1 Copyright © 2011, Oracle and/or its affiliates. All ... · Author: Oracle $Jayant Sharma & Siva Ravada$ Subject: Oracle OpenWorld 2011 Presentation

$Page 1: 1 Copyright © 2011, Oracle and/or its affiliates. All ... · Author: Oracle $Jayant Sharma & Siva Ravada$ Subject: Oracle OpenWorld 2011 Presentation$
1 Copyright © 2011, Oracle and/or its affiliates. All rights reserved.


Oracle Spatial Technologies: Location Analysis for Better Business Solutions Jayant Sharma Siva Ravada Director, Prod. Mgmt. Director, Prod. Development

ORACLE PRODUCT

LOGO



Latin America 2011 December 6–8, 2011 Tokyo 2012

April 4–6, 2012


Oracle OpenWorld Bookstore

•  Visit the Oracle OpenWorld Bookstore for a fabulous selection of books on many of the conference topics and more!

•  Bookstore located at Moscone West, Level 2 •  All Books at 20% Discount


The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


Agenda

• Overview of Spatial • New Features in 11gR2 • Overview of Fusion Middleware MapViewer • New Features in FMW MapViewer • Discussion


Oracle’s Spatial Technologies Location Analysis for Better Business solutions


•  Business data that contains or describes location – Street and postal address (constituents, customers, warehouse) – Sales data (sales territory, customer registration, etc.) – Assets (cell tower, fire hydrant, electrical transformer, etc.) – Geographic features (roads, rivers, parks, etc.)

•  Anything connected to a physical location •  Every database in the world contains some form of

business data that can be leveraged using spatial technologies

What is spatial data?


Spatial Information Has Many Uses

Information Type Uses

Address Map customers, stores, and business relationships

Roads, facilities, infrastructure … Logistics planning, trace and manage fixed or mobile assets

Administrative areas (zip, tax, county, floodplain, real estate, sales territories...)

Summarize, Drill down, Map key performance indicators

Satellite imagery, 3D models Risk assessment, engineering planning, asset maintenance


Usage across industries Local Government

•  Jurisdiction

•  Tax assessment, zoning

•  Public facility planning

Financial Services

•  Insurance risk assessment

•  Mortgage, loan portfolio analysis

•  Retail branch site, service analysis

Consumer Packaged Goods

•  Product line market share analysis

•  Vending machine location, product mix

•  Marketing, promotions analytics

Healthcare

•  Service area, patient origination analysis

•  Provider network analysis

•  Tracking spread of disease

Real Estate

•  Appraisal/Risk assessment

•  Community, neighborhood profiles

•  Tenant mix analysis

Transportation, Utilities

•  Asset management

•  Workforce scheduling, management

•  Network and service planning


Natively manage all spatial content

Data

Points Lines

Polygons

Satellite Imagery Topologies 3D

f1

f2 n1 n2

e1

e2 e3

e4

Networks

Web Services (OGC)

Geocoding Routing


“Spatial” Tables

•  Just like regular tables • Contain a column of type SDO_GEOMETRY to store the

geometric shape of the objects

CREATE TABLE map_countries ( id NUMBER PRIMARY KEY, name VARCHAR2(30), geometry SDO_GEOMETRY);


Native Spatial Analyses

Address Geocoding

Linear Referencing

Raster Management

Oracle database Vehicle Routing

SELECT a.owner_name, a.acquisi6on_status FROM proper6es a, projects b WHERE sdo_within_distance (a.property_geom, b.project_geom, ‘distance = .1 unit = mile’) = ‘TRUE’ and b.project_id=189498;

Have we acquired rights-of-way for a proposed road widening project?

