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Ing. Andrea Aime
Ing. Simone Giannecchini
GeoSolutions
Processing Data In GeoServer
With WPS And SQL Views
GeoSolutions
 Founded in Italy in late 2006
 Expertise
• Image Processing, GeoSpatial Data Fusion
• Java, Java Enterprise, C++, Python
• JPEG2000, JPIP, Advanced 2D visualization
 Supporting/Developing FOSS4G projects
 GeoServer, MapStore
 GeoNetwork, GeoNode, Ckan
 Clients
 Public Agencies
 Private Companies
 http://www.geo-solutions.it
FOSS4G 2016, Bonn
22nd - 26th August 2016
Some historical perspective
 Year 2008:
 Publish maps on the net
 Nice styling, maybe time/elevation based selector,
some little extra filtering
 Maybe some editing, some PDF printing
 Since 2013:
 All of the above, but…
 We can hardly make a new application without
some data processing in it
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS: some quick reminders
FOSS4G 2016, Bonn
22nd - 26th August 2016
Web Processing Service
 Wikipedia introduces OGC WPS as:
 [A service] designed to standardize
the way that GIS calculations are
made available to the Internet.
 WPS can describe any calculation
including all of its inputs and
outputs, and trigger its execution
 The specific processes served up by
a WPS implementation are defined
by the owner of that implementation.
 Although WPS was designed to work
with spatially referenced data, it can
be used with any kind of data.
FOSS4G 2016, Bonn
22nd - 26th August 2016
An Example
 Buffer a L shaped
geometry with
distance “2”
 Get the result back
as GML
FOSS4G 2016, Bonn
22nd - 26th August 2016
Synchronous vs asynchronous
WPS
client
WPS
Launch
process
Send back
results
Simple
Suitable for fast executions
Synchronous
WPS
client
WPS
Launch process
Status URL
Check progress
50%
Check progress
100%
Results inline
Link to results
More complex
Suitable for longer computations
Asynchronous
FOSS4G 2016, Bonn
22nd - 26th August 2016
Common WPS setup
WPS
Remote
WCS
Remote
WFS
HTTP
server
WPS
client
Request
+
data or links to data
Result
data
Fetch
data
FOSS4G 2016, Bonn
22nd - 26th August 2016
GeoServer WPS integration
WPS
Remote
WCS
Remote
WFS
HTTP
server
WPS
client
All GeoServer
Layers
WMS
clientWMS
GeoServer
UI
FOSS4G 2016, Bonn
22nd - 26th August 2016
Demo request builder
 List processes
 Describe
 Set parameters and
execute
 All in one form
FOSS4G 2016, Bonn
22nd - 26th August 2016
Rendering transformations
 On-the-fly data transformations inside rendering
chain
 Calling WPS processes from SLD docs
 Optimized for performance
FOSS4G 2016, Bonn
22nd - 26th August 2016
Let’s take one step back…
you don’t always need a WPS
Spatial DBMS!
• Never under-estimate the processing power of
your BDMS:
• Designed to efficiently juggle large quantities of
data
• Efficient spatial primitives (at least, in PostGIS)
• Doesn’t get more local to your data than this!
• Passing params down?
• Parametric SQL views!
FOSS4G 2016, Bonn
22nd - 26th August 2016
Parametric SQL views
WMS/WFS client
GeoServer
Spatial database
&viewparams=from:2000000;high:5000000
Expanded Query
FOSS4G 2016, Bonn
22nd - 26th August 2016
Parametric SQL views
FOSS4G 2016, Bonn
22nd - 26th August 2016
SELECT Date_part('year'::text, t1.obs_datetime) AS obs_year,
t1.storm_num, t1.storm_name,
t1.wind, t2.wind AS wind_end,
t1.press, t2.press AS press_end,
t1.obs_datetime, t2.obs_datetime AS obs_datetime_end,
St_makeline(t1.geom, t2.geom) AS geom
FROM storm_obs t1
join(SELECT storm_obs.id,
storm_obs.storm_num, storm_obs.storm_name,
storm_obs.wind, storm_obs.press,
storm_obs.obs_datetime,
storm_obs.geom FROM storm_obs) t2
ON(t1.obs_datetime + '06:00:00'::interval) = t2.obs_datetime
AND t1.storm_name::text = t2.storm_name::text
WHERE Date_part('year'::text, t1.obs_datetime)
BETWEEN %min_obs_year% AND %max_obs_year%
ORDER BY Date_part('year'::text, t1.obs_datetime),
t1.storm_num,
t1.obs_datetime
• Building lines of the fly from point data:
Enough theory
Let’s get down to business!
