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Temporal DatabasesMultimedia & Databases

DB2 Extenders

nikos dimitrakaswww.nikosdimitrakas.com

nikos@dsv.su.se08-162099room 6626

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Temporal Databases

• Time– Transaction time

When something is registered in the database

– Valid time

When something occurs in the real world

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Database Taxonomy

• Snapshot databases– no time – just the current state

• Historical databases– only valid time – records the full history/evolution of

concepts in the database

• Rollback databases– only transaction time – records all previous states of the

database

• Temporal databases– both valid and transaction time – combines the

advantages of both historical and rollback databases.

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Database Taxonomy

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An Example

Consider the following trivial information:

• A database of people and their salary.

PID Name Salary

001

002

…

Bill

John

…

7500

8100

…

Snapshot database:

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Snapshot Database

PID Name Salary

001

002

…

Bob

John

…

7500

8100

…

We can only see the current value. We do not know when the value was entered in the database nor whether it has ever been changed.

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Historical Database

PID Name Salary StartTime EndTime

001

001

001

002

002

…

Bob

Bob

Bob

John

John

…

6500

8000

7500

7900

8100

…

Jan 1998

Feb 1999

Dec 1999

May 1999

Mar 2001

…

Feb 1999

Dec 1999

<now>

Mar 2001

<now>

…

We can see the current value for any point in time. We still do not know when the value was entered in the database nor whether it has ever been changed (error correction).

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Historical Database error correction

PID Name Salary StartTime EndTime

001

001

001

001

002

002

…

Bob

Bob

Bob

Bob

John

John

…

6500

7500

8000

7500

7900

8100

…

Jan 1998

Feb 1999

Apr 1999

Dec 1999

May 1999

Mar 2001

…

Feb 1999

Apr 1999

Dec 1999

<now>

Mar 2001

<now>

…

If we discover an error in the database we have the possibility to change it for that period of time.If we find out that Bob earned 7500 between February 1999 and April 1999 we can modify our data to the following:

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Rollback Database

PID Name Salary TransTime

001

001

001

002

002

…

Bob

Bob

Bob

John

John

…

6500

8000

7500

7900

8100

…

Mar 1998

Feb 1999

Sep 2001

Mar 2001

Sep 2001

…

We can see all the values that have been valid in the database. We know when the values were entered in the database, but we do not know when they were valid. We can not change values in any of the records. We can only add new records.

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Rollback Database interpretation

PID Name Salary TransTime

001

001

001

002

002

…

Bob

Bob

Bob

John

John

…

6500

8000

7500

7900

8100

…

Mar 1998

Feb 1999

Sep 2001

Mar 2001

Sep 2001

…

We can always see which value was current in the database at any point in time. It can be an advantage to know what errors were contained in the database at a certain time!

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Temporal Database

PID Name Salary StartTime EndTime TranTime

001

001

001

002

002

…

Bob

Bob

Bob

John

John

…

6500

8000

7500

7900

8100

…

Jan 1998

Feb 1999

Dec 1999

May 1999

Mar 2001

…

Feb 1999

Dec 1999

<now>

Mar 2001

<now>

…

Mar 1998

Feb 1999

Sep 2001

Mar 2001

Sep 2001

…

We can see the valid value for any point in time. We can see when a value was entered in the database.We can see what errors have been corrected and when.

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Temporal Databaseerror correction

PID Name Salary StartTime EndTime TranTime

001

001

001

002

002

001

001

…

Bob

Bob

Bob

John

John

Bob

Bob

…

6500

8000

7500

7900

8100

7500

8000

…

Jan 1998

Feb 1999

Dec 1999

May 1999

Mar 2001

Feb 1999

Apr 1999

…

Feb 1999

Dec 1999

<now>

Mar 2001

<now>

Apr 1999

Dec 1999

…

Mar 1998

Feb 1999

Sep 2001

Mar 2001

Sep 2001

May 2003

May 2003

…

Errors can be corrected but the transaction time shows when they where corrected. We can therefore still see that until May 2003 the database ”believed” that Bob earned 8000 between February 1999 and Dec 1999.

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QueryingSnapshot Historical Rollback Temporal

How much does Bob earn?

7500 7500 7500 7500

How much did Bob earn in March 1999?

cannot be expressed

7500 maybe 8000

7500

What was Bob’s current salary in March 1999?

cannot be expressed

cannot be expressed

8000 8000

What did we think that Bob earned in March 1999 (vt) a year ago (tt)?

cannot be expressed

cannot be expressed

cannot be expressed

7500

What did we think that Bob earned in March 1999 (vt) three years ago (tt)?

cannot be expressed

cannot be expressed

cannot be expressed

8000

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Pros & Cons

• Pros– No missing data

• Cons– Requires more space

– More complicated to update records

– More complicated to query the database

• Workarounds– Horizontal segmentation (simplifies querying of current data)

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Multimedia

• Types– Images, graphics

– Audio

– Video

– Text documents

– ??