Network Tracing Spatial relationships

Proximity

Nearest Neighbors


Map data © NAVTEQ

Native Spatial Analysis

SELECT c.holding_company, c.location FROM competitor c, bank b WHERE b.site_id = 1604 AND SDO_WITHIN_DISTANCE( c.location, b.location, 'distance=2 unit=mile‘ ) = 'TRUE'

Find all competitors within 2 miles of Northport Branch


Oracle Locator vs Spatial

Topology Data Model Linear Referencing System

Spa6al Analy6c Func6ons

OGC Web Services

Native Spatial datatype Native Spatial index

Basic spatial queries Full projection support

GeoRaster Geocoder Routing Engine 3D Misc advanced spatial analyses

Oracle Locator

Oracle Spatial Option

Oracle Database

Enumerated in detail in the online Locator doc

http://download.oracle.com/docs/cd/B28359_01/appdev.111/b28400/sdo_locator.htm#i632018


OBIEE 11g

© 2010, NAVTEQ

Oracle Fusion CRM Sales

Phase Forward U6li6es Network Management System U6li6es Outage Analy6cs

Spatially Enabled Oracle Apps and Tools Oracle SQL Developer Oracle BI 11g Mobile


Oracle Exadata Extreme Performance for Spa8al Workloads

•  Oracle Spatial is architected to exploit the processing power, bandwidth, and parallelism of the Exadata Database Machine

•  Only Oracle Spatial is part of the Oracle Database kernel

•  Spatial operations can be performed in up to 2 Terabytes of Database System Global Area memory


Agenda



SPATIAL ENGINE


Spatial on Exadata

21

• We achieve performance improvements based on the exploitation of the processing power, bandwidth, and parallelism of the Exadata machine

•  Parallel query and partitioning help improve Spatial performance

•  Speedups of up to 100 times (compared to a 1-core CPU box) for the typical SDO_ANYINTERACT spatial query

•  Spatial predicates are not currently pushed into the Exadata storage nodes


Fast Coordinate System Transformations

22

•  SDO_CS.Transform is upto 10 times faster in 11gR2 –  This speedup is seen if 1000s of transformations are done in a

session –  This is typical for mapping applications where themes are

transformed at run time to match the base map SRID

•  In the prior releases, the transformation context was created for each transform() call –  now we use that context between transform() calls with the same

source and traget SRIDs

23 Copyright © 2011, Oracle and/or its affiliates. All rights reserved. 23

•  This computes a polygon that represents the area occupied by a set of points in the plane

•  Input geometry should be a 2D Geometry of any type –  This is typically a multipoint geometry

•  A concavehull is returned which is guaranteed to be a valid polygon (gtype 2003)

•  Very useful for generating trade areas from a given set of points of interest (e.g., customers)

•  This is different from convexhull

Concave Hull


Convex Hull vs Concave Hull


Transparent support for TTS

25

• Cross-Endian support for TTS and Spatial Index •  SDO_UTIL.PREPARE_FOR_TTS Deprecated

– When spatial data is transported as TTS, there is no need to do any special processing for Spatial indexes

–  This applies to any TTS export done with 11gR2 database

•  SDO_UTIL. INITIALIZE_INDEXES_FOR_TTS now automatically fixes the index if the TTS export is done in a different endian format than the target format


SQLDEVELOPER


SQL Developer Support for Spatial

•  Support for Spatial Data Management – Metadata creation –  Index creation – Validating the Spatial data – MapViewer metadata support

•  Support for Spatial Data Querying – Query results can be viewed graphically


Spatial Data Querying: Single Value •  Spatial shapes can be graphically viewed


Spatial data querying: Map View Display

•  Secondary queries are overlaid

Here we show the counties in California over the States layer


NETWORK DATA MODEL


Oracle Spatial Network Data Model •  An open data model to store and analyze network data. •  Network analyses include:

•  Shortest path •  Nearest neighbor •  Within cost •  Minimum cost spanning tree •  Traveling salesman problem •  Reachable/Reaching nodes •  K-shortest paths


Partitioned Networks •  Smaller partition boundaries in denser portions of the

network (urban areas). •  The number of nodes in each partition is still balanced. •  Load partitions

as needed


Sample Application: Shortest Path Analysis 747 Howard Street, San Francisco, CA 1099 Lombard Street, San Francisco, CA

5% on link 1234567 10% on link 89101112

Path consisting 500 nodes [….] and 499 links [….]