Pure local WPS: Soil Monitor
Soil Monitor
• Computing Soil Monitor Indeces at country level
• Soil Sealing
• Change Matrix
• GeoServer as the W*S Server
• MapStore as the mapping Front-End
• Webmapping and WPS Orchestration
• Charting
• GPU processing wrapper as WPS Processes
• JCuda
• Custom code to bridge between
GeoServer/GeoTools and Cuda
• Direct Ingestion of the resulting raster data
• Raster Algebra as rendering transformation using
Jiffle
http://www.soilmonitor.it/
FOSS4G 2016, Bonn
22nd - 26th August 2016
https://github.com/mbedward/jiffle
Soil sealing algorithm
FOSS4G 2016, Bonn
22nd - 26th August 2016
Change matrix results
FOSS4G 2016, Bonn
22nd - 26th August 2016
Charting what changed
FOSS4G 2016, Bonn
22nd - 26th August 2016
Tracking running processes
FOSS4G 2016, Bonn
22nd - 26th August 2016
Pure SQL views: Tuna Atlas
Mapping Tuna Catches
• Multiple Filtering
• Aggregation
• Joining quartely
stats against the
grid
FOSS4G 2016, Bonn
22nd - 26th August 2016
Filtering, joining and aggregation
Some example control regexps:
• Y_INTERV:
• Default: 1
• Regex: ^(d)+$
• OP
• Default: sum
• Regex: ^[avg|sum]$
SELECT (T.TS_VALUE / %Y_INTERV%) AS TS_VALUE,
T.CD_TA_OCEANAREA, G.GEOMETRY
FROM
(SELECT CD_TA_OCEANAREA,
OP%(TS_VALUE) AS TS_VALUE
FROM FIGIS.TS_FI_TA
WHERE FIC_ITEM IN (%FIC_ITEM%)
AND CD_GEAR IN (%CD_GEAR%)
AND YR_TA IN (%YR_TA%)
AND QTR_TA IN (%QTR_TA%)
GROUP BY CD_TA_OCEANAREA
) t
LEFT OUTER JOIN FIGIS_GIS.GRID_G5 g
ON T.CD_TA_OCEANAREA = g.CD_OAREA
ORDER BY T.CD_TA_OCEANAREA
FOSS4G 2016, Bonn
22nd - 26th August 2016
Animation
• Animator tool
• GetMap + variying parameters + frame control
=> animated GIF!
