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Ch9
1.
Chapter 9: ObjectBased Databases
Database System Concepts ©Silberschatz, Korth and Sudarshan See www.dbbook.com for conditions on reuse Database System Concepts ©Silberschatz, Korth and Sudarshan
2.
Chapter 9: ObjectBased Databases
s Complex Data Types and Object Orientation s Structured Data Types and Inheritance in SQL s Table Inheritance s Array and Multiset Types in SQL s Object Identity and Reference Types in SQL s Implementing OR Features s Persistent Programming Languages s Comparison of ObjectOriented and ObjectRelational Databases Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
3.
ObjectRelational Data Models
s Extend the relational data model by including object orientation and constructs to deal with added data types. s Allow attributes of tuples to have complex types, including nonatomic values such as nested relations. s Preserve relational foundations, in particular the declarative access to data, while extending modeling power. s Upward compatibility with existing relational languages. Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
4.
Complex Data Types
s Motivation: q Permit nonatomic domains (atomic ≡ indivisible) q Example of nonatomic domain: set of integers,or set of tuples q Allows more intuitive modeling for applications with complex data s Intuitive definition: q allow relations whenever we allow atomic (scalar) values — relations within relations q Retains mathematical foundation of relational model q Violates first normal form. Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
5.
Example of a Nested Relation
s Example: library information system s Each book has q title, q a set of authors, q Publisher, and q a set of keywords s Non1NF relation books Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
6.
4NF Decomposition of Nested Relation
s Remove awkwardness of flatbooks by assuming that the following multivalued dependencies hold: q title author q title keyword q title pubname, pubbranch s Decompose flatdoc into 4NF using the schemas: q (title, author ) q (title, keyword ) q (title, pubname, pubbranch ) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
7.
4NF Decomposition of flat–books Database System Concepts 5th Edition, Aug 9, 2005.
9.<number> ©Silberschatz, Korth and Sudarshan
8.
Problems with 4NF Schema
s 4NF design requires users to include joins in their queries. s 1NF relational view flatbooks defined by join of 4NF relations: q eliminates the need for users to perform joins, q but loses the onetoone correspondence between tuples and documents. q And has a large amount of redundancy s Nested relations representation is much more natural here. Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
9.
Complex Types and SQL:1999
s Extensions to SQL to support complex types include: q Collection and large object types Nested relations are an example of collection types q Structured types Nested record structures like composite attributes q Inheritance q Object orientation Including object identifiers and references s Our description is mainly based on the SQL:1999 standard q Not fully implemented in any database system currently q But some features are present in each of the major commercial database systems Read the manual of your database system to see what it supports Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
10.
Structured Types and Inheritance in SQL
s Structured types can be declared and used in SQL create type Name as (firstname varchar(20), lastname varchar(20)) final create type Address as (street varchar(20), city varchar(20), zipcode varchar(20)) not final q Note: final and not final indicate whether subtypes can be created s Structured types can be used to create tables with composite attributes create table customer ( name Name, address Address, dateOfBirth date) s Dot notation used to reference components: name.firstname Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
11.
Structured Types (cont.)
s Userdefined row types create type CustomerType as ( name Name, address Address, dateOfBirth date) not final s Can then create a table whose rows are a userdefined type create table customer of CustomerType Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
12.
Methods
s Can add a method declaration with a structured type. method ageOnDate (onDate date) returns interval year s Method body is given separately. create instance method ageOnDate (onDate date) returns interval year for CustomerType begin return onDate self.dateOfBirth; end s We can now find the age of each customer: select name.lastname, ageOnDate (current_date) from customer Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
13.
Inheritance
s Suppose that we have the following type definition for people: create type Person (name varchar(20), address varchar(20)) s 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)) s Subtypes can redefine methods by using overriding method in place of method in the method declaration Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
14.
Multiple Inheritance
s SQL:1999 and SQL:2003 do not support multiple inheritance s If our type system supports multiple inheritance, we can define a type for teaching assistant as follows: create type Teaching Assistant under Student, Teacher s To 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 ) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
15.
Consistency Requirements for Subtables
s Consistency requirements on subtables and supertables. q 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) q 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 type We cannot have a tuple in people corresponding to a tuple each in students and teachers Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
16.
Array and Multiset Types in SQL
s Example of array and multiset declaration: create type Publisher as (name varchar(20), branch varchar(20)) create type Book as (title varchar(20), authorarray varchar(20) array [10], pubdate date, publisher Publisher, keywordset varchar(20) multiset ) create table books of Book s Similar to the nested relation books, but with array of authors instead of set Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
17.
