Software Group – Spatial Information Management © 2004 IBM Corporation Putting the world in your...

Software Group – Spatial Information Management

© 2004 IBM Corporation

Putting the world in your Database:The Informix Spatial and Geodetic DataBlades

Robert UlemanConsulting IT SpecialistWorldwide Information Management Sales Support – Spatiotemporal Technology


© 2003 IBM Corporation2

Agenda

Overview– GIS: Geographic Information Systems– Spatial data in an object-relational DBMS– The Spatial DataBlade– Competitive differences

Details– Spatial SQL syntax– Spatial indexing– Geodetic: round-earth spatial



Geographic Information System





GIS Application

GIS Application

SQL

Proprietarydata format1st Generation:

2nd Generation:

3rd Generation:SQL

ProprietaryGIS API

ProprietaryGIS APIGIS

Application

GIS Application

GIS Application

GIS Application

FileSyste

m

FileSyste

m

GIS Data

Engin

e

GIS Data

Engin

eRDBMSRDBMS

“Spatial” Application

“Spatial” Application

Architectural Evolution of GIS Data Management

Spatially enabled DBMS

Spatially enabled DBMS

RDBMSRDBMSSQL

Spatial features, indexes in

BLOBs

Attributes

GIS Data

Engin

e

GIS Data

Engin

e

Spatial types functions indexes

Spatial Features

Proprietaryspatial

structures

Open or proprietary

Open

Spatial business logicSpatial business logic



What’s Special about Spatial?

Traditionally not supported by relational databases Requires new indexing techniques Voluminous data

– Individual values can get arbitrarily large:• Large, convoluted lines and polygons (e.g., a coastline)• Raster images

– Lots of features Maps can effectively represent lots of information

– Much more than spreadsheets or reports– Queries often retrieve many more rows than “normal”

queries Individual operations may be computationally expensive

– WHERE clause predicates Transactions generally long, unlike OLTP

– Resembles code revision control in software development



Extender/DataBlade Introduction: Component Technology

ConnectivityConnectivity BackupBackup RestoreRestoreServer SubsystemsServer Subsystems

IDSIDSIDSIDSSpatialGeodetic

GridYour idea goes here

SpatialGeodetic

GridYour idea goes here



Extender/DataBlade Elements

TypesTypes

FunctionsFunctions

CastsCasts

AggregatesAggregates

IndexesIndexes

TablesTables

Client CodeClient Code

New New Extender/Extender/DataBladeDataBlade

New New Extender/Extender/DataBladeDataBlade



If Integer were not built in …

Domain– Whole numbers, up to some maximum magnitude

Data types– Smallint, Integer, Bigint– Representations: ASCII ([+|-]d..),

binary (2’s complement, byte order)Functions and operators

– Add(+), Subtract(-), Multiply(*), Abs, Mod, …– Equal(=), LessThan(<), GreaterThanOrEqual(>=), …

Index support– B-Tree



Integer not built in? Not so far-fetched

Illustra: Pure object-relational database– Commercialization of UC Berkeley Postgres project– Acquired by Informix in 1996, Informix acquired by IBM in 2001– Postgres continues as open-source PostgreSQL– No built-in data types; everything is bound at runtime

Land Information New Zealand: Fraction data type “5/7”– Avoid roundoff in cumulative subdivision of property– Legally mandated improvement in area/tax calculation precision

Dates– Birthdate: understands that February 28 is a birthday for

someone born on February 29– Tradingdate: skips weekends, holidays



User-Defined Data Types

compensation locationname jobs_held

CREATE TABLE employee (name varchar(30),compensation salary_t,location point,jobs_held set(varchar(30)),picture image

);

John T. Smith (123 256) Clerk, Administrator, Manager

image

349,876 yen

Data Type: Descriptor assigned to a column or a variable



Some SQL Queries Location-Based Services: List Points of Interest

– SELECT name, description, addressFROM restaurantsWHERE Overlaps(location, box(getGPS(), 2000, 2000))AND category = ‘chinese’AND docContains(menu, ‘Peking duck’);

List volcanic eruptions in a region of interest– SELECT name, year, mag, locationFROM volcanoWHERE ST_Within(location,'polygon((-125 43,-125 46,-120 46,-120 43,-125 43))')ORDER BY name, year;

name year mag location HOOD MOUNT 1854 0 POINT (-121.69999 45.36000) HOOD MOUNT 1859 2 POINT (-121.69999 45.36000)

Name Description AddressDynastie Chinese restaurant in

glass pyramidMisburger Str. 81



OpenGIS Standard Spatial Types and Functions– Certified compliant with OpenGIS Simple Features Specification

– Geometric data types

• ST_Point, ST_Linestring, ST_Polygon, ST_Geometry, etc.

