Chapter 9: Object-Based Databases

Chapter 9: Object-Based Databases

اسلاید 1: Chapter 9: Object-Based Databases

اسلاید 2: Chapter 9: Object-Based DatabasesComplex Data Types and Object OrientationStructured Data Types and Inheritance in SQLTable InheritanceArray and Multiset Types in SQLObject Identity and Reference Types in SQLImplementing O-R FeaturesPersistent Programming LanguagesComparison of Object-Oriented and Object-Relational Databases

اسلاید 3: Object-Relational Data ModelsExtend the relational data model by including object orientation and constructs to deal with added data types.Allow attributes of tuples to have complex types, including non-atomic values such as nested relations.Preserve relational foundations, in particular the declarative access to data, while extending modeling power.Upward compatibility with existing relational languages.

اسلاید 4: Complex Data TypesMotivation:Permit non-atomic domains (atomic  indivisible)Example of non-atomic domain: set of integers,or set of tuplesAllows more intuitive modeling for applications with complex dataIntuitive definition:allow relations whenever we allow atomic (scalar) values — relations within relationsRetains mathematical foundation of relational model Violates first normal form.

اسلاید 5: Example of a Nested RelationExample: library information systemEach book has title, a set of authors,Publisher, anda set of keywordsNon-1NF relation books

اسلاید 6: 4NF Decomposition of Nested RelationRemove awkwardness of flat-books by assuming that the following multivalued dependencies hold:title authortitle keywordtitle pub-name, pub-branchDecompose flat-doc into 4NF using the schemas:(title, author )(title, keyword )(title, pub-name, pub-branch )

اسلاید 7: 4NF Decomposition of flat–books

اسلاید 8: Problems with 4NF Schema4NF design requires users to include joins in their queries.1NF relational view flat-books defined by join of 4NF relations:eliminates the need for users to perform joins,but loses the one-to-one correspondence between tuples and documents.And has a large amount of redundancyNested relations representation is much more natural here.

اسلاید 9: Complex Types and SQL:1999Extensions to SQL to support complex types include:Collection and large object typesNested relations are an example of collection typesStructured typesNested record structures like composite attributes InheritanceObject orientationIncluding object identifiers and referencesOur description is mainly based on the SQL:1999 standardNot fully implemented in any database system currentlyBut some features are present in each of the major commercial database systemsRead the manual of your database system to see what it supports

اسلاید 10: Structured Types and Inheritance in SQLStructured 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 finalNote: final and not final indicate whether subtypes can be createdStructured types can be used to create tables with composite attributes create table customer (nameName,addressAddress,dateOfBirth date)Dot notation used to reference components: name.firstname

اسلاید 11: Structured Types (cont.)User-defined row typescreate type CustomerType as (name Name,address Address,dateOfBirth date)not finalCan then create a table whose rows are a user-defined typecreate table customer of CustomerType

اسلاید 12: MethodsCan add a method declaration with a structured type.method ageOnDate (onDate date)returns interval yearMethod body is given separately.create instance method ageOnDate (onDate date)returns interval yearfor CustomerTypebeginreturn onDate - self.dateOfBirth;endWe can now find the age of each customer:select name.lastname, ageOnDate (current_date)from customer

اسلاید 13: InheritanceSuppose 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))Subtypes can redefine methods by using overriding method in place of method in the method declaration

اسلاید 14: Multiple InheritanceSQL:1999 and SQL:2003 do not support multiple inheritanceIf our type system supports multiple inheritance, we can define a type for teaching assistant as follows: create type Teaching Assistant under Student, TeacherTo avoid a conflict between the two occurrences of department we can rename them create type Teaching Assistant under Student with (department as student_dept ), Teacher with (department as teacher_dept )

اسلاید 15: Consistency Requirements for SubtablesConsistency requirements on subtables and supertables.Each tuple of the supertable (e.g. people) can correspond to at most one tuple in each of the subtables (e.g. students and teachers)Additional constraint in SQL:1999:All tuples corresponding to each other (that is, with the same values for inherited attributes) must be derived from one tuple (inserted into one table). That is, each entity must have a most specific typeWe cannot have a tuple in people corresponding to a tuple each in students and teachers

اسلاید 16: Array and Multiset Types in SQLExample of array and multiset declaration: create type Publisher as (name varchar(20), branch varchar(20)) create type Book as (title varchar(20), author-array varchar(20) array [10], pub-date date, publisher Publisher, keyword-set varchar(20) multiset ) create table books of BookSimilar to the nested relation books, but with array of authors instead of set

اسلاید 17: Creation of Collection ValuesArray construction array [‘Silberschatz’,`Korth’,`Sudarshan’]Multisetsmultisetset [‘computer’, ‘database’, ‘SQL’]To create a tuple of the type defined by the books relation: (‘Compilers’, array[`Smith’,`Jones’], Publisher (`McGraw-Hill’,`New York’), multiset [`parsing’,`analysis’ ])To insert the preceding tuple into the relation books insert into books values (‘Compilers’, array[`Smith’,`Jones’], Publisher (`McGraw-Hill’,`New York’), multiset [`parsing’,`analysis’ ])

