintenance cost in order to improve a system's performance,only the right set of methods should be materialised method materialisation (precomputation,caching) was proposed in the context of indexing techniques and query optimisation.

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Two important issues arise for methodmaterialisation :

(1) what technique to use for method materialisation,and(2) which methods to materialise?

use the dynamic hierarchical methodmaterialisation technique: if the method m i is materialised then other methods

called by m i are materialised. the system decides whether to materialise a given

method or not based on the gathered statistics(method reads and updates of base objects)

Method MaterialisationStorage Structures

Materialised Methods Dictionary (MMD)contains information about all methods:

a method name and class,the array of input arguments,a method return type,a method implementation,and a flag indicating if a method wasmaterialised.


Materialised Method Results Structure (MMRS) stores

the following information about every materialisedmethod:(1) the identifier of a method,(2) an object identifier the method was invoked for,(3) the array of input argument values a method was invoked

with,(4) the value returned by a method while executed for a given

object and for a given array of input argument values. When materialised method m i is required, then MMRS is

searched in order to get the result of m i. If it is not foundthen, the value of m i is computed and stored in MMRS.

When an object used to compute the materialised valueof m i is updated or deleted, then the materialised valuebecomes invalid and is removed from MMRS.

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GMC stores pairs of values:

the identifier of a calling method andthe identifier of a method being called. Graph of Method Calls (GMC) represent

dependencies between methods, whereone calls another one.

GMC is used by the procedure thatmaintains the materialised results ofmethods.


In order to invalidate dependent methodsthe system must be able to find alsoinverse references in object compositionhierarchy.

The references are maintained in a datastructure called Inverse References Index(IRI).


Method Value Index (MVI) is an index definedon results of methods. Every method of a classhas its own MVI. The index stores the following:

(1) the value of a method input argument,(2) a method result, and(3) an object identifier a method was invoked for.

By using this index, the system is able to quicklyfind answers to queries that use methods. Thecontent of MVI is filled in with data whenmethods are materialised.

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Dynamic Method Materialisation

The dynamic method materialisation technique consistsin:(1) gathering method usage statistics and based on thestatistics(2) finding methods whose materialisation increasessystem's performance and methods whosematerialisation deteriorates system's performance.

A software module, called the method analyser and optimiser does the final selection of methods formaterialisation and monitors method accesspatterns and gathers execution statistics.

Dynamic Method Materialisation Tuning of a system is performed in two following steps.Step 1:

select the set S M of methods for materialisation.materialise results of these methods for their first calls.monitor the usage of the methods and gather execution statisticsfor the set of transactions using m i and its materialised valuescalled the batch transaction set .

The size of the batch transaction set is parameterised by a system administrator.

Step 2:identify methods whose materialisation increases system'sperformancedematerialise automatically methods whose materialisationdeteriorates the system's performance

Dynamic Method MaterialisationGathering method usage statistics

For a given method m i the execution statistics include:method execution times and the number of disk accessesfor every object and every set of input argument values,the number of base object updates,the number of reads of m i materialised values,method invalidation times and the number of diskaccesses for every object and every set of input argumentvalues,method recomputation times and the number of diskaccesses for every object and every set of input argumentvalues,time and the number of disk accesses required for findingan already materialised value.

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Dynamic Method MaterialisationSelecting methods for materialisation

Cost Modelr - number of transactions reading the materialised value v of

method m i.u - number of transactions updating a base object of m i.r +u - number of transactions in the batch transaction set.tRMAT - time of reading a materialised value of m i using MMRS.tEXEC - execution time of non-materialised method m i.tREMAT - time of rematerialising value v of m i, after its baseobject was updated.

All the discussed times include I/O as well as CPU times.


The materialisation of method m i will reducequery response time if the following holds:

represents a coefficient by which an overallsystem's response time is to be reduced. It takesits value from the range of (0, 1) and it isconsidered as a tuning parameter set up by anadministrator.


In the worst case, i.e. when all branches in theGMC have to be invalidated, therematerialisation time (t REMAT ) includes:

tINV - invalidation time of a materialised resulttEXEC -time of computing of a method resulttWMAT time of writing the materialised result ondisk.

Thus can be expressed as follows:

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Formula 1 and Formula 2 Formula 3 expressthe number of updates to the number of reads.

for a given method m i and a given batch transaction set, if the inequality in formula 3 istrue, then m is materialisation increase system'sperformance. Otherwise, m i has to bedematerialised.

Object Oriented Databases

Advantages Good integration with

Java, C++, etc Can store complex

information Fast to recover whole

objects Has the advantages of

the (familiar) objectparadigm

Disadvantages There is no underlying

theory to match therelational model

Can be more complexand less efficient

OODB queries tend tobe procedural, unlikeSQL

Object Relational Databases

Extend a RDBMSwith object concepts Data values can be

objects of arbitrarycomplexity

These objects haveinheritance etc.

You can query theobjects as well as thetables

An object relationaldatabase Retains most of the

structure of therelational model

Needs extensions toquery languages (SQLor relational algebra)

OODBS

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