– Spatial functions

• ST_Distance, ST_Intersects, ST_Within, etc.

– Standard Data representations

• Well-Known Binary, Well-Known Text, ESRI Shape Tailored to ESRI’s ArcSDE 9.x (spatial database gateway)

– Additional functions, support for annotation, SDE format, etc.

– Based on ESRI’s geometry engine (Shape library)

– Consistent results of spatial operations in all software tiers: database, middle (ArcSDE), client (ArcGIS, ArcIMS)

The Informix Spatial DataBlade



DB2 Spatial Extender, IDS Spatial DataBlade

Developed, supported and maintained by IBM

– Wrapped around ESRI’s geometry engine (Shape library)

– Spatial index: R-tree

– Spatially aware optimizer

• Recognizes spatial operators and index

• Cost, selectivity provided by R-tree

– Administration tools: Blade Manager

– Utilities: Shape file import, export

Strategic alliance with ESRI

– Close relationship in engineering, marketing, and sales

– Software (Data, WebSphere), Hardware, Services



Spatial/OpenGIS SQL Data Types

ST_Geometry

ST_Curve ST_SurfaceST_Geom-Collection

ST_Multi-Surface

ST_Multi-Curve

ST_LineString ST_Polygon

ST_Point

ST_Multi-Polygon

ST_Multi-LineString

ST_Multi-Point

“Abstract” Classes

Instantiable Classes



OpenGIS Spatial SQL Functions

ST_Intersects(geometry1,geometry2)

?



ClientClient

SDE SDE Client APIClient API

ArcGIS Family

Open API

ApplicationApplication

ArcSDEArcSDEServerServer

IDS

SQL SQL ApplicationsApplications

Spatial DataBlade

ArcSDE Architecture for Informix

R-tree index

ODBCODBC

OpenGISSpatialQueries

CachingCompression Connection pooling(Projections)(Long transactions)(Raster support)

ESQL/CODBCJDBC

TCP/IPTCP/IP

Geodatabase, business rules, custom types

ArcExplorerArcExplorer

JDBC



FATArcSDEServer

<nothing>

ArcSDE Architecture for Others

SQL Applications

ArcSDEServer

Oracle

Oracle Spatial

Index tables

SQL Applications

NO SpatialQueries

OracleSpatialQueries

ArcSDEServer

Informix

Spatial DataBlade

SQL Applications

OpenGISSpatialQueries

SQLServer,Oracle “binary”



The Informix Spatial Advantage Standard, intuitive syntax

– Easy development, maintainable, fewer bugs

– Result of true Object-Relational extensibility

– OpenGIS Simple Features conformance for interoperability with other compliant systems

Performance

– Spatial index and functions integrated into server at code interface level, not based on tables and SQL

Tight cooperation and integration with ESRI



SQL Comparisons: Query

Oracle SpatialSELECT A.Feature_IDFROM TARGET AWHERE

sdo_relate( A.shape, mdsys.sdo_geometry( 2003, NULL, NULL, mdsys.sdo_elem_info_array( 1,1003,1 ), mdsys.sdo_ordinate_array( x1,y1, x2,y2, x3,y3, x4,y4, … ) ), 'mask=anyinteract querytype=window‘) = 'TRUE‘

;

DB2 SpatialSELECT A.Feature_IDFROM AWHERE

ST_Overlaps( A.shape, ST_GeomFromText( ‘ST_POLYGON( x1 y1, x2 y2, x3 y3, x4 y4 … )’, 5 -- OpenGIS requirement ))

;