اسلاید 18: Querying Collection-Valued AttributesTo find all books that have the word “database” as a keyword,select title from books where ‘database’ in (unnest(keyword-set ))We can access individual elements of an array by using indicesE.g.: If we know that a particular book has three authors, we could write:select author-array[1], author-array[2], author-array[3] from books where title = `Database System Concepts’To get a relation containing pairs of the form “title, author-name” for each book and each author of the book select B.title, A.authorfrom books as B, unnest (B.author-array) as A (author )To retain ordering information we add a with ordinality clause select B.title, A.author, A.positionfrom books as B, unnest (B.author-array) with ordinality as A (author, position )

اسلاید 19: UnnestingThe transformation of a nested relation into a form with fewer (or no) relation-valued attributes us called unnesting.E.g. select title, A as author, publisher.name as pub_name, publisher.branch as pub_branch, K.keyword from books as B, unnest(B.author_array ) as A (author ),unnest (B.keyword_set ) as K (keyword )

اسلاید 20: Nesting Nesting is the opposite of unnesting, creating a collection-valued attributeNOTE: SQL:1999 does not support nestingNesting can be done in a manner similar to aggregation, but using the function colect() in place of an aggregation operation, to create a multisetTo nest the flat-books relation on the attribute keyword:select title, author, Publisher (pub_name, pub_branch ) as publisher, collect (keyword) as keyword_set from flat-books groupby title, author, publisherTo nest on both authors and keywords: select title, collect (author ) as author_set, Publisher (pub_name, pub_branch) as publisher, collect (keyword ) as keyword_set from flat-books group by title, publisher

اسلاید 21: 1NF Version of Nested Relation1NF version of booksflat-books

اسلاید 22: Nesting (Cont.)Another approach to creating nested relations is to use subqueries in the select clause. select title, array ( select author from authors as A where A.title = B.title order by A.position) as author_array, Publisher (pub-name, pub-branch) as publisher, multiset (select keyword from keywords as K where K.title = B.title) as keyword_set from books4 as B

اسلاید 23: Object-Identity and Reference TypesDefine 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 DepartmentWe can omit the declaration scope people from the type declaration and instead make an addition to the create table statement: create table departments of Department (head with options scope people)

اسلاید 24: Initializing Reference-Typed ValuesTo create a tuple with a reference value, we can first create the tuple with a null reference and then set the reference separately:insert into departments values (`CS’, null)update departments set head = (select p.person_id from people as p where name = `John’) where name = `CS’

اسلاید 25: User Generated IdentifiersThe type of the object-identifier must be specified as part of the type definition of the referenced table, andThe table definition must specify that the reference is user generated create type Person (name varchar(20) address varchar(20)) ref using varchar(20) create table people of Person ref is person_id user generatedWhen creating a tuple, we must provide a unique value for the identifier: insert into people (person_id, name, address ) values (‘01284567’, ‘John’, `23 Coyote Run’)We can then use the identifier value when inserting a tuple into departmentsAvoids need for a separate query to retrieve the identifier: insert into departments values(`CS’, `02184567’)

اسلاید 26: User Generated Identifiers (Cont.)Can use an existing primary key value as the identifier: create type Person (name varchar (20) primary key, address varchar(20)) ref from (name) create table people of Person ref is person_id derivedWhen inserting a tuple for departments, we can then useinsert into departments values(`CS’,`John’)

اسلاید 27: Path ExpressionsFind the names and addresses of the heads of all departments:select head –>name, head –>address from departmentsAn expression such as “head–>name” is called a path expressionPath expressions help avoid explicit joinsIf department head were not a reference, a join of departments with people would be required to get at the addressMakes expressing the query much easier for the user

اسلاید 28: Implementing O-R FeaturesSimilar to how E-R features are mapped onto relation schemasSubtable implementationEach table stores primary key and those attributes defined in that tableor,Each table stores both locally defined and inherited attributes

اسلاید 29: Persistent Programming LanguagesLanguages extended with constructs to handle persistent dataProgrammer can manipulate persistent data directlyno need to fetch it into memory and store it back to disk (unlike embedded SQL)Persistent objects:by class - explicit declaration of persistenceby creation - special syntax to create persistent objectsby 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

اسلاید 30: Object Identity and PointersDegrees of permanence of object identityIntraprocedure: only during execution of a single procedureIntraprogram: only during execution of a single program or queryInterprogram: across program executions, but not if data-storage format on disk changesPersistent: interprogram, plus persistent across data reorganizationsPersistent versions of C++ and Java have been implementedC++ODMG C++ObjectStoreJavaJava Database Objects (JDO)

اسلاید 31: Comparison of O-O and O-R DatabasesRelational systemssimple data types, powerful query languages, high protection.Persistent-programming-language-based OODBscomplex data types, integration with programming language, high performance.Object-relational systemscomplex data types, powerful query languages, high protection.Note: Many real systems blur these boundariesE.g. persistent programming language built as a wrapper on a relational database offers first two benefits, but may have poor performance.

اسلاید 32: End of Chapter