nsf industry/university cooperative research center high performance database research center...
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![Page 1: NSF Industry/University Cooperative Research Center High Performance Database Research Center Naphtali D. Rishe, Director, rishe@fiu.edu HPDRC.FIU.edu](https://reader035.vdocument.in/reader035/viewer/2022062518/5697bf741a28abf838c7f9bb/html5/thumbnails/1.jpg)
NSF Industry/University Cooperative Research Center
High Performance Database Research CenterNaphtali D. Rishe, Director, [email protected] TerraFly.com
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HPDRC Expertise:HPDRC Expertise:
• Data visualization
• Spatial databases
• Internet-distributed heterogeneous databases
• Database design methodologies
• Information analysis
• GIS
• Location Data
• Health Informatics
Director: Dr. Naphtali David Rishe Director: Dr. Naphtali David Rishe
The Inaugural Outstanding University Professor of FIU
Awards: $40M, Patents: 4, Books: 4, Papers: 250
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GIS Solutions Based On Geo-Spatial Research GIS Solutions Based On Geo-Spatial Research TechnologyTechnology• Next generation GIS: Internet geo-visualization & spatial
cloud-computing platform and service
• Advanced geo-spatial computing engine
• Open architecture, API provided
• 40 TB database of aerial imagery and spatial data
• Rich datasets in a user-friendly environment
• Professionally customizable to domain requirements
• NASA, NSF, IBM and USGS funded technology
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Web-BasedWeb-BasedWeb-BasedWeb-Based
Open Architecture APIOpen Architecture APIOpen Architecture APIOpen Architecture API
Geo-Spatial Mapping SolutionGeo-Spatial Mapping SolutionGeo-Spatial Mapping SolutionGeo-Spatial Mapping Solution
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Address LocatorAddress LocatorAddress LocatorAddress Locator
Vicinity InformationVicinity InformationVicinity InformationVicinity Information
Demographic DataDemographic DataDemographic DataDemographic Data
Nationwide Layers: 2000 US Census, Businesses, Schools, Travel, Features (airports, heliports, public buildings, churches, hospitals, libraries, post offices, towers, tunnels, water, etc.), Property Lines and much more
Nationwide Layers: 2000 US Census, Businesses, Schools, Travel, Features (airports, heliports, public buildings, churches, hospitals, libraries, post offices, towers, tunnels, water, etc.), Property Lines and much more
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Your System Your System Your DataYour Data
TerraFly TerraFly systemsystem
TerraFly TerraFly IntegrationIntegration
Solution Solution
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Query Date Range
Time Series
Animation Player
Census Block
Groups are Selectable
Layer Control
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MapReduce use casesMapReduce use cases● Spatial data indexing [SSDBM’09]● Geospatial query support [SSDBM’10]● Parallel spatial data processing
[GrC’10]● Parallel set-similarity spatial joins● Real Estate data analytics
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● Objective: Provide computational analytics for estimating how an event influences property values
● Dataset: Miami-Dade county records (~ 20M)● Community Boundaries: U.S. Census Blocks and Tracts
(polygons)● Property transaction geo-database: Join of property
public records (Deeds, Tax Roll)
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Parcel
Date Value Area Type Location
...
1001 03-10-2005 100K 840 Condo 1,2
1002 03-15-2005 130K 2000 Single-Family 2,3
1003 12-22-2005 80K 1085 Single-Family 2,2
… … … … … …
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● MethodMethod• Virtual Community (VC): a set of homes with similar
characteristics within a geographical area• Consider unit price per VC, e.g. median of $/sq-foot• Compute VC’s unit price rate change to compare communities• Hadoop MapReduce: Temporal, in parallel, self-join of the
dataset to compute property value rate change
Parcel Date Value … Loc.
1001 03-10-2005 100K 1,2
1002 03-15-2005 130K 2,3
1003 05-22-2005 80K 3,2
1004 06-20-2005 80K 4,2
1005 07-10-2006 100K 5,2
1006 03-15-2005 130K 6,3
1007 12-22-2005 80K 7,2
1008 12-22-2005 80K 8,2
… … … …
9000 03-15-2005 130K 9,3
9001 12-22-2005 80K 9,2
9002 01-22-2006 80K 2,2
9003 02-10-2006 100K 1,2
9004 03-15-2005 130K 2,3
9005 12-22-2005 80K 2,2
9006 12-22-2005 80K 9,2
Reduce
Map
Map
(Partitions records by: Community, Type, Date)
(Computes community values and change
rate)
…
Reduce
…
Community Rate Value …
300 -10% 100
301 -60% 80
302 15% 55
303 2% 60
… … …
Input: dataset, tstart, tend
Output: Community value change rate
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Hurricane Andrew, August 1992, Q2’92 vs. Q4’92
Drop
Raise
No change
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