• http://docs.geoserver.org/stable/en/user/tutoria
ls/animreflector.html
FOSS4G 2016, Bonn
22nd - 26th August 2016
Animator
• …/geoserver/wms/animate?request=GetMap&…
&format=image/gif;subtype=animated
&aparam=viewparams:YR_TA
&avalues=2000,2001,2002,2003,…
FOSS4G 2016, Bonn
22nd - 26th August 2016
Compunding WFS/WCS deficiencies:
Download services
Advanced Clip and Ship
• Community WPS module plus MapStore UI
• Requirements
• Download large amounts of data
• Generic data filtering
• Clip on polygon/bbox/circle, both vector and
raster
• Reproject to target CRS
• Band selection in raster
• Work in a cluster
• Solution: new WPS processes, asynch WPS
call
FOSS4G 2016, Bonn
22nd - 26th August 2016
MapStore GUI
Buffer process called synchronously when buffer size
changes
FOSS4G 2016, Bonn
22nd - 26th August 2016
MapStore GUI
Tracking download status (asynch WPS)
FOSS4G 2016, Bonn
22nd - 26th August 2016
Download service architecture
WPS
GeoServer
Layers
MapStore WMS
GetCapabilities
List of layers
Buffer
DownloadEstimator
Download
GetStatus
Fetch data
Status
database
Shared
Hazelcast/DBMS
database
FOSS4G 2016, Bonn
22nd - 26th August 2016
Pure WPS
calling to other computing nodes:
WPS Remote
WPS Remote
• Use GeoServer as WPS Broker  Run Remote
Processes Asynchronously
• Support Python or command line tools
• Relies on XMPP for discovery and
messaging/logging
• Supports Dismiss and basic load balancing for
different executors
• Automagic results ingestion in GeoServer
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS Remote
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS Remote
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS Remote
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS Remote
FOSS4G 2016, Bonn
22nd - 26th August 2016
WPS Remote  Change Detection
FOSS4G 2016, Bonn
22nd - 26th August 2016
Mixing parametric SQL views and WPS:
The Destination Project
Intro
Computing the risk of road accidents involving
dangerous goods (chemicals, petrol, gases and so
on)
Road segments
and stats about
car accidents
Human and environmental «targets»
Involved area,
depending on
type of good and
amount of
damage
FOSS4G 2016, Bonn
22nd - 26th August 2016
Large Data Volume
• Road network of good part of northern Italy
• Road divided into segments
• 100m portions (500k of them)
• 500m aggregation (120k of them)
• 1 km square cells (few hundreds)
• 51 buffer distances (depending on good,
scenario, level of damage)
• Several types of targets: schools, malls,
hospitals, populated areas, superficial and
underground acquifers, crops, woods, ….
FOSS4G 2016, Bonn
22nd - 26th August 2016
The road arc risk formula (s)
• Adding togheter the risk caused by the
different
• Arc own propension to accidentds
• Types of goods
• Human and enviromental targets
• The system allows to compute partial views of
the formula, either by selection of
targets/goods or by computing portions of it
• Has a number of coefficients that can be hand-
tuned by the caller
FOSS4G 2016, Bonn
22nd - 26th August 2016
The results, visually
• Rendering
transformation
• Read the
arcs/polys from
the DB, compute
their risk based
on the chosen
formula,
scenario, targets,
and coefficients
FOSS4G 2016, Bonn
22nd - 26th August 2016
How to compute it efficiently?
• Using SQL Views? No, the possible
aggregations variants are too many
• Using a pure Java process? No, too much data
to transfer from the DBMS
• Fully on the fly? No, too much data involved
•  Pre-compute all buffers and locate all
involved targets before hand (pre-cooked per
buffer risk)
•  Use a process that builds a final
aggregation query on the fly (dynamic sql
views)
FOSS4G 2016, Bonn
22nd - 26th August 2016
Parametric queries on steroids
• Find which queries are needed, replace params
• Some queries have sub-queries as params
FOSS4G 2016, Bonn
22nd - 26th August 2016
Efficient rendering tx
Risk
process
Queries
database
Arcs/Buffer
areas db
Map
renderer
Build overall
query, replace
params
Compute risk for
a batch of arcs
Raw arcs
Arcs + risk
• Compute risk on the
fly in the viewing
area
• Batch requests to
the BDMS to
minimize round-trip
overhead
FOSS4G 2016, Bonn
22nd - 26th August 2016
Efficient cross layer filtering
• Show only targets
involved in the
scenario under
study, e.g., the ones
crossing the buffer
areas where there is
significant risk
• Limit query to the
current bbox
FOSS4G 2016, Bonn
22nd - 26th August 2016
Efficient cross layer filtering
SELECT v_geo_popolazione_residente_pl.*
FROM v_geo_popolazione_residente_pl
WHERE v_geo_popolazione_residente_pl.fk_bersaglio_umano_pl in
(
SELECT distinct bersaglio.fk_bersaglio_umano_pl
FROM v_geo_popolazione_residente_pl bersaglio
join siig_geo_ln_arco_1 on
st_dwithin(bersaglio.geometria,
siig_geo_ln_arco_1.geometria,
%distanzaumano%)
WHERE siig_geo_ln_arco_1.geometria &&
st_makeenvelope(%bounds%, 32632)
)
This is a job for a parametric sql view
FOSS4G 2016, Bonn
22nd - 26th August 2016
Efficient computation of multi-buffers
• Computing 51 buffers
around each of 500k
arcs…
• Slow!