Street Addresses

Network Nodes and Links

Path Represented in Nodes and Links

Geocoder

NDM Analysis API: Shortest Path

Path Displayed On Map

Path geometry is …. Path Geometry

NDM Network IO API: Read Spatial Path

Oracle Maps Java Script API



NDM Customization -  Network constraints

- Trucking restrictions - Turn restrictions - Avoid toll road - Avoid/use Highway

-  Multiple Cost calculators - Travel distance - Travel time - Local/Highway/Scenic Drive preference - Penalty of road under construction/traffic congestion

-  Goal nodes - Restaurants within 10 min’s drive


Multiple Cost Support in Path Analysis

•  Path/Subpath analysis now supports multiple costs in a single analysis

•  First cost is the one NDM optimizes •  Second cost can be returned as an accumulated

value •  Examples

– Shortest distance paths with travel time –  Fastest paths with travel distance


Hierarchical A* shortest path Analysis

•  Support A* shortest path algorithm •  Provide user defined heuristic cost function •  Support hierarchical shortest path analysis •  Better performance than Dijkstra Algorithm as less

number of nodes are explored – Uses much less memory than Dijkstra


Traveling Sales Man (TSP) Analysis

• Minimum cost tour that includes all given nodes •  Support Points on Network as nodes to be visited • Node visit order can be enforced using network

constraints •  This is useful scheduling problems where a service

representative has to visit a number of customers


Drive Time Polygon Generation

•  A spatial representation (polygon) based on minimum cost network coverage

• Concavehull polygon or convexhull polygon (accuracy and performance)

•  Example – Compute Drive Time Polygon (with travel time as link cost) from

a service station – Use the polygon to determine if a given address can be reached

within a given time using point in polygon operation


Routing with Traffic Patterns •  Fastest Routes are based on speed limits

–  Not very accurate during rush hours – A good non-rush route can be the worst rush route!

•  Traffic Patterns are historical traffic speeds on roads – Can be further classified as speeds on Mon-Thur. Fri. Sat. Sun.

holidays, and special events at 15 min, 30 min, 60 min intervals.

• Need to add temporal dimension (start time) in routing with traffic patterns


Routing with Traffic Patterns • Model Traffic Patterns as user data in NDM

– Neutral traffic pattern metadata and schema – Generate traffic pattern user data automatically – Currently Support NavTeq Traffic Patterns

•  Link Cost is now a time-dependent function returning actual travel time – Start time determines which set of traffic pattern

•  (M-T,Fri.Sat. Sun. Holidays) –  Link distance/Link speed limit (for non-covered links) – Actual Speeds from traffic patterns (interval in a day) – Actual Travel Time = Link Distance/Actual Speed


Routing with Traffic Patterns Fastest Routes at different Start Times

10 PM

8 AM


3D SUPPORT


3D in Spatial 11g

–  SDO_GEOMETRY (3D)

–  SDO_TIN

–  SDO_POINT_CLOUD 3D C

OO

RD

INAT

E S

YS

TEM

S

Types Building Models,..

Surface Modeling

Scene, Object Modeling

Efficient

Storage

Query

Analysis


SDO_GEOMETRY •  Points, Lines •  Simple Surfaces

–  All points of a surface lie in a 3D plane

•  Composite surfaces –  Has one or more connected simple surfaces –  Simple surfaces cannot cross

•  Simple Solids –  Composed of closed surfaces –  Can have interior surfaces

•  Composite Solids –  Consists of n connected simple solids –  Representation might be easier

•  Multi-points, -lines, -surfaces, -solids –  Multi-solid is different from composite solid


SDO_TIN


Raw LiDAR Point Cloud Color-scaled by elevation (red= high – blue=low)

Gate House

Spillway

Bridge


RGB 3D Point Cloud


GEORASTER


GeoRaster •  A data type to store raster data

– Satellite images, remote sensing data, digital elevation models

– An XML schema to store Metadata

•  Functionality –  storage and indexing of raster data – Generate resolution pyramid –  query and analysis –  delivery to external consumers

•  Publish as JPEG, GIFF images


ETL tool – the GDAL GeoRaster Driver

• GDAL is the best open source geospatial ETL tool/API for raster data –  natively supports import/export to/from SDO_GEORASTER and

many formats including GeoTIFF, JPEG2000, ECW, NITF, HDF, NetCDF, ERDAS IMG, USGS DEM, SPOT.

