Presentation held during the NKUA postgraduate course “DATA BASES MANAGEMENT SYSTEMS” on 6th of December 2016 at National and Kapodistrian University of Athens. Nikolas Laskaris, UoA Giota Koltsida, UoA http://bit.ly/2hEkn3G

1. BlueBRIDGE receives funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No. 675680 www.bluebridge-vres.eu
Geo-analytics
Architecture - Technologies
Nikolas Laskaris, UoA (laskarisn@di.uoa.gr)
Giota Koltsida, UoA (p.koltsida@di.uoa.gr)
UOA postgraduate course
“DATA BASE MANAGEMENT SYSTEMS”
Prof. Y. Ioannidis
8th December 2016, Athens

2. Platform Objectives
2
• Support investors & research
communities
 Optimize their intended investment
 Find areas of environmental importance
• Recommend locations of interest
 Consumes geospatial datasets
 Exploits performance – economic – socioeconomic models
 Produces new datasets through analysis
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS

3. System Objectives
3
• High Performance
• Distributed
• Modular and Pluggable
• In terms of functionality and
algorithms
• Adoptable to new type of datasets /
layers
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS

4. External Geospatial
Repositories
Architecture Overview
GAAP Backend
Geospatial Server instances
GAAP Analytics Layer
(ex GeoPolis)
Tile cache
Data Abstraction Layer
(WMS, WFS, Custom REST Protocols)
Model Manager
Virtual Layer
Manager
UI & Visualization Layer
Logical Layer Manager
Geoserver
Geo-
database
ProjectManagement
Layer/DataManagement
DataVisualization
Logical Layer Broker
OGC / Custom API
Configuration Service
Information System
- service and resources discovery
- Service registry
Geoservers
GAAP* : Geospatial Analytics & Alerting Platform
Geoserver
Geo-
database
Geoserver
Geo-
database
Zookeeper
Cluster

5. Data access scheme
• Data access is modular
• Platform can operate in various configurations, from
entirely local to completely distributed
• Local: Single node RDBMS-backed (first release)
• Distributed: Geospatial cluster, Spark operations (currently
working)
• Layers replication
• Custom logic for replication
• Accomplishes synchronisation and updates
UoA course: DATA BASE MANAGEMENT SYSTEMS08/12/2016

6. Cluster Coordination
• Apache ZooKeeper (through Apache Curator)
• Event watchers for node state observation
• Distributed locking for future needs
• Curator provides easy to use pre-cooked solutions
• Pure ZooKeeper for more fine-grained work if needed
• Maintains layers of each geospatial node
• Maintains layers of all external geoserver
nodes
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS

7. Apache Spark
• Generic engine for Big Data processing
• Tabular data (e.g. CSV files)
• Geospatial big data processing is still embryonic
• We attempt towards this
• Parallel loading of geospatial layers
• Each spark worker will have particular layer regions
• From different geospatial nodes
• Evaluating functions (fitness, cost, etc) in parallel for a
region
• Model-based
• Each model needs specific layers
• Utilises specific function(s)
• Development of modules for Spark is in progress
• Currently experimenting on monolithic geospatial
08/12/2016

8. Technologies and Frameworks
Back-end
• Java EE version 8
• Hibernate and Spring frameworks
• ORM and persistence framework
• Postgres with PostGIS extension and Geoserver
for the geospatial data manipulation
• Restful web services
• Spring web services
• JAX-RS - Jersey Framework implementation
• Apache Tomcat as an application server
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS

9. Technologies and Frameworks
Front-End
• Liferay 6.2 portal framework compliant
• Portlet development
• Bootstrap 2
• Javascript and Jquery
• OpenLayers for layer visualisation
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS

10. Technologies and Frameworks
Front-End
• Liferay 6.2 portal framework compliant
• Portlet development
• Bootstrap 2
• Javascript and Jquery
• OpenLayers for layer visualisation
08/12/2016 UoA course: DATA BASE MANAGEMENT SYSTEMS