• Buffering over the
previous buffer proved
to be much faster than
computing each buffer
from the original arc
• Custom multibuffer
process
FOSS4G 2016, Bonn
22nd - 26th August 2016
The CMRE-IDA Project
Intro
• The Integrated Decision Aid (IDA) has been developed at the Centre for
Maritime Research and Experimentation (CMRE) in order to provide naval
exercise planners with an effective tool to assess risk to marine mammals
from acoustic transmissions.
• Assessment of potential hazard is performed through sound propagation
modeling available in the interface.
Sound
Propagation
Model
FOSS4G 2016, Bonn
22nd - 26th August 2016
Sound Propagation Model
• External Octave Matlab Process
• Logs the asynchrouns process status to the
DB as a Feature
Octave Matlab Script
for SPM
WFS
Follows the process
status through the
WFSWFSLog
Process allows
to insert and
update the
status of SPM
into the DB
Dynamically builds an external Octave
command line using the input parameters
through a FreeMarker Template (FTL)
FOSS4G 2016, Bonn
22nd - 26th August 2016
Sound Propagation Model
• The list of model runs is available on the bottom Data
Grid
• It is possible to get information on the input parameters
and execution from the WFS
FOSS4G 2016, Bonn
22nd - 26th August 2016
Raster Algebra Processes
• Simple Raster Algebra
• Gets an OGC Filter containing logical operations
between raster layers and produces a binary (0/1) layer
FOSS4G 2016, Bonn
22nd - 26th August 2016
Raster Algebra Processes
• Advanced Raster Algebra using Jiffle
• Wraps Jiffle (http://code.google.com/p/jiffle/) in order to
execute complex Raster Algebra scripts against the
input layers
Jiffle is a scripting language for creating and analysing raster images. Rather
than having to write and test lots of JAI or Java AWT boiler-plate code to
access and manipulate images, Jiffle lets you concentrate on the interesting
bit: your algorithm.
Jiffle is being developed as part of the JAITools project.
Update 16 January 2013: Jiffle sources have moved to GitHub
FOSS4G 2016, Bonn
22nd - 26th August 2016
Raster Algebra Processes
• Advanced Raster Algebra using Jiffle
• Gets an OGC Filter containing logical operations
between raster layers and produces a binary light layer
FOSS4G 2016, Bonn
22nd - 26th August 2016
Raster Algebra Processes
• Raster Algebra detailed info
• Input parameters and outcomes are logged into WFS
• WPS Raster Stats Process provides statistics on the
coverages
Raster
Statistics and
Area in sq Km
Raster Algebra
Process user
inputs
FOSS4G 2016, Bonn
22nd - 26th August 2016
Utility Processes
• WPS Raster Stats process
• WPS Temp Cleaner async process
The WPS Raster Stats process can
be invoked at run-time.
It computes the Raster Stats on the
current viewport area.
A cleaner process has been created to
cleanup all the IDA temporary files.
Is invoked asynchronously and makes use
of the IDA config parameters.
Also a WFS Delete Transaction listener is
available cleaning up all the input and
temp files when removing a row from the
Data Grid.
