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Graph Gurus Episode 8
Location, Location, Location:
Geospatial Analysis with A Native Parallel Graph Database
© 2018 TigerGraph. All Rights Reserved
Welcome
● Attendees are muted but you can talk to us via Chat in Zoom
● Send questions at any time using the Q&A tab in the Zoom menu
● We will have 10 min for Q&A at the end
● The webinar will be recorded and sent via email
● A link to the presentation and reproducible steps will be emailed
2
ZOOM ISSUES: update to the latest version of Zoom and if you are using
multiple monitors disable “use dual monitors” in settings
© 2018 TigerGraph. All Rights Reserved
Developer Edition Available
We now offer Docker versions and VirtualBox versions of the TigerGraph
Developer Edition, so you can now run on
● MacOS
● Windows 10
● Linux
Developer Edition Download https://www.tigergraph.com/developer/
3
© 2018 TigerGraph. All Rights Reserved
Today's Gurus
4
Emma Liu
Product Manager
● BS in Engineering from Harvey
Mudd College, MS in Engineering
Systems from MIT
● Prior work experience at Oracle
and MarkLogic
● Focus - Cloud, Containers,
Enterprise Infra, Monitoring,
Management, Connectors
Xinyu Chang
Solution Team Lead
● 4 Years with TigerGraph
● Co-authored GSQL
● Created solutions for most
major customers
● Expert in graph solutions and
algorithms
© 2018 TigerGraph. All Rights Reserved© 2018 TigerGraph. All Rights Reserved
Agenda
● GeoSpatial Use Case
● Geospatial Search with Graph Database
● Why TigerGraph for GeoSpatial Analytics?
● GeoGraph Concepts and Definitions
● GeoGraph Design and Implementation
● GeoGraph Demo
5
© 2018 TigerGraph. All Rights Reserved 6
Traffic Inflow
(predicted)
Traffic Outflow (predicted)
Saturday, 11:15 pm Japan Standard Time
Number of Taxis needed: 105
Number of Taxis available: 65
Geospatial Operational Analytics
Example: Real-time Taxi Positioning
© 2018 TigerGraph. All Rights Reserved
40
Matching Demand & Supply
with Predicted Traffic Flow Data For Busy Locations
78 96 120 92
45 45 80 29
45 323445
60
35
17
54
35
14
79 25 72
45 35 44 57
89 648745
45
98
34
65
35
78
78 85 78 45 45 35 98 64 33 63 654 69
Input Driver
Suggested Moving direction
120
In Flow
40
Out Flow
Flow Prediction Based on
Historical data
40
Number of Taxis in
that mesh
© 2018 TigerGraph. All Rights Reserved 8
Develop Location-Based Customer 360 Profiles
© 2018 TigerGraph. All Rights Reserved
Recommendation
Similar Users With
Similar Movement
Pattern
= Grid
Input User
Geo-Temporal Patterns for Recommendation
© 2018 TigerGraph. All Rights Reserved
GeoSpatial Analytics with Graph Database
11
Finding entities (nodes/edges) in a connected network
matching certain geolocation patterns
One More Dimension(s) to
Your Solution Space
© 2018 TigerGraph. All Rights
Reserved
Common GeoSpatial Questions
12
RDBMS
• Real World Challenge:
• Not designed for complex Geo
based search questions in real time
• Rely on third party index
• No easy SQL for answering these
questions
TigerGraph
• Real World Benefit:
• GeoSpatial data is on a graph
• Designed for discovery/exploratory
type of analytics
• GSQL can naturally and efficiently
express and solve the Geo search
queries
A. Who are the closest target entities (e.g., taxi drivers) to customer A?
B. Find all hospitals in real time which are within this region with Rh-negative blood type.
C. Find all doctors nearby who are specialists in congenital heart defects.
13
Why TigerGraph for GeoSpatial
Analytics?
Not Just Search, But
Real-time Geo Intelligence!
© 2018 TigerGraph. All Rights Reserved
Why TigerGraph for GeoSpatial Search?
