DRESDEN UNIVERSITY OF TECHNOLOGY DATABASES Henrike Berthold Schema design and query processing in a...

Henrike BertholdDRESDEN UNIVERSITY OF TECHNOLOGY

DATABASES

Schema design and query processing in a federated multimedia database system

CoopIS, Trento, Italy, 05/09/2001

Problem

A Federated Multimedia Database System

Global schema construction

Query processing

Summary

Henrike Berthold & Klaus Meyer-Wegener

Dresden University of Technology, Germany


DATABASES

Problem

• SDBS: Database system with a schema, a query language, ...• MRS: Media retrieval system• MSS: Media storage system

Application 1 Application n

SDBS 1 SDBS k MRS 1 MRS m MSS 1 MSS n


DATABASESMedia retrieval systems• Perform content-based search based on automatically extracted

features (perception + semantical primitives)• work for a set of media objects of a certain media type such as

image, text, video, audio or a subset with a certain semantics such as passport photos

• Retrieval functions– single: search argument (example, feature, weighting),

media object -> similarity value– coll: search argument -> list if tuples (similarity value, MID)– result restrictions of coll: lower bound for similarity values,

subset of media objects, top n• Example systems: QBIC (IBM), Excalibur Image Datablade,

Melodiscov (LIP6)• Problem: only interactive interface and no programming one


DATABASES

Media storage systems

• Store and manage media objects like images, videos• provide operations for those• support especially timed playout of continuous media objects• all systems provide media description data such as size, format• some systems support transactional concepts like durability,

atomicity• Example systems: Tiger Shark (IBM), Symphony (Uni Texas),

Fellini (Bell Labs), Kangaroo/Memo.REAL (Dresden University of Technology)


DATABASESA Federated Multimedia Database System

- Database schema and query processing

- Operations on media objects

- Transactions

FMDBS

Application 1 Application n

SDBS 1 SDBS k MRS 1 MRS m MSS 1 MSS n

FMDBMS


DATABASESGlobal schema construction

• Structured-data schema (SDS) = global schema of all SDBS-Schemas

MSS1-Schema MSSn-Schema

Media Schema (MS)

SDBS1-Schema SDBSk-Schema

Structured-data Schema (SDS)

integrates

based on two intermediate schemas:

• Media schema (MS) = global schema of all MSS schemas


DATABASESExample media schemaCommon data model: ODMG, CROQUE• Types and subtype-relation• Classes and subclass-relation

Image:TImage

CityPart:TImagePartPassportPhoto:TImage City:TImageWithPart1 *

Video:TVideo Audio:TAudio Text:TText

ContMedia:TContMedia

:TSingleMedia :TObject


DATABASESStep 1: Base integration

Schema architecture:


Media Schema (MS)


Structured-data Schema (SDS)

integrates

Global Schema


DATABASESStep 2: Integration of media retrieval functions

• single: objekt method +• coll: class method -, function -

• allows combination of boolean queries with media retrieval queries


DATABASES

Step 2: Example

t5 (=t1‘)

t6 (=t3‘) t7 (=t4‘)

c2:t1 c3:t2c1:t1

c6:t4 c7:t3c5:t3c4:t3t2

t0

t1

t3 t4

t0t0

t1

t3

t0

t4

t0

t1

t3

t0

c11:t6 c12:t6 c13:t7

c1:t5


DATABASESStep 3: Extension

• complex extension: new objects + relationships

TVideoTText

TSingleMediaTLecture TSlide

TImage

1 1..*TVisualElement

Time interval Region

TVideoElementTTextElement

TImageElement

2 8x

y

Region forvideo

Region forimage

Region for text

t in min

Text1

Image1

Video

Image2

Text2

• Simple extension: relationships


DATABASES

Schema architecture


Media Schema


Structured-data Schema

integrates

Global Schema

Internal Schema

MRS1-Function MRSm-Function


DATABASESConstruction data


DATABASESQuery processingGlobal OQL Query

Global querycomputation

Decomposition andglobal optimization

Modification

Local optimizationand execution

Global execution

Result

Type checking andmapping to intermediate representation

Replacing global specifiers by local ones

Decomposition and optimization by theglobal query processor

Optimization by the local queryprocessors and local execution

Combining local results globally

Constructiondata


DATABASES

FMDBS-specific problems

• Modification– Vertical fragmentation

GT1 GT2GT3

GT4

complete replacement of a global object is not possible

– Replacement of search methods


DATABASESComprehension syntax


DATABASESMonads and algebras


DATABASES

Advantages

• uniform representation of collections (set, bag, list) and aggregations

• readability• there are equivalences defined

– easy manipulation

• there is a mapping to an algebraic expression– embedding in traditional query processing is possible

• thus: better suited for manipulations than an object algebra


DATABASESModification


DATABASES

Improvements

• Paths that belong to one source are replaced completely; so far: replacement of each single function

• A generator which binds a global object is replaced by a sequence of qualifiers which produce all local objects that are used in the query; so far: production of local objects there, where they are used

• exploit function coll and its result restrictions


DATABASESReplacement of function single by coll


DATABASESIdentification of a lower bound


DATABASESIdentification of a subcollection restriction


DATABASESPrototype


DATABASES

Summary• An FMDBS manages structured data and media

data. It takes the integration efforts from the applications.

• Development of a procedure to construct the global schema– data (relationships, new types and classes) and media

retrieval functions can be added

• Development of a procedure to modify queries– can handle the vertical fragmentation– choses efficiently executable media search functions

• Applications have a powerful mean to find suitable data


DATABASES

Outlook

• Problem: Chose a result restriction if some are applicable

• Need of a general cost model of media search systems

• Construction of a complete FMDBS• Need of tools which support the construction

and the administration

DRESDEN UNIVERSITY OF TECHNOLOGY DATABASES Henrike Berthold Schema design and query processing in a...

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