FOSS4G 2016, Bonn
22nd - 26th August 2016
The End
Questions?
andrea.aime@geo-solutions.it
simone.giannecchini@geo-solutions.it
FOSS4G 2016, Bonn
22nd - 26th August 2016

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Crunching Data In GeoServer: Mastering Rendering Transformations, WPS Processes And SQL Views - FOSS4G 2016

  • 1. Ing. Andrea Aime Ing. Simone Giannecchini GeoSolutions Processing Data In GeoServer With WPS And SQL Views
  • 2. GeoSolutions  Founded in Italy in late 2006  Expertise • Image Processing, GeoSpatial Data Fusion • Java, Java Enterprise, C++, Python • JPEG2000, JPIP, Advanced 2D visualization  Supporting/Developing FOSS4G projects  GeoServer, MapStore  GeoNetwork, GeoNode, Ckan  Clients  Public Agencies  Private Companies  http://www.geo-solutions.it FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 3. Some historical perspective  Year 2008:  Publish maps on the net  Nice styling, maybe time/elevation based selector, some little extra filtering  Maybe some editing, some PDF printing  Since 2013:  All of the above, but…  We can hardly make a new application without some data processing in it FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 4. WPS: some quick reminders FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 5. Web Processing Service  Wikipedia introduces OGC WPS as:  [A service] designed to standardize the way that GIS calculations are made available to the Internet.  WPS can describe any calculation including all of its inputs and outputs, and trigger its execution  The specific processes served up by a WPS implementation are defined by the owner of that implementation.  Although WPS was designed to work with spatially referenced data, it can be used with any kind of data. FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 6. An Example  Buffer a L shaped geometry with distance “2”  Get the result back as GML FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 7. Synchronous vs asynchronous WPS client WPS Launch process Send back results Simple Suitable for fast executions Synchronous WPS client WPS Launch process Status URL Check progress 50% Check progress 100% Results inline Link to results More complex Suitable for longer computations Asynchronous FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 8. Common WPS setup WPS Remote WCS Remote WFS HTTP server WPS client Request + data or links to data Result data Fetch data FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 9. GeoServer WPS integration WPS Remote WCS Remote WFS HTTP server WPS client All GeoServer Layers WMS clientWMS GeoServer UI FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 10. Demo request builder  List processes  Describe  Set parameters and execute  All in one form FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 11. Rendering transformations  On-the-fly data transformations inside rendering chain  Calling WPS processes from SLD docs  Optimized for performance FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 12. Let’s take one step back… you don’t always need a WPS
  • 13. Spatial DBMS! • Never under-estimate the processing power of your BDMS: • Designed to efficiently juggle large quantities of data • Efficient spatial primitives (at least, in PostGIS) • Doesn’t get more local to your data than this! • Passing params down? • Parametric SQL views! FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 14. Parametric SQL views WMS/WFS client GeoServer Spatial database &viewparams=from:2000000;high:5000000 Expanded Query FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 15. Parametric SQL views FOSS4G 2016, Bonn 22nd - 26th August 2016 SELECT Date_part('year'::text, t1.obs_datetime) AS obs_year, t1.storm_num, t1.storm_name, t1.wind, t2.wind AS wind_end, t1.press, t2.press AS press_end, t1.obs_datetime, t2.obs_datetime AS obs_datetime_end, St_makeline(t1.geom, t2.geom) AS geom FROM storm_obs t1 join(SELECT storm_obs.id, storm_obs.storm_num, storm_obs.storm_name, storm_obs.wind, storm_obs.press, storm_obs.obs_datetime, storm_obs.geom FROM storm_obs) t2 ON(t1.obs_datetime + '06:00:00'::interval) = t2.obs_datetime AND t1.storm_name::text = t2.storm_name::text WHERE Date_part('year'::text, t1.obs_datetime) BETWEEN %min_obs_year% AND %max_obs_year% ORDER BY Date_part('year'::text, t1.obs_datetime), t1.storm_num, t1.obs_datetime • Building lines of the fly from point data:
  • 16. Enough theory Let’s get down to business!
