1. Distributed Geospatial Indexing
Rich Fecher
Kent Miller

2. What is GeoWave? GeoWave…
Bridges the gaps between popular geospatial projects, and distributed processing/analytics frameworks.
Leverages the scalability of distributed key-value stores for effective storage, retrieval, and analysis of massive geospatial datasets.
An open source LocationTech project from the National Geospatial-Intelligence Agency (NGA) in collaboration with RadiantBlue Technologies and Booz-Allen Hamilton.

3. Core Problem
How should GeoWave index multi-dimensional (i.e. spatial) data in a 1-dimensional, sorted key-value store?

4. Dimensionality Reduction
Use a Space Filling Curve (SFC) to impose multi-dimensional data.

5. Space Filling Curve Selection
Z-Order
Hilbert
H-order
Peano
AR2W2 BΩ
WL∞ ∞ 6 4 8
5.40
5.00
WL2
6.04
WL1 9
10.66
12.00
9.00
WBA
2.40
3.00
2.00
3.05
2.22
ABA
2.86
1.41
1.69
1.42
1.47
1.40
Haverkort, Walderveen Locality and Bounding-Box Quality of Two-Dimensional Space-Filling Curves 2008 arXiv: v2
Worst Case Bounding Box
Area Ratio (WBA)
Average Total Bounding
Box Area (ABA)
Worst Case Dilation

6. Query-Time Aggregation
Computes customized summaries on query
Runs distributed on data nodes
Returns user-specified aggregate values

7. Map Occlusion Culling: Subsample At Pixel Resolution
A specific determined zoom level, each pixel signifies a range in degrees. Scanning the data, only one entry is needed within each pixel range. The rest of the entries can be skipped.
The block identified in red represents many data points, but is rendered by the 9 pixels.

8. Pixel-based Subsampling: Apply at Data Node on Keys1 2 3 4 2 3
Database Data
Displayed Pixels
The accumulo iterator starts at the first pixel, scans until it hits a geometry, then skips to the next pixel. 1 4
TO DO: Fix graphic
The rendering engine received only these points
Scan to the first pixel
Seek to the beginning of the next pixel
Points that were all skipped.

9. Distributed Rendering
GeoServer
(GeoWave Plugin)
Map Request
Layer
Style
GeoWave Data Nodes
Each scan result is an image
with the data in the range
Rendered
Map
Map Response
All resultant images
are composited together

10. Built On

11. Additional Core Features in GeoWave
Command Line Utilities & RESTful Web Services
Local/HDFS Ingest
Kafka Streaming Ingest
Stats Generation
OSM Utilities
Landsat8 Utilities
Base Analytics
KDE Heat Map
DBSCAN
K-Means Clustering
Open Geospatial Consortium standard services via GeoServer
Spatial-Temporal indexing
Integrated with other geospatial frameworks
PDAL, Mapnik
HBase Support
Raster datasets
Rapid Deployment via AWS EMR
GeoWave MapReduce input/output formats
Statistics
Attribute ranges/histograms
Enveloping bounding box over all geometries
Counts of # of stored items
Counts of discrete attribute values
Support for a variety of ingest types
Shapefile, GeoJSON, PostGIS, ArcGrid, GeoTIFF, GPX, T-Drive

12. GeoWave Where can I find it?
GitHub
Source
Examples
Documentation
This Demo

13. Thanks! Rich Fecher rfecher@radiantblue.com Kent Miller

14. Backup Slides

15. OSM – Planet GPX Every track ever uploaded to Open Street Map
Complete data attribution
2.9 Billion spatial entities (points)

16. Global View Entire Pointset Visualized

17. Zoomed In

19. Kernel Density Estimate Global View

20. Kernel Density Estimate Zoomed In

21. Tiered Indexing Tier 0 (1x1) Tier 1 (2x2) Tier 2 (4x4) Tier 3 (8x8)
Point
Polygon
Tier
Duplicates
Cell(s) 1 4 2 14 6 3 56
21-24
222 9
35-42

22. Space Filling Curve Granularity
8x8 Grid
64x64 Grid
Polygons overlap few cells
Many points per cell
Polygons overlap many cells
Fewer points per cell
Which is better?
Why?

23. Good to Know Space Filling Curve Range Decomposition
Intersects
Bounding Box
Query (71 -> 98)
Range of cells from 92-99
Range of cells from 70-75
Range of cells from

24. Microsoft - GeoLife
Microsoft research has made available a trajectory data set that contains the GPS coordinates of 182 users over a three year period (April 2007 to August 2012).
There are 17,621 trajectories in this data set.

25. GeoLife Original Track Data

26. Kernel Density Estimate Gaussian Kernel

27. Zoomed In Original Track Data

28. Kernel Density Estimate Zoomed In

29. Good to Know GeoWave Key Structure
Value
Row ID
Column
Time-Stamp
Family
Qualifier
Visibility
Index ID
Adapter ID
Data ID
Adapter ID Length
Data ID Length
# of Duplicates
Field ID
Field Value
Tier
Bin
Hilbert
GeoWave Feature Metadata
Feature Attribute Field/Value Pair
Tier Index
Hilbert SFC Index

30. Initially 2 Points, 2 Polygons
Ingest Example
Ingest a Line
Tier 31
Tier 3
Initially 2 Points, 2 Polygons
Many Duplicates
18 Duplicates
Tier 2
Tier 1
Tier 0
Final State
8 Duplicates
3 Duplicates
1 Duplicate
Final State

31. Query Example Intersects Query Tier 1 Tier 2 Magenta Bounding Box
1 cell, 0 filtered, 0 intersect
2 cells, 2 filtered, 0 intersect
Tier 3
Tier 4
Tier 31
Final Result
4 cells, 1 filtered, 0 intersect
6 cells, 0 filtered, 1 intersect
0 filtered, 1 intersect
1 Point, 1 Polygon Returned