Deep Link Analysis
in Physical World
• Geo Aware Multi Hop
Entity Relationship
• Native Parallel Graph
Enabled by MPP
Geo Enriched
Graph Applications
• GeoSpatial Intelligence
to All Use Cases
• Example: Smart Mobile
Location Based
Recommendation
14
• Movement at the
Same Time with
Many Entities
(People and Things)
• Continuous Big Data
Real-Time Geo
Insights
Unique TigerGraph Features
© 2018 TigerGraph. All Rights Reserved
GeoSpatial Search (Intelligence) with TigerGraph
15
Problem:
Finding entities
(nodes/edges) in a
connected network
matching certain
geolocation patterns
with movements
with continuously
increasing real time
data
Solution:
First and Only
OLAP and OLTP
Graph Database
16
GeoGraph In Depth
TigerGraph GeoSpatial Search Solution and Demo
Xinyu Chang, Solution Team Lead
© 2018 TigerGraph. All Rights Reserved
What is GeoGraph?
17
1. The earth is cut into a grid of
bounding boxes or cells.
2. Each box can be represented by a
vertex in the graph.
3. Each vertex has a predictable ID,
which is x + y*c, where c is the
number of columns.
4. Each object vertex is connected to
the corresponding geo location
vertex based on its coordinates.
© 2018 TigerGraph. All Rights Reserved
Graph Representation
18
123122 124
22 23 24
223222 224
Object
Object
Relationship
between objects
Location Edge
Geo Location Vertex Object
© 2018 TigerGraph. All Rights Reserved
R-Tree vs. Grid
19
R-Tree Approach
• Advantages:
Search for arbitrary regions, points
Allows us to estimate the number of dots in a
region without a full data scan
• Disadvantages:
Significant redundancy in the data storage
Slow update
Grid Approach
• Advantages:
Stored as vertices and edges, naturally
integrated with TIgerGraph System.
Do the analytics including geo in a MPP way.
Fast to update.
Easy to implement and maintain.
• Disadvantages:
Might have uneven distribution of objects on
each grid
© 2018 TigerGraph. All Rights Reserved
Example Dataset
California Healthcare Facility Locations
https://data.chhs.ca.gov/dataset/healthcare-facility-locations
City Zipcode and Location
https://www.aggdata.com/
© 2018 TigerGraph. All Rights Reserved
Graph Schema & Data Loading
21
Token Function getGridId:
Given latitude and longitude, return the id of the
grid vertex id.
© 2018 TigerGraph. All Rights Reserved
Graph Exploration & Queries
© 2018 TigerGraph. All Rights Reserved
Query Mechanism
Expression Function getNearbyGridId:
Given latitude, longitude and distance, return the nearby
grid vertex ids within distance.
Expression Function geoDistance:
Given two pairs of latitude and longitude, return the
distance between the two locations.
© 2018 TigerGraph. All Rights Reserved
Query Mechanism
User Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Geo
Grid
Facility
Facility
Facility
Facility
Facility
© 2018 TigerGraph. All Rights Reserved
Demo
Geospatial Search UI
http://54.88.6.143:14240/geo/#
GraphStudio UI
http://54.88.6.143:14240
26
Takeaways
© 2018 TigerGraph. All Rights Reserved
Summary
• Graph Database is a natural fit for Geospatial Analytics
• TigerGraph is designed from the ground up for fast
GeoSpatial Analytics
• GeoSpatial Analytics algorithms with GSQL Queries
• Graph Studio Demo for GeoSpatial Analytics
27
Q&A
Please send your questions via the Q&A menu in Zoom
28
© 2018 TigerGraph. All Rights Reserved
Additional Resources
29
New Developer Portal
https://www.tigergraph.com/developers/
Download the Developer Edition or Enterprise Free Trial
https://www.tigergraph.com/download/
Guru Scripts
https://github.com/tigergraph/ecosys/tree/master/guru_scripts
Join our Developer Forum
https://groups.google.com/a/opengsql.org/forum/#!forum/gsql-users
@TigerGraphDB youtube.com/tigergraph facebook.com/TigerGraphDB linkedin.com/company/TigerGraph

