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Rob Emanuele
ENABLING ACCESS TO BIG
GEOSPATIAL DATA WITH
&
What we’ll be covering…
LocationTech projects that geospatially enable
Apache big data frameworks by providing spatial
indexing.
Discuss how those four project approach
indexing, focusing on the use of space filling
curves.
STORING AND PROCESSING
GEOSPATIAL DATA @ SCALE
STORING AND PROCESSING
GEOSPATIAL DATA @ SCALE
WHAT IS ?
GEOJINNI
(FORMERLY SPATIALHADOOP)
SPACE FILLING CURVES
00 01
1011
10
11 00
01
11
10
00
01
Hilbert Index (52) =
11 01 00
Geo +
accessed through
Z curve
Z curve
(also XZ)
Geo +
accessed through
GEOWAVE
Hilbert Curve
Range Decomposition
70 -> 75
92 -> 99
116 -> 121
False positives - secondary filtering
Geo +
Rasters +
Z or Hilbert
Data
Node
Data
Node
Data
Node
Name
Node
Master
Tablet
Server
Tablet
Server
Tablet
Server
Accumulo
BigTable clone (columnar database)
Records stored on HDFS
Lexicographically sorted table index
partition
id
split
id
split
id
partition
id
Tiered Indexing
Tiered Indexing
Periodicity (time dimension)
1997 1998 1999
Periodicity (arbitrary dimensions)
Time
Elevation
Velocity
Spatial index stored per file on HDFS
Z order (2D and 3D),
Hilbert (N-Dimensional)
Z order (2D and 3D)
Binned per week for spatiotemporal
N-Dimensional Hilbert with
arbitrary binning and tiered indexing
Spatial Indexing
CQL
Future integration work
?
THANK YOU
@lossyrob
gitter.im/geotrellis/geotrellis
github.com/geotrellis/geotrellis
remanuele@azavea.com
GeoMesa
GeoWave
Tiered Indexing

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