Indexing for Multidimensional Data

1
Indexing for Multidimensional Data

• An Introduction

2
Applications of Multidimensional Databases

• Normal databases with multiple key
• Spatial databases
• Geographic information system (GIS)
• Computer-aided design (CAD)
• Multimedia databases
• Medical applications

3
Characteristics of Good Index Structures (1)

• Dynamic
• Insert, delete, and update data in any order
• Handle necessary queries
• Point or exact queries
• Range quesries
• Spatial queries
• Boolean queries

4
Characteristics of Good Index Structures (2)

• Good performance (disk accesses, running time,
  etc.) for
• Query, insert, delete
• Good storage (memory or disk) utilization
• Low percentage of waste space
• Scalability
• Simple

5
Why hierarchical structures

• Allow the search to be focused on interesting
  subset of data
• Eliminate useless search
• Clean and simple implementation

6
Hierarchical index structures for single attribute

• B tree
• Binary tree
• Unbalanced
• Organize data
• Memory-based index
• Measuring the running time
• Practical mem. size

• B tree
• N-ary tree
• Height-balanced
• Organize data space
• Disk-based index
• Measuring the number of disk accesses
• Disk page size

7
B tree
10
4
20
7
9
6
8
B tree
9
Handling multiple attributes (1)

• Separate index structure for each attributes
• Update all index structures for each record
  update.
• Data are scattered in many disk pages.

a1
a2
a3
a4
disk
10
Handling multiple attributes (2)

• Bit interleaving
• Attribute interleaving

11
Multiple-attribute indexing

• Quad-tree
• k-d tree
• k-d-B tree
• Grid file
• hB-tree

12
Spatial Indexing

• R-tree
• R-tree
• SKD-tree

13
High-dimensional indexing

• SS-tree
• TV-tree