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Graph Gurus Episode 8: Location, Location, Location - Geospatial Analysis with a Native Parallel Graph Database

  • 1. Graph Gurus Episode 8 Location, Location, Location: Geospatial Analysis with A Native Parallel Graph Database
  • 2. © 2018 TigerGraph. All Rights Reserved Welcome ● Attendees are muted but you can talk to us via Chat in Zoom ● Send questions at any time using the Q&A tab in the Zoom menu ● We will have 10 min for Q&A at the end ● The webinar will be recorded and sent via email ● A link to the presentation and reproducible steps will be emailed 2 ZOOM ISSUES: update to the latest version of Zoom and if you are using multiple monitors disable “use dual monitors” in settings
  • 3. © 2018 TigerGraph. All Rights Reserved Developer Edition Available We now offer Docker versions and VirtualBox versions of the TigerGraph Developer Edition, so you can now run on ● MacOS ● Windows 10 ● Linux Developer Edition Download https://www.tigergraph.com/developer/ 3
  • 4. © 2018 TigerGraph. All Rights Reserved Today's Gurus 4 Emma Liu Product Manager ● BS in Engineering from Harvey Mudd College, MS in Engineering Systems from MIT ● Prior work experience at Oracle and MarkLogic ● Focus - Cloud, Containers, Enterprise Infra, Monitoring, Management, Connectors Xinyu Chang Solution Team Lead ● 4 Years with TigerGraph ● Co-authored GSQL ● Created solutions for most major customers ● Expert in graph solutions and algorithms
  • 5. © 2018 TigerGraph. All Rights Reserved© 2018 TigerGraph. All Rights Reserved Agenda ● GeoSpatial Use Case ● Geospatial Search with Graph Database ● Why TigerGraph for GeoSpatial Analytics? ● GeoGraph Concepts and Definitions ● GeoGraph Design and Implementation ● GeoGraph Demo 5
  • 6. © 2018 TigerGraph. All Rights Reserved 6 Traffic Inflow (predicted) Traffic Outflow (predicted) Saturday, 11:15 pm Japan Standard Time Number of Taxis needed: 105 Number of Taxis available: 65 Geospatial Operational Analytics Example: Real-time Taxi Positioning
  • 7. © 2018 TigerGraph. All Rights Reserved 40 Matching Demand & Supply with Predicted Traffic Flow Data For Busy Locations 78 96 120 92 45 45 80 29 45 323445 60 35 17 54 35 14 79 25 72 45 35 44 57 89 648745 45 98 34 65 35 78 78 85 78 45 45 35 98 64 33 63 654 69 Input Driver Suggested Moving direction 120 In Flow 40 Out Flow Flow Prediction Based on Historical data 40 Number of Taxis in that mesh
  • 8. © 2018 TigerGraph. All Rights Reserved 8 Develop Location-Based Customer 360 Profiles
  • 9. © 2018 TigerGraph. All Rights Reserved Recommendation Similar Users With Similar Movement Pattern = Grid Input User Geo-Temporal Patterns for Recommendation
  • 10.
  • 11. © 2018 TigerGraph. All Rights Reserved GeoSpatial Analytics with Graph Database 11 Finding entities (nodes/edges) in a connected network matching certain geolocation patterns One More Dimension(s) to Your Solution Space
  • 12. © 2018 TigerGraph. All Rights Reserved Common GeoSpatial Questions 12 RDBMS • Real World Challenge: • Not designed for complex Geo based search questions in real time • Rely on third party index • No easy SQL for answering these questions TigerGraph • Real World Benefit: • GeoSpatial data is on a graph • Designed for discovery/exploratory type of analytics • GSQL can naturally and efficiently express and solve the Geo search queries A. Who are the closest target entities (e.g., taxi drivers) to customer A? B. Find all hospitals in real time which are within this region with Rh-negative blood type. C. Find all doctors nearby who are specialists in congenital heart defects.
  • 13. 13 Why TigerGraph for GeoSpatial Analytics? Not Just Search, But Real-time Geo Intelligence!