  • 17. Pure local WPS: Soil Monitor
  • 18. Soil Monitor • Computing Soil Monitor Indeces at country level • Soil Sealing • Change Matrix • GeoServer as the W*S Server • MapStore as the mapping Front-End • Webmapping and WPS Orchestration • Charting • GPU processing wrapper as WPS Processes • JCuda • Custom code to bridge between GeoServer/GeoTools and Cuda • Direct Ingestion of the resulting raster data • Raster Algebra as rendering transformation using Jiffle http://www.soilmonitor.it/ FOSS4G 2016, Bonn 22nd - 26th August 2016 https://github.com/mbedward/jiffle
  • 19. Soil sealing algorithm FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 20. Change matrix results FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 21. Charting what changed FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 22. Tracking running processes FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 23. Pure SQL views: Tuna Atlas
  • 24. Mapping Tuna Catches • Multiple Filtering • Aggregation • Joining quartely stats against the grid FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 25. Filtering, joining and aggregation Some example control regexps: • Y_INTERV: • Default: 1 • Regex: ^(d)+$ • OP • Default: sum • Regex: ^[avg|sum]$ SELECT (T.TS_VALUE / %Y_INTERV%) AS TS_VALUE, T.CD_TA_OCEANAREA, G.GEOMETRY FROM (SELECT CD_TA_OCEANAREA, OP%(TS_VALUE) AS TS_VALUE FROM FIGIS.TS_FI_TA WHERE FIC_ITEM IN (%FIC_ITEM%) AND CD_GEAR IN (%CD_GEAR%) AND YR_TA IN (%YR_TA%) AND QTR_TA IN (%QTR_TA%) GROUP BY CD_TA_OCEANAREA ) t LEFT OUTER JOIN FIGIS_GIS.GRID_G5 g ON T.CD_TA_OCEANAREA = g.CD_OAREA ORDER BY T.CD_TA_OCEANAREA FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 26. Animation • Animator tool • GetMap + variying parameters + frame control => animated GIF! • http://docs.geoserver.org/stable/en/user/tutoria ls/animreflector.html FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 29. Advanced Clip and Ship • Community WPS module plus MapStore UI • Requirements • Download large amounts of data • Generic data filtering • Clip on polygon/bbox/circle, both vector and raster • Reproject to target CRS • Band selection in raster • Work in a cluster • Solution: new WPS processes, asynch WPS call FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 30. MapStore GUI Buffer process called synchronously when buffer size changes FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 31. MapStore GUI Tracking download status (asynch WPS) FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 32. Download service architecture WPS GeoServer Layers MapStore WMS GetCapabilities List of layers Buffer DownloadEstimator Download GetStatus Fetch data Status database Shared Hazelcast/DBMS database FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 33. Pure WPS calling to other computing nodes: WPS Remote
  • 34. WPS Remote • Use GeoServer as WPS Broker  Run Remote Processes Asynchronously • Support Python or command line tools • Relies on XMPP for discovery and messaging/logging • Supports Dismiss and basic load balancing for different executors • Automagic results ingestion in GeoServer FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 35. WPS Remote FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 36. WPS Remote FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 37. WPS Remote FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 38. WPS Remote FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 39. WPS Remote  Change Detection FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 40. Mixing parametric SQL views and WPS: The Destination Project
  • 41. Intro Computing the risk of road accidents involving dangerous goods (chemicals, petrol, gases and so on) Road segments and stats about car accidents Human and environmental «targets» Involved area, depending on type of good and amount of damage FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 42. Large Data Volume • Road network of good part of northern Italy • Road divided into segments • 100m portions (500k of them) • 500m aggregation (120k of them) • 1 km square cells (few hundreds) • 51 buffer distances (depending on good, scenario, level of damage) • Several types of targets: schools, malls, hospitals, populated areas, superficial and underground acquifers, crops, woods, …. FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 43. The road arc risk formula (s) • Adding togheter the risk caused by the different • Arc own propension to accidentds • Types of goods • Human and enviromental targets • The system allows to compute partial views of the formula, either by selection of targets/goods or by computing portions of it • Has a number of coefficients that can be hand- tuned by the caller FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 44. The results, visually • Rendering transformation • Read the arcs/polys from the DB, compute their risk based on the chosen formula, scenario, targets, and coefficients FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 45. How to compute it