Multi-Dimensional Clustering: A High-Level Overview

© 2009 IBM Corporation

Multi-Dimensional ClusteringA High-Level Overview

Zoran Kulina

DB2 CE Kernel Development

Multi-Dimensional Clustering

© 2009 IBM Corporation2

MDC Purpose

One of the three methods for partitioning data in DB2 (others being range and database partitioning).

Allows flexible, continuous and automatic clustering of data along multiple dimensions.

Primarily intended for data warehousing and large database systems; can also be used in OLTP environments.

Enables a table to be physically clustered on more than one key (or dimension) simultaneously.



MDC Concepts

Block– MDC version of extent

– Consecutive set of pages on the disk

– The smallest allocation unit of an MDC table

Block index– Automatically created

– Point to blocks of data rather than individual rows

– Cannot enforce uniqueness

– Cannot be dropped



MDC Concepts

Dimension block index– One per dimension

– Used to access dimension data

Composite block index– One per table or partition

– Contains all dimension columns

– Used to maintain clustering of data during insert or update



MDC Concepts

Block map

– Maintains usage status information for blocks (extents)

– Facilitates quick lookup of empty blocks in MDC tables

Reserved Data stored

year

East, 1996

North, 1996

North, 1997

South, 1999

0

1

2

3

4

5

6...

Extents in the table

0

X

1

F U U U F U

2 3 4 5 6 ...7

F ...

Reserved

Free - no bits set

X

F

U In use - data assigned to a cell



MDC Concepts

Dimension– Ordered set of one or more columns (clustering keys) of the table

– Axis along which data is organized in an MDC table

– Example: dimensions for nation, color, and year

1997, Canada,

blue

1997, Mexico, yellow

1997, Mexico,

blue

1997, Canada, yellow

1998, Mexico, yellow1997,

Mexico, yellow

1998, Canada, yellow1997,

Canada, yellow

yeardimension

colourdimension

nationdimension



MDC Concepts

Slice

– Portion of the table that contains all the rows that have a specific dimension value (e.g. nation = ‘Canada’)

1997, Canada,

blue


1997, Mexico,

blue



Mexico, yellow

1998, Canada, yellow1997,

Canada, yellow

yeardimension

colourdimension

nationdimension

Canada slice



MDC Concepts

Cell

– Portion of the table that contains rows having the same unique set of dimension values

– Intersection of slices from each dimension (e.g. all records where year=2002, country='Canada', and color='yellow‘)

yeardimension

colourdimension

nationdimension

Cell for (1997, Canada, yellow)

1997, Canada,

blue


1997, Mexico,

blue





Canada, yellow



Each cell contains one or more blocks.



MDC Syntax

ORGANIZE BY clause in CREATE TABLE

CREATE TABLE mdctable (Year INT,Nation CHAR(25),Colour VARCHAR(10),... )ORGANIZE BY (Year, Nation, Colour)

This MDC table will have four block indexes:

– Three dimension block indexes: Year, Nation and Colour

– One composite block index: (Year, Nation, Colour)



MDC Syntax

DB2_MDC_ROLLOUT registry variable

– 1, TRUE, ON, YES, IMMEDIATE (default)

– 0, FALSE, OFF, NO

– DEFER

Delete statement special register

– SET CURRENT ROLLOUT MODE IMMEDIATE CLEANUP

– SET CURRENT ROLLOUT MODE NONE

– SET CURRENT ROLLOUT MODE DEFERRED CLEANUP



MDC Benefits

Improved query performance

– Block indexes are much smaller than row-level indexes

– Data is guaranteed to be clustered

– Prefetching is more efficient with MDC tables

Reduced logging

– Inserts are not logged unless a new block is needed

– Mass deletes (rollouts) of entire cells log less data than regular deletes



MDC Benefits

Reduced table maintenance

– Clustering maintained automatically

– No need for reorg unless to reclaim space

Reduced application dependence on clustering indexes

– No need to reference columns in particular order for optimum usage



MDC Usage Considerations

Performance – Best suited for data warehouses where queries are complex and

long-running

– Good for OLTP environments, but some update operations on MDC tables may take longer than on regular tables

Disk space– MDC tables takes more space than equivalent regular tables

Table design– Poor selection of clustering key may lead to wasted disk space and

no performance gain



References

DB2 V9.7 Documentation

– http://publib.boulder.ibm.com/infocenter/db2luw/v9r7/topic/com.ibm.db2.luw.admin.partition.doc/doc/c0007201.html

Database Partitioning, Table Partitioning and MDC for DB2 9

– http://www.redbooks.ibm.com/abstracts/SG247467.html

Technology

Multi-Dimensional Clustering: A High-Level Overview