– C/C++, Java, Python API for accessing GeoRaster – many tools. Two of the important ones are:

• gdal_translate – utility to translate raster formats to/from GeoRaster objects

• gdalinfo – utility to view information about a raster, such as a GeoRaster object


Georeferencing Using GCP •  Georeferencing is the process of mapping pixels on the image to

ground coordinates •  GCP: stands for Ground Control Points •  GCP Model: GeoRaster supports a generic GCP model. In the

current release, 2D cell coordinates, 2D and 3D model coordinates are supported.

•  GCP Storage: GeoRaster defines a GCP XML schema and can (optionally) store GCP natively in the metadata of GeoRaster objects.

•  GCP Manipulation: GeoRaster provides a set of update and query functions to manipulate GCP’s and related data


The GeoRaster Java API

•  Sample Applications: using this Java API, users can easily develop simple applications, particularly web-based applications. GeoRaster viewer is a simple application built with this API.

Tools.java Viewer.java Loader.java Exporter.java


The GeoRaster Java API •  The GeoRaster JAVA API

–  oracle.spatial.georaster: Map SDO_GEORASTER object type to Java objects, support for the core GeoRaster features

–  oracle.spatial.georaster.sql: Java wrapper of the GeoRaster PL/SQL API for some server-side operations

–  oracle.spatial.georaster.image: For generating Java images from a GeoRaster object and for processing the images

•  The image package is based on Java 2D and JAI –  users can leverage all advanced capabilities of Java 2D and JAI

for developing web or image processing applications


•  SDO_GEOR.reproject: transform from one projection to another •  All oracle spatial coordinate systems are supported •  Five re-sampling methods are supported •  NN, Bilinear, Cubic, Avarage4 and Average16.

•  Supports two options •  Reproject persistently: reproject a GeoRaster object and store the

result as a new GeoRaster. •  Reproject on-the-fly: equivalent to getRasterSubset except the

window-based cropping result is transformed into a different projection. The result is stored as a single BLOB.

Raster CS Transformations


From: SRID 26986 "NAD83 / Massachusetts Island"

To: SRID 26988 "NAD83 / Michigan North"

sdo_geor.reproject ( gr1, 'resampling=cubic', ‘blocksize=(256,256,3) interleaving=BIP', 26988, gr2 );

Raster Reprojection Example


Polygon-based Raster Clipping

SDO_GEOR.getRasterSusbet –  Lets users clip the query result along the polygon (irregular)

boundary


Agenda



• A J2EE component (.ear) for developing web mappingapplications. Usually deployed in WLS. Free (with iAS,WLS, or ADF runtime)

• Renders data from Oracle Spatial (also WMS,WFS, .shp). Background can be from 3rd party providers

• JavaScript, Java, and XML APIs for web mappingapplications

Oracle Fusion Middleware MapViewer



Mapviewer facilitates different options

•  For content –  Local (Oracle database) – Online web services – Hybrid (local database + online content)

•  For development –  Java or javascript code embedded in application – Using ADF Faces (<dvt:map>) GeoMap component


MapViewer renders application data on a map


Or application data on background maps from online services


It lets users display and interact with BI content


SOME NEW FEATURES IN MAPVIEWER


Some new features •  FOI aggregation • Opacity for layers, themes, FOIs •  External tile layers via metadata •  Support for WMS with Authentication • MVFoiGroup (set visibility, opacity as a group)


FOI aggregation

Multiple FOIs at the same location are displayed with a specified marker. On hover a hyperlinked list of IDs is shown. Clicking on an ID brings up FOI info-window.


Theme or FOI Opacity


Background maps via metadata

GUI op8on to select map source in MapViewer

Enter clientID obtained from Google Maps Enterprise


WMS with Authentication


Summary

•  Location information is a key part of managing any business

• Oracle applications, analysis and reporting tools can query, manage, and display location information

• Useful across various industries: e.g. public sector, banking, insurance, retail, telecomm, healthcare

• Maps convey complex information and context compactly and effectively


The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.


Q&A



Documents

1 Copyright © 2011, Oracle and/or its affiliates. All ... · Author: Oracle \(Jayant Sharma & Siva Ravada\) Subject: Oracle OpenWorld 2011 Presentation