efficiently? • Using SQL Views? No, the possible aggregations variants are too many • Using a pure Java process? No, too much data to transfer from the DBMS • Fully on the fly? No, too much data involved •  Pre-compute all buffers and locate all involved targets before hand (pre-cooked per buffer risk) •  Use a process that builds a final aggregation query on the fly (dynamic sql views) FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 46. Parametric queries on steroids • Find which queries are needed, replace params • Some queries have sub-queries as params FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 47. Efficient rendering tx Risk process Queries database Arcs/Buffer areas db Map renderer Build overall query, replace params Compute risk for a batch of arcs Raw arcs Arcs + risk • Compute risk on the fly in the viewing area • Batch requests to the BDMS to minimize round-trip overhead FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 48. Efficient cross layer filtering • Show only targets involved in the scenario under study, e.g., the ones crossing the buffer areas where there is significant risk • Limit query to the current bbox FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 49. Efficient cross layer filtering SELECT v_geo_popolazione_residente_pl.* FROM v_geo_popolazione_residente_pl WHERE v_geo_popolazione_residente_pl.fk_bersaglio_umano_pl in ( SELECT distinct bersaglio.fk_bersaglio_umano_pl FROM v_geo_popolazione_residente_pl bersaglio join siig_geo_ln_arco_1 on st_dwithin(bersaglio.geometria, siig_geo_ln_arco_1.geometria, %distanzaumano%) WHERE siig_geo_ln_arco_1.geometria && st_makeenvelope(%bounds%, 32632) ) This is a job for a parametric sql view FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 50. Efficient computation of multi-buffers • Computing 51 buffers around each of 500k arcs… • Slow! • Buffering over the previous buffer proved to be much faster than computing each buffer from the original arc • Custom multibuffer process FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 52. Intro • The Integrated Decision Aid (IDA) has been developed at the Centre for Maritime Research and Experimentation (CMRE) in order to provide naval exercise planners with an effective tool to assess risk to marine mammals from acoustic transmissions. • Assessment of potential hazard is performed through sound propagation modeling available in the interface. Sound Propagation Model FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 53. Sound Propagation Model • External Octave Matlab Process • Logs the asynchrouns process status to the DB as a Feature Octave Matlab Script for SPM WFS Follows the process status through the WFSWFSLog Process allows to insert and update the status of SPM into the DB Dynamically builds an external Octave command line using the input parameters through a FreeMarker Template (FTL) FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 54. Sound Propagation Model • The list of model runs is available on the bottom Data Grid • It is possible to get information on the input parameters and execution from the WFS FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 55. Raster Algebra Processes • Simple Raster Algebra • Gets an OGC Filter containing logical operations between raster layers and produces a binary (0/1) layer FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 56. Raster Algebra Processes • Advanced Raster Algebra using Jiffle • Wraps Jiffle (http://code.google.com/p/jiffle/) in order to execute complex Raster Algebra scripts against the input layers Jiffle is a scripting language for creating and analysing raster images. Rather than having to write and test lots of JAI or Java AWT boiler-plate code to access and manipulate images, Jiffle lets you concentrate on the interesting bit: your algorithm. Jiffle is being developed as part of the JAITools project. Update 16 January 2013: Jiffle sources have moved to GitHub FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 57. Raster Algebra Processes • Advanced Raster Algebra using Jiffle • Gets an OGC Filter containing logical operations between raster layers and produces a binary light layer FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 58. Raster Algebra Processes • Raster Algebra detailed info • Input parameters and outcomes are logged into WFS • WPS Raster Stats Process provides statistics on the coverages Raster Statistics and Area in sq Km Raster Algebra Process user inputs FOSS4G 2016, Bonn 22nd - 26th August 2016
  • 59. Utility Processes • WPS Raster Stats process • WPS Temp Cleaner async process The WPS Raster Stats process can be invoked at run-time. It computes the Raster Stats on the current viewport area. A cleaner process has been created to cleanup all the IDA temporary files. Is invoked asynchronously and makes use of the IDA config parameters. Also a WFS Delete Transaction listener is available cleaning up all the input and temp files when removing a row from the Data Grid. FOSS4G 2016, Bonn 22nd - 26th August 2016