Spatial queries

Compute the percentage overlap of imagery that covers part of a region of interest

– ROI = Ontario Province, with 25 km buffer, but only over Canada

SELECT i.id AS image_id, ST_Area(ST_MultiPolygon ST_Intersection( i.footprint, p.shape ) ::ST_Polygon ) / ST_Area( i.footprint ) * 100 AS "%overlap"FROM images i, provinces pWHERE ST_Overlaps( i.footprint, ST_Difference( ST_Buffer( p.shape, 25, 'KILOMETRE' ), (SELECT shape FROM countries WHERE name = 'USA')) AND p.name = 'Ontario'ORDER BY 2 DESC;



The B-tree index

A through Z

A - I S - Z

A - B C - E P - R Sq - U

B-tree indexes rapidly reduce the number of items to search through in a selection process and are the industry standard for alpha-numeric data. But how can spatial data be sorted???

J - R

F - I M - OJ - L S - Sp V - Z

“Polygon”

N2

N1

K8 K9

L4

K8

K9

L5

K10

K11

N1 N2

L4 L5

K10 K11

A Simple R-treeK = Key bounding boxL = Leaf node bounding boxN = Node (internal) bounding box

L1

L2 L3

L1 L2

K1

K1

K2

K4

K3

K5

K6 K7

L3

K5 K6 K7K2 K3 K3 K4

Data space

Index structure

SearchObject



Planar Coordinates

500,000

5,000,000

Northing

Easting



longitude

latitude

0

-90(90° W)

+90(90° N)

R

Spherical Coordinates



Flattening the Earth

Plane Geometry on lat-long

– Singularities and scale distortion at and toward the poles

– Wrap-aroundat 180º longitude

– Poor location of lines, edges, intersections

Local/Regional Projections

– Limited valid range

– Map edge-matching problems

– Non-uniform scale

Indexing: it gets worse!

– Multiple “bounding boxes” or complete loss of selectivity

UTM 32

UTM 33

?

?

?

?

0

0-180 +180-90

+90



FLAT

0° ±180°±180°

Single bounding box: high

selectivity, low

complexity

+180-180 0 +90-90-90

0

+90

Y↑

→ X

Single bounding strip: low selectivity

Split bounding

boxes: high complexity

ROUND



Geodetic DataBlade/Extender Latitude-longitude (‘geodetic’) coordinates, ellipsoidal datum

Uniform accuracy and resolution around the globe (“world to cm”)

No scale singularities and map edges

Based on Hipparchus geometry engine by Geodyssey Ltd.

Integrated time and floating-point dimensions for single-index searches and true spatio-temporal data management

Powerful indexes for high performance:

– Voronoi Tessellation – adaptive space partitioning

– R-tree – self-tuning multidimensional index (up to 5 dimensions)

Unique to IBM



Connect the dots...

Flat plane: line segmentsconnecting vertices are

straight lines

Ellipsoid: line segmentsconnecting vertices are

geodesics



Connect the dots, continued

parallels

meridians

Add vertices if you want a line segmentto follow a parallel (line of constant

latitude)



Distances

What is the distance from Anchorage to Tokyo?

The shortest path is the shorter of thetwo possible geodesic paths:the thick part of the great circle



Polygons that straddle the 180th meridiansplit flat-plane representation into 2 or more pieces

MULTIPOLYGON( ((-180 30,-165 30,-165 40, -180 40,-180 30)), ((180 30,180 40,165 40, 165 30, 180 30)))

POLYGON( (165 30, -165 30, -165 40, 165 40))



Polygons that enclose a pole

extra vertex extra vertex extra edgeextra edge

POLYGON( (180 -60, -180 -60, -180 -90, 180 -90, -180 -60))

POLYGON( ( 0 -60, -120 -60, 120 -60, 0 -60))



HemispheresWestern hemisphere, flat-earth representation:

POLYGON((0 -90, 0 90, -180 90, 180 -90, 0 -90))

Western hemisphere, round-earth representation:

POLYGON((0 -30, 0 90, 180 -30))

1

2

3

4 1

23

Note that the same three points, specified in opposite order, define the eastern hemisphere

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