Presented at the 2011 Texas GIS Forum

1. Leveraging SQL Server
to Improve Vector
Display through Point
Clustering

2. The Problem…
 Due to Java Script limitation,
Large Numbers of Vectors don’t
draw in Web-Mapping
Environments.
 Cutoff is ~ 300-500 Features

3. Current ways to solve…
1. Use Silverlight or Flash
 Increases capacity roughly an order of magnitude, but similar
limitation exists.
2. Show Pictures, Query Features
 Has the capability to show and query ALL features for a
pleasant user experience, but takes time to build tile cash (the
pretty pictures).
 However, Tile Caches are Large and are, basically, redundant
storage.
3. Use a WMS to feed ‘pictures’ dynamically and then use
a separate, spatial query for feature attributes.
 Extra ‘moving’ parts in the solution.
 Possibly extra cost in licenses.

4. Why Invent a ‘Better’
Solution???
 Original Design…
 Texas Hydrologic Information System (TexasHIS)
 www.waterdatafortexas.org
 Client desires immediate access to vector data
and attributes
 Data Characteristics
 Lots of tightly packed ‘Sites’ ~ 300K+
 data with gobs of related attribute data ~
5,000,000+ related records!

5. Factors Affecting a Good ‘Clustering’
 The Data
Solution…
 Density
 Distribution
 The Scale
 Large – Basically Draw everything
 ‘Medium’ – Draw some, Cluster some – Lots of Code and
Logic!
 Small – Basically Cluster everything
 Logic
 Thresholds/Limits of when to Cluster vs. When to Draw
 How to Carve the display to deal with Data Distribution
 Complex Algorithms to determine the optimal number of
features to draw.

6.  Create a ‘smart’ solution that…
 Isn’t affected by the java script limit
 Only queries the database one time
(other solutions can query the
database for image creation and
attribute retrieval.
 Is still capable of retrieving vector
attributes for single features

7. Solution Basics…
1. Drawing Thresholds
 When to Draw everything
 When to Cluster
 When to take no action
2. Carving The Display
 At first glance, a 16 x 16 ‘Grid’ would be
best. It would yield 256 Cluster ‘Features’
3. Clustering Logic
 Draw the Singles
 Cluster Everything Else

8. Solution Basics: Thresholds…
1. Drawing Thresholds
 Draw Everything – if the total number
of Points to ‘cluster’ is below 500
 Cluster – If there are 500 (Lower Limit)
to 5000 (Upper Limit)
 Above the Upper Limit – Take no
action. The Clustering Query becomes
too expensive. So much so that user
experience is drastically diminished.

9. Solution Basics: Carving up the Display
and Applying the Logic Rules…
 Spatial Indexes are Similar in concept
 16 x 16 creates 256 Cells – Near the upper limit of
our display threshold
 Polygons with more than 1 Site are ‘Cluster
Candidates’. The Centroid of the polygon will
represent the cluster spatially.
 Threshold values are variables so that they are
easily ‘tuned’ in a series of runs.

10. Solution Basics: How it works…
 The Envelope of the Display is passed as a parameter
 First Function, a Scalar-Valued Function, determines
how ‘big’ the cells will be in the X and Y direction –
Returns a comma separated number pair –
“0.3456778,0.3456777”
 Second Function, a Table-Valued Function, returns a
table of polygon cells that are ‘built’ from the output
of the SVF and the starting point of the Display
Envelope. A ‘cutter’ variable is used to build-out
polygons with @var_Y rows and @var_X columns.
 The results of these functions are then used to
0perate on the ‘Sites’ point dataset.

11. X
Y

13. At Long Last…
DEMO!!!

14. Further Improvements…
 Add logic to always draw ‘up-to’
the lower limit.
 Possibly add some ‘weight’ to the
clustered point so that it doesn’t
show in such a ‘regular’ way.
 Others…

15. TNRIS Information Services…
 Richard Wade – Team Lead
 Ryan Mitchell – Web Systems and Data Czar
 Yvette Giraud – Web Development
 Ragunath Jayabalakrishnan – Developer (Contract)
 Chris Williams – Database Administrator

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