Creation of Collection Values
s Array construction array [‘ Silberschatz’ ,`Korth’ ,`Sudarshan’ ] s Multisets q multisetset [‘ computer’ , ‘ database’ , ‘ SQL’ ] s To create a tuple of the type defined by the books relation: (‘ Compilers’ , array[`Smith’ ,`Jones’ ], Publisher (`McGraw-Hill’ ,`New York’ ), multiset [`parsing’ ,`analysis’ ]) s 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’ ]) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
18.
Querying CollectionValued Attributes
s To find all books that have the word “database” as a keyword, select title from books where ‘database’ in (unnest(keywordset )) s We can access individual elements of an array by using indices q E.g.: If we know that a particular book has three authors, we could write: select authorarray[1], authorarray[2], authorarray[3] from books where title = `Database System Concepts’ s To get a relation containing pairs of the form “title, authorname” for each book and each author of the book select B.title, A.author from books as B, unnest (B.authorarray) as A (author ) s To retain ordering information we add a with ordinality clause select B.title, A.author, A.position from books as B, unnest (B.authorarray) with ordinality as A (author, position ) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
19.
Unnesting
s The transformation of a nested relation into a form with fewer (or no) relationvalued attributes us called unnesting. s 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 ) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
20.
Nesting
s Nesting is the opposite of unnesting, creating a collectionvalued attribute s NOTE: SQL:1999 does not support nesting s Nesting can be done in a manner similar to aggregation, but using the function colect() in place of an aggregation operation, to create a multiset s To nest the flatbooks relation on the attribute keyword: select title, author, Publisher (pub_name, pub_branch ) as publisher, collect (keyword) as keyword_set from flatbooks groupby title, author, publisher s To 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 flatbooks group by title, publisher Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
21.
1NF Version of Nested Relation
1NF version of books flatbooks Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
22.
Nesting (Cont.)
s 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 (pubname, pubbranch) as publisher, multiset (select keyword from keywords as K where K.title = B.title) as keyword_set from books4 as B Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
23.
ObjectIdentity and Reference Types
s 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) s We can then create a table departments as follows create table departments of Department s We 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) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
24.
Initializing ReferenceTyped Values
s To 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’ Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
25.
User Generated Identifiers
s The type of the objectidentifier must be specified as part of the type definition of the referenced table, and s The 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 generated s When 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’) s We can then use the identifier value when inserting a tuple into departments q Avoids need for a separate query to retrieve the identifier: insert into departments values(`CS’, `02184567’) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
26.
User Generated Identifiers (Cont.)
s 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 derived s When inserting a tuple for departments, we can then use insert into departments values(`CS’,`John’) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
27.
Path Expressions
s Find the names and addresses of the heads of all departments: select head – >name, head – >address from departments s An expression such as “head– >name” is called a path expression s Path expressions help avoid explicit joins q If department head were not a reference, a join of departments with people would be required to get at the address q Makes expressing the query much easier for the user Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
28.
Implementing OR Features
s Similar to how ER features are mapped onto relation schemas s Subtable implementation q Each table stores primary key and those attributes defined in that table or, q Each table stores both locally defined and inherited attributes Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
29.
Persistent Programming Languages
s Languages extended with constructs to handle persistent data s Programmer can manipulate persistent data directly q no need to fetch it into memory and store it back to disk (unlike embedded SQL) s Persistent objects: q by class explicit declaration of persistence q by creation special syntax to create persistent objects q by marking make objects persistent after creation q by reachability object is persistent if it is declared explicitly to be so or is reachable from a persistent object Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
30.
Object Identity and Pointers
s Degrees of permanence of object identity q Intraprocedure: only during execution of a single procedure q Intraprogram: only during execution of a single program or query q Interprogram: across program executions, but not if datastorage format on disk changes q Persistent: interprogram, plus persistent across data reorganizations s Persistent versions of C++ and Java have been implemented q C++ ODMG C++ ObjectStore q Java Java Database Objects (JDO) Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
31.
Comparison of OO and OR Databases
s Relational systems q simple data types, powerful query languages, high protection. s Persistentprogramminglanguagebased OODBs q complex data types, integration with programming language, high performance. s Objectrelational systems q complex data types, powerful query languages, high protection. s Note: Many real systems blur these boundaries q E.g. persistent programming language built as a wrapper on a relational database offers first two benefits, but may have poor performance. Database System Concepts 5th Edition, Aug 9, 2005. 9.<number> ©Silberschatz, Korth and Sudarshan
32.
End of Chapter
Database System Concepts ©Silberschatz, Korth and Sudarshan See www.dbbook.com for conditions on reuse Database System Concepts ©Silberschatz, Korth and Sudarshan
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