Spot db consistency checking and optimization in spatial database

SPOT DATABASES: EFFICIENT
CONSISTENCY CHECKING AND
OPTIMISTIC SELECTION IN
PROBABILISTIC SPATIAL
DATABASES
Presented By : Pratik S. Udapure

Agenda
 Introduction
 Optimization
 Spatial Indexes
 Spatial Query
 SQL examples
 Features of Spatial Databases
 Advantages of Spatial Databases
 Disadvantages of Spatial Databases
 Conclusion

Introduction
 Spatial database: is a database that is
optimized to store and query data that
represents objects defined in a geometric
space
 It offers additional functions that allow
processing spatial data types.
 Geometry.
 Geography.

Introduction Cont.
 Spatial Objects: Consists of lines, surfaces,
volumes and higher dimension objects that are
used in applications of computer-aided design,
cartography, geographic information systems.
 Spatial Data: The values of the objects spatial
attributes (length, configuration, perimeter,
area, volume, etc.)

Optimization:
 Optimizing spatial databases means
optimizing the queries, which requires less
time spent by running the queries before
receiving an answer.

Spatial Indexes
 Indexing Spatial Data: a mechanism to decrease the
number of searches (optimize spatial queries).
 A Spatial Index is used to locate objects in the
same area of data or from different locations
 Spatial indexes include:
 Grid index
 Z-order
 Octree
 Quadtree
 UB-tree
 R-tree
 kd-tree
 M-tree

Spatial Indexes: Grid Index
In the context of a Spatial Index, a grid (a.k.a. "mesh", also
"global grid" if it covers the entire surface of the globe) is a
regular division of a 2-D surface that divides it into a series
of contiguous cells, which can then be assigned unique
identifiers and used for spatial indexing purposes.

Spatial Indexes: Z-Order
 In mathematical analysis and computer
science, Z-order, Morton order, or Morton code
is a function which maps multidimensional
data to one dimension while preserving locality
of the data points.

Spatial Indexes: Octree
An octree is a tree data structure in which each
internal node has exactly eight childern. Octrees
are most often used to partition a three dimensional
space by recursively subdividing it into eight octants

Spatial Indexes: Quad Tree
 A quadtree is a tree data structure in which
each internal node has exactly four children.
Quadtrees are most often used to partition a
two-dimensional space by recursively
subdividing it into four quadrants or regions.

Spatial Indexes: UB Tree
 The UB-tree as proposed by Rudolf Bayer and Volker
Markl is a balanced tree for storing and efficiently
retrieving multidimensional data. It is basically a B+tree
(information only in the leaves) with records stored
according to z-order, also called Morton order. Z-order is
simply calculated by bitwise interlacing the keys.

Spatial Indexes: R Tree
 R-trees are tree data structure used for spatial
access methods,i.e., for indexing multi-
dimensional information such as geographical
coordinates, rectangles or polygons.

Spatial Indexes: KD Tree
 The k-d tree is a binary tree in which every node
is a k-dimensional point. Every non-leaf node can
be thought of as implicitly generating a splitting
hyperlane that divides the space into two parts,

Spatial Indexes: M Tree
 M-trees are tree data structure that are similar to
R-trees and B-trees. As in any Tree-based data
structure, the M-Tree is composed of Nodes and
Leaves. In each node there is a data object that
identifies it uniquely and a pointer to a sub-tree
where its children reside. Every leaf has several

Spatial Query
 A spatial query is a special type of database
query supported by geo databases and spatial
databases
 Some of the most important are that they allow
for the use of geometry data types such as
points, lines and polygons and that these
queries consider the spatial relationship
between these geometries.

SQL example
 Create “pubs” table
create table pubs (name varchar,
beer-price float4);
addgeometrycolumn(‘beer-db’,'pubs','location’
,2167,'POINT',3);

Insert data
insert into pubs values ('Garricks Head',4.50,
GeometryFromText('POINT (1196131 383324)’,2167));

Perform Query
 select name, beer-price, distance(location,
GeometryFromText('POINT(1195722 383854)',2167))
from pubs order by beer-price;
 name | beer-price | distance
 ---------------+------------+------------------
 Fireside | 4.25 | 1484.10275160491
 The Forge | 4.33 | 1533.06561109862
 Rumours | 4.46 | 2042.00094093097
 Garricks Head | 4.5 | 669.389105609889
 Slap Happy | 4.5 | 1882.31910168298
 Old Bailys | 4.55 | 1147.20900404641
 Black Sheep | 4.66 | 536.859935972633
 Big Bad Daves | 4.75 | 907.446543878884

Features of spatial databases
 Spatial Measurements: Computes line length, polygon
area, the distance between geometries, etc.
 Spatial Functions: Modify existing features to create new
ones, for example by providing a buffer around them,
intersecting features, etc.
 Spatial Predicates: Allows true/false queries about
spatial relationships between geometries. Examples
include "do two polygons overlap" or 'is there a
residence located within a mile of the area we are
planning to build the landfill?'
 Geometry Constructors: Creates new geometries,
usually by specifying the vertices (points or nodes)
which define the shape.
 Observer Functions: Queries which return specific
information about a feature such as the location of the
center of a circle

Advantages of Spatial
Databases
Able to treat your spatial data like anything else in the DB
 transactions
 backups
 integrity checks
 less data redundancy
 fundamental organization and operations handled by the DB
 multi-user support
 security/access control
 locking

Advantages cont.
Spatial querying using SQL
 use simple SQL expressions to determine spatial
relationships
 distance
 adjacency
 containment
 use simple SQL expressions to perform spatial
operations
 area
 length
 intersection
 union
 buffer

Disadvantages of Spatial
Databases
 Cost to implement can be high
 Some inflexibility
 Incompatibilities with some GIS software
 Slower than local, specialized data structures
 User/managerial inexperience and caution

Conclusion
 Spatial Databases are widely used nowadays.
 Optimizing Spatial Databases is of a
significant importance.
 Spatial databases can be optimized using
spatial indexes like R-tree or Quadtree and
other indexing structures.
 Big career opportunities in Spatial DB sector
in developing GIS software

Spot db consistency checking and optimization in spatial database

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