• Aspects– Time

– Size

– Interpretation

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Time & Dimensions

• Text– Time independent (discrete)

– 1 dimension

• Audio– Time dependent (continuous)

– 1 dimension

• Image– Time independent

– 2 dimensions (height & width)

• Video– Time dependent

– 3 dimensions (height, width & time)

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Managing & Effects of Size

• Multimedia in file system (Reference in database)

• Multimedia in database– Stored separately

– Mixed with “normal” data

• Storage choice affects performance– slower access to multimedia faster access to normal data

• Vertical segmentation

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Applications

• Travel industry

• Entertainment industry• Medical databases• Text and photograph archives• Digital libraries• Electronic encyclopedias• Geographic information systems• Shopping guides• …

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Requirements

• Querying– On

» Content dependent data

» Content descriptive data

» Content independent data

• Retrieval– Fast retrieval

– Smooth retrieval for time dependent media

• Presentation– This can be placed outside the DBMS

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Multimedia Metadata• Data about the multimedia objects

– Content dependent dataData that can be derived from the contents of the multimedia objectThe color of the bird in the picture.The lyrics of the song.

– Content descriptive dataData associated with the contents of the multimedia object, but cannot be automatically identifiedThe breed of the bird in the picture.The singer’s sex.

– Content independent dataData that is associated with the multimedia object, but does not relay to its contentsThe name of the photographerThe name of the song writer, the brand of the microphone used.

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Querying needs• Find all images taken by J. Smith!

• Find all images with the same color, shape and texture as this image!

• Find all images which look like this image!

• Find all images with the same color distribution like this sunset photograph!

• Find all images which contain a car!

• Find all images which contain a car and a man who looks like this!

• Find all the songs that are about surfing!

• Find all documents that have the words church and song in the same sentence!

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Querying needs• Find all videos with big explosions!

• Find a video where there is an explosion after a car chase!

• Find an instrumental audio clip with both violin and electric guitar!

• Show me the first 10 seconds of all the videos!

• Show me the 20 seconds exactly before the explosion in videos that contain explosions!

• Find all songs that are duets and end with a fade-out!

• Find all images with a dog standing next to a tree!

• …

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Query Types• Queries on the content of the media information

– Find all images which contain a car!– Find all videos with big explosions!– Find an instrumental audio clip with both violin and electric

guitar!• Queries by example (QBE)

– Find all images which look like this image!• Time indexed queries

– Show me the first 10 seconds of all the videos!• Spatial queries

– Find all images with a dog standing next to a tree!– Find a video where there is an explosion after a car chase!– Find all documents that have the words church and song in

the same sentence!• Application specific queries

– Queries on content descriptive/content independent data (?)• Combinations of the above

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Querying Multimedia vs. Normal Data

Multimedia Data Normal Data

Query Matching Approximate Exact

Sorting By Relevance User Specified

Examples:•All people that live in Stockholm sorted by name.•All pictures like this one.

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Multimedia Analysis

• Identify features– There is a river in the picture– There is a violin playing– Blue eyes, brown hair

• Manually add features– The person on the picture is Indian– The dog’s name i Barky

• Identify relations– The car is on the left of the house– The person is inside the car– The saxophone solo was before the guitar solo

• Manually add relations– The dog is owned by Howard– James employs Roger

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Other Considerations

• Similarity searches

• Ranking results

• Weighing conditions

• Synonym management

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Example

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IBM DB2 & Multimedia• Built-in support for

– Basic content dependent data

– Query by example (image only)

– Spatial queries (text only)

– Returning only complete objects

• Possible to define other tables and columns for features and relations

• Possible to define functions

• Possible to extend (with programming)

• Multimedia Storage– in the database

– outside the database

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DB2 Extenders & Assignments

• Text– Exact searches

– Linguistic searches

– Spatial searches

– Synonym searches

– Similarity searches

– Ranking results

• Audio, Video, Image– Metadata searches

• Image only– Query by example

– Color related searches

– Similarity searches

– Ranking

• Storage– In the database

» mixed with other data (Text)

» in separate tables (Multimedia)

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DB2 Extenders & Labs

• Text– Create database

– Load data

– Enable for text indexing

– Query database

• Audio, Video, Image– Create database

– Enable for multimedia

– Load data

– Query database

We will not extract the actual multimedia objects, since that would require some presentation facilities which are not included in DB2

This would be an interesting project for those interested in learning more about working with multimedia and wouldn’t mind doing a little programming.

Project course: IS8/2i1410 Current Problems in Information Systems

More on Text Retrieval: ISBI/2I1068/2I4078 Internet Search Techniques and Business Intelligence

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Large Objects vs. Performance testing in DB2

1. Create a table with multimedia and normal columns!

2. Load the table with data!

3. Write a query for extracting only normal data (Varchars, Integers, etc.)!

4. Evaluate your query with an Access Plan!

5. Create a similar table only with the normal columns!

6. Load the same data to the new table!

7. Rewrite the query so that it uses the new table!

8. Evaluate the new query!

9. Compare the two results!