CS 500: Database Theory
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Object-relational databases!
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supplementary material:
class notes
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Material of this lecture is based on Chapter 23 of !
“Database Management Systems” 3rd Ed, Ramakrishnan & Gehrke!
Julia Stoyanovich ([email protected])
Motivating example
California Department of Water Resources: 500,000
photos, with captions
Find sunset pictures of landmarks within 20 miles of
Sacramento, CA.
create table Photos (
id number primary key,
ts date,
caption document,
picture photo_CD_image);
!
create table Landmarks (
name varchar(64) primary key,
location point);
select
from
where
and
and
and
id
Photos P, Landmarks L, Landmarks S
sunset(P.picture)
contains(P.caption, L.name)
L.location |20| S.location
S.name = ‘Sacramento, CA'
Note: user-defined functions
(UDFs) and operators!
!
Note: query optimization must
be re-considered
Julia Stoyanovich
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Object-database systems
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Relational databases: relations are in first normal form. Clean
and simple. But the world is more complex!!
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There is sometimes a need to accommodate!
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complex data types / nesting!
inheritance hierarchies!
Two directions, conceptually very similar but implementations
differ!
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Object-Oriented Database Systems (OODBMS) !
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implemented by Oracle, PostgreSQL and others
Object-Relational database Systems (ORDBMS) is the
currently accepted model, part of the SQL:1999 standard.
Extends the relational model, borrows concepts from OO
programming languages.!
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The Dinky Entertainment Company
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About the company!
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Location: Holywood, CA!
Main assets: cartoon characters, e.g., Herbert the Worm!
Products: film shows, voice and video-footage licenses
(e.g., for action figures, video games)!
DBMS manages everything!!
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New data types required!
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user-defined abstract data types (ADTs): image, sound,
video, with functions and operators!
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type constructors: sets, tuples, arrays!
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inheritance: low-resolution and high-resolution images
are images
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Why an RDBMS won’t do
BLOB = binary large object!
create table Frames (
frame_number number primary key,
image BLOB,
category number
);
!
no structure / semantics!
!
cannot issue any conditional
queries against the image
attribute
Enter ORDBMS!
• user-defined data types possible for attributes!
• complex attributes are possible (non 1NF)!
• reference types (pointers) - why do we need them? why are these
potentially problematic?!
• inheritance
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User-Defined Abstract Data Types
I’ve got one word for you: encapsulation! !
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Users define new types, with their operations (methods). !
Define how to read and output objects of the new type!
Define the size of the objects of the new type
create abstract data type jpeg_image
(internallength=VARIABLE, input=jpeg_in, output=jpeg_out);
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create function is_sunrise(jpeg_image) returns boolean
as external name '/usr/local/bin/dinky.jar';
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Atomic and user-defined types!
Type constructors: !
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row (f1 t1, …,fn tn) - a tuple of n fields, where fi us the bane if the filed and ti
is its type !
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Listof (base), Arrayof(base), Setof(base), Bagof(base)
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Reference types
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Objects have an OID!
Consequences? ref / deref!
Examples:!
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ref(theater_t) !
setof(ref(arrayof(integer)))!
Shallow vs. deep equality !
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deep equality is defined recursively for complex
types
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Inheritance
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To reuse and refine type definitions!
To create hierarchies of collections of similar but
not identical objects!
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create type superhero_t
under superbeing_t (strength, power);
Substitution principle: Given a super type A, and a subtype
B, i t is always possible to substitute an object of type B
into a legal expression written for objects of type A.
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ORDBMS Implementation
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Physical data layout!
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objects that vary in size over their lifetime!
Access methods!
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nested objects, arrays!
indexes on predicates!
indexes over collection hierarchies!
Query processing!
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New aggregates!
1.specify what to do with first object (e.g., sum=0)!
2.specify what do to on next (e.g., sum+=item)!
3.specify what to do on last object (e.g., avg = sum / cnt)!
- Method caching for expensive predicates
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Query optimization
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Using new indexes!
• what where-clause conditions are matched by the index!
• what does it cost to fetch a tuple using the index - either
supplied or measured by the DBMS directly!
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Reduction factor and cost estimation for ADT methods!
• effect of evaluating a selection condition is no longer
negligible! Must consider both selectivity and cost.!
• selectivity of a condition is 1/N means that 1 in N tuples
will pass the selection condition
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Query optimization example
Retrieve all photos in which Herbert is enjoying the sunrise.
σ
isSunrise()∧isHerbert ()
N=100,000 images in R!
isHerbert: cost = 0.5 sec/image, sel = 1/10 !
isSunrise: cost = 0.01 sec/image, sel = 1/5
Julia Stoyanovich
R
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Query optimization example
Retrieve all photos of Herbert in which there is no sunrise.
σ
isSunrise()∧ NOT isHerbert ()
N=100,000 images in R!
isHerbert: cost = 0.5 sec/image, sel = 1/10 !
NOT isSunrise: cost = 0.01 sec/image, sel = 4/5
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R
Query optimization
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Reduction factor and cost estimation for ADT methods!
1. compute the rank of each condition involving an ADT method!
2. order conditions by increasing rank, process in that order
rank =
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reductionFactor − 1
Cost
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