  • 14. © 2018 TigerGraph. All Rights Reserved Why TigerGraph for GeoSpatial Search? Deep Link Analysis in Physical World • Geo Aware Multi Hop Entity Relationship • Native Parallel Graph Enabled by MPP Geo Enriched Graph Applications • GeoSpatial Intelligence to All Use Cases • Example: Smart Mobile Location Based Recommendation 14 • Movement at the Same Time with Many Entities (People and Things) • Continuous Big Data Real-Time Geo Insights Unique TigerGraph Features
  • 15. © 2018 TigerGraph. All Rights Reserved GeoSpatial Search (Intelligence) with TigerGraph 15 Problem: Finding entities (nodes/edges) in a connected network matching certain geolocation patterns with movements with continuously increasing real time data Solution: First and Only OLAP and OLTP Graph Database
  • 16. 16 GeoGraph In Depth TigerGraph GeoSpatial Search Solution and Demo Xinyu Chang, Solution Team Lead
  • 17. © 2018 TigerGraph. All Rights Reserved What is GeoGraph? 17 1. The earth is cut into a grid of bounding boxes or cells. 2. Each box can be represented by a vertex in the graph. 3. Each vertex has a predictable ID, which is x + y*c, where c is the number of columns. 4. Each object vertex is connected to the corresponding geo location vertex based on its coordinates.
  • 18. © 2018 TigerGraph. All Rights Reserved Graph Representation 18 123122 124 22 23 24 223222 224 Object Object Relationship between objects Location Edge Geo Location Vertex Object
  • 19. © 2018 TigerGraph. All Rights Reserved R-Tree vs. Grid 19 R-Tree Approach • Advantages: Search for arbitrary regions, points Allows us to estimate the number of dots in a region without a full data scan • Disadvantages: Significant redundancy in the data storage Slow update Grid Approach • Advantages: Stored as vertices and edges, naturally integrated with TIgerGraph System. Do the analytics including geo in a MPP way. Fast to update. Easy to implement and maintain. • Disadvantages: Might have uneven distribution of objects on each grid
  • 20. © 2018 TigerGraph. All Rights Reserved Example Dataset California Healthcare Facility Locations https://data.chhs.ca.gov/dataset/healthcare-facility-locations City Zipcode and Location https://www.aggdata.com/
  • 21. © 2018 TigerGraph. All Rights Reserved Graph Schema & Data Loading 21 Token Function getGridId: Given latitude and longitude, return the id of the grid vertex id.
  • 22. © 2018 TigerGraph. All Rights Reserved Graph Exploration & Queries
  • 23. © 2018 TigerGraph. All Rights Reserved Query Mechanism Expression Function getNearbyGridId: Given latitude, longitude and distance, return the nearby grid vertex ids within distance. Expression Function geoDistance: Given two pairs of latitude and longitude, return the distance between the two locations.
  • 24. © 2018 TigerGraph. All Rights Reserved Query Mechanism User Geo Grid Geo Grid Geo Grid Geo Grid Geo Grid Geo Grid Geo Grid Geo Grid Geo Grid Facility Facility Facility Facility Facility
  • 25. © 2018 TigerGraph. All Rights Reserved Demo Geospatial Search UI http://54.88.6.143:14240/geo/# GraphStudio UI http://54.88.6.143:14240
  • 27. © 2018 TigerGraph. All Rights Reserved Summary • Graph Database is a natural fit for Geospatial Analytics • TigerGraph is designed from the ground up for fast GeoSpatial Analytics • GeoSpatial Analytics algorithms with GSQL Queries • Graph Studio Demo for GeoSpatial Analytics 27
  • 28. Q&A Please send your questions via the Q&A menu in Zoom 28
  • 29. © 2018 TigerGraph. All Rights Reserved Additional Resources 29 New Developer Portal https://www.tigergraph.com/developers/ Download the Developer Edition or Enterprise Free Trial https://www.tigergraph.com/download/ Guru Scripts https://github.com/tigergraph/ecosys/tree/master/guru_scripts Join our Developer Forum https://groups.google.com/a/opengsql.org/forum/#!forum/gsql-users @TigerGraphDB youtube.com/tigergraph facebook.com/TigerGraphDB linkedin.com/company/TigerGraph