Transcript Indexing for Multidimensional Data

Indexing for Multidimensional
Data
An Introduction
Applications of
Multidimensional Databases
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Normal databases with multiple key
Spatial databases
Geographic information system (GIS)
Computer-aided design (CAD)
Multimedia databases
Medical applications
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Advanced Data Structures
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Characteristics of
Good Index Structures (1)
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Dynamic
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Handle necessary queries
• Insert, delete, and update data in any order
• Point or exact queries
• Range quesries
• Spatial queries
• Boolean queries
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Advanced Data Structures
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Characteristics of
Good Index Structures (2)
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Good performance (disk accesses,
running time, etc.) for
• Query, insert, delete
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Good storage (memory or disk)
utilization
• Low percentage of waste space
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Scalability
Simple
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Advanced Data Structures
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Why hierarchical structures
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Allow the search to be focused on
interesting subset of data
Eliminate useless search
Clean and simple implementation
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Advanced Data Structures
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Hierarchical index structures for
single attribute
B tree
B+ tree
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Binary tree
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Unbalanced
Organize data
Memory-based index
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Measuring the running
time
Practical mem. size
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N-ary tree
Height-balanced
Organize data space
Disk-based index
•
Measuring the number
of disk accesses
Disk page size
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B tree
10
4
20
7
6
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Advanced Data Structures
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B+ tree
16 31
6 11 14
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Handling multiple attributes (1)
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Separate index structure for each attributes
• Update all index structures for each record
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update.
Data are scattered in many disk pages.
a1
a2
a3
a4
disk
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Handling multiple attributes (2)
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Bit interleaving
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Attribute interleaving
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Multiple-attribute indexing
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Quad-tree
k-d tree
k-d-B tree
Grid file
hB-tree
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Spatial Indexing
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R-tree
R*-tree
SKD-tree
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Advanced Data Structures
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High-dimensional indexing
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SS-tree
TV-tree
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Advanced Data Structures
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