This document discusses using NoSQL databases for geographic search and location-based services. It explains that geographic data is complex to store in SQL databases due to its multiple dimensions and large size. NoSQL databases provide alternatives like quadtrees and R-trees to index and search geographic data more efficiently. The document provides examples of geographic implementations in databases like MongoDB, Lucene, ElasticSearch, and Neo4j. It also gives examples of building point of interest search using technologies like SQL, Lucene, and Hibernate Search.

1. No(Geo)SQL
Geographic search in (No)SQL

2. 8 years mappy.com as platform architect
and deputy CTO
Founding partner of NovaCodex since 2008
@NHelleringer
Me

3. Geo in databases
What the point ?
Why

4. Geo in databases challenges
 Data is complex to store in SQL
 Data is bi dimensional
 Data is dense
 Data is huge
Why

5. Multiples dimensions but B-trees sort on one
Query dependent index sorting calculation
New data structures and algorithms to handle dimensions
A two phases search : select and then filter
Origin (challenge)

6. Geographic Information Systems
handling of geometric objects
The origins of geography in the information systems are in the needs
administrations had to handle data of the real world :
 Geology / Geography
 Roads, administrative areas for cadastral surveys
 Census data
 Infrastructure elements (water delivery network, electrical delivery
network, communication network)
Other needs came when the data became available and use the same
tools :
 Geo marketing (market areas)
Origin (needs)

7. All you ever hated about SQL … and more !
 Complex SQL additions
 Full size complex normalized API
 Vendor dependent implementations
 Not scalable
How

8. The Open Geospatial Consortium edits a norm : OpenGIS
Oracle
SQL Server
Quad Trees / R-Trees
4 level Grid Index
Oracle 4 side dev (1984)
Since 2008 version (2007)
integrated in Oracle 7 (1992)
PostgreSQL
Spatialite
R-tree-over-GiST
R-Trees
since PostGIS 1.0 for 8.0
since 3.6.0 (Mar 2008)
(Apr 2005)
MySQL since Feb 2005, DB2 Spatial Extender since July 2006, Ingres added
support very recently
Hibernate Spatial is a generic access to OpenGis implementations
GIS Software as ESRI, MapInfo, GeoConcept, QuantumGIS use this standard to
access data
Current Implementations (traditionnal SGBD)

10. Do we need all this ?
Is Geo only for geo
centric companies ?
Puzzled ?

11. LBS changed everything !
 Maps, geocoding & route planning available
 Platforms handle millions of hits/day
 Available through multiples APIs
 Often for free
How

12. MAPS GEOCODING
Data is huge and complex Data is huge
objects
Indexing is geo
Not a geo problem
Processing capabilities required Expertise extremely valued
Provided Provided
ROUTE PLANNING POI SEARCH
Data is huge Data is less huge (your
Not a geo problem business size)
Not shard able Indexing is geo
May shard
Provided Less relevant
How

13. Location aware data
handling of data associated with a latitude/longitude tuple
Location became a search criterion :
 Geo search
The map/the geography is the center of the search process
 Proximity search
The location is one in many criteria to refine a search
Origin (needs)

15. Does NoSQL
help ?
New Solutions ?

16. Why does Geo fits a NoSQL approach ?
Geo does not fit in traditional ‘pure’ DBMS : First normal form
(1NF), many dimensions in one column break the rules
(48,23) <?> (47,25)
Geo Objects hard to be strictly defined by SQL types : they are
fickle
Tim Anglade ‘No SQL for fun and profit’ : Geo/hierarchical is
one of seven forms of NoSQL to date
Geo as a NoSQL Technology

17. Extensions to SQL or NoSQL data stores
 Quad-trees
 R-trees
Geo as a NoSQL Technology

18. quad-tree

19. Search steps
1) Select
 Compute level
 Compute boxes ids
 Fetch boxes
2) Filter
 Compute distance
 Select result set
Limits
 High levels
How does it work ?

20. r-tree

21. Spatial Lucene/Solr, Elastic Search
 Quad tree labels in Lucene tokens
 Tile indices or GeoHash labels
GeoCouch
 R-tree in Erlang
Neo4J Spatial
 R-tree & quad-tree
 Object can be stored as graph elements
Current Implementations (NoSQL databases)

22. MongoDb
 Geo hashes into MongoDB B-trees
 Shard support incoming
 Spherical model since 1.7
Pincaster
 In memory quad tree
Current Implementations (NoSQL databases)

23. How do I build PoI search ?
How

24. Do it in pure SQL !!
Use a clustered long, lat index :
o Select is done by the cluster on longitude
(whish is more selective than latitude !)
o Bounding box requests are handled on the
index level as latitude is included
o Filter with distance calculation can be
done by a stored procedure on the
database side or in application code
POI Search

25. Lucene via Hibernate Search
o Available in 4.2 beta 1
o Annotation based
o Simple to step in
o Refine by usage
o DSL supported
POI Search

26. @Indexed
@Spatial
public class Hotel {
@Latitude
Double latitude;
@Longitude
Double longitude;
[...]
Sample indexation code

27. QueryBuilder builder =
fullTextSession.getSearchFactory()
.buildQueryBuilder().forEntity( PoI.class ).get();
double centerLatitude= 24;
double centerLongitude= 31.5;
Query luceneQuery = builder.spatial()
.onCoordinates( PoI.class.getName() )
.within( 50, Unit.KM )
.ofLatitude( centerLatitude )
.andLongitude( centerLongitude )
.createQuery();
Sample search code

28. Thank you for listening !
End !

29. http://www.slideshare.net/timanglade/nosql-for-fun-profit
http://en.wikipedia.org/wiki/First_normal_form
http://en.wikipedia.org/wiki/Quadtree
http://technet.microsoft.com/en-us/library/bb964712.aspx
http://www.nsshutdown.com/projects/lucene/whitepaper/locallucene_v2.html
http://vmx.cx/cgi-bin/blog/index.cgi/geocouch-geospatial-queries-with-
couchdb:2008-10-26:en,CouchDB,Python,geo
http://wiki.neo4j.org/content/Neo4j_Spatial
http://www.osgeo.org/
http://relation.to/Bloggers/SpatialQueriesFirstBetaForHibernateSearch42IsAv
ailable
http://www.novacodex.net/
Ref