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Geoindexing with MongoDB
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Leszek Krupiński
May 17, 2012
Programming
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49
Geoindexing with MongoDB
Leszek Krupiński
May 17, 2012
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Transcript
Geoindexing with MongoDB Leszek Krupiński WebClusters 2012
About me
On-line since 1997
Funny times
1 hr of internet for 1 USD
None
None
First social site: geocities
My first web page
What do I do now
Day-time job Managing team of developers for Polish Air Force
Side: consulting, optimizing, desiging
Buzzwords incoming!
The Internet 2008
Web 2.0
http://en.wikipedia.org/wiki/File:Web_2.0_Map.svg CC-BY-SA-2.5
Be social in your bedroom
alone.
The Internet 2012
Web 3.0
None
Why geospatial?
Needs shifted
Why? Because they could.
None
None
None
How to implement?
Database. Duh.
Keep, but also query
Is there a person at 53.438522,14.52198? Nope. Is there a
person at 53.438522,14.52199? Nope. Is there a person at 53.438522,14.52199? Yeah, here’s Johnny!
Not too useful.
Give me nearby homies. Within the range of 1 km
there is: • Al Gore (53.438625,14.52103) • Bill Clinton (53.432531,14.55127) • Johnny Bravo (53.438286,14.52363)
Now that’s better.
Geoindexing. Nothing new.
Oracle, PostreSQL, Lucene/Solr, even MySQL (via extensions)
SELECT c.holding_company, c.location FROM competitor c, bank b WHERE b.site_id
= 1604 AND SDO_WITHIN_DISTANCE(c.location, b.location, ’distance=2 unit=mile’) = ’TRUE’ ORACLE
SQL is so last year
Let’s use something cool
MongoDB. Because all the cool kids use NoSQL now
None
Why MongoDB?
Choose your NoSQL wise.
NoSQL in MongoDB • Document –based • Queries (JS-like syntax)
• JSON-like storage
Why MongoDB? Use Cases • Archiving • Event logging •
Document and CMS • Gaming • High volume sites • Mobile • Operational datastore • Agile development • Real-time stats Features • Ad hoc queries • Indexing • Replication • Load Balancing • File Storage • Aggregation • Server-side JavaScript • Capped collections http://en.wikipedia.org/wiki/Mongodb
Back to geo.
{ loc: [ 52.0, 21.0 ], name: ”Warsaw”, type: ”City”
}
db.nodes.ensureIndex({loc: '2d'})
That’s it.
Query • Exact o db.places.find( { loc : [50,50] }
) • Near o db.places.find( { loc : { $near : [50,50] } } ) • Limit o db.places.find( { loc : { $near : [50,50] } } ).limit(20) • Distance o db.places.find( { loc : { $near : [50,50] , $maxDistance : 5 } } ).limit(20)
Compound index • db.places.ensureIndex( { location : "2d" , category
: 1 } ); • db.places.find( { location : { $near : [50,50] }, category : 'coffee‚ } );
Bound queries • box = [ [40.73083, -73.99756], [40.741404, -73.988135]
] • db.places.find( {"loc" : {"$within" : {"$box" : box }} } )
Problems
Units
Coordinates in arc units Distance in kilometers
In query
earthRadius = 6378 // km multi = earthRadius * PI
/ 180.0 range = 3000 // km … maxDistance : range * multi…
In results
pointDistance = distances[0].dis / multi
Earth is not flat.
Problem: can’t use linear distance
Earth isn’t flat too.
Solution? Use approximation.
MongoDB has it built-in distances = db.runCommand( { geoNear :
"points", near : [0, 0], spherical : true, maxDistance : range / earthRadius /* to radians */ } ).results
Focus: runCommand distances = db.runCommand({ geoNear : "points" …
Sort by distance Only with runCommand
Automatically sorted • db.runCommand( { geoNear : "places" , near
: [50,50], num : 10 } ); • { "ns" : "test.places", "results" : [ { "dis" : 69.29646421910687, "obj" : … }, { "dis" : 69.29646421910687, "obj" : … }, … ], … }
Demo
OpenStreetMaps database of Poland imported into MongoDB
14.411.552 nodes
3GB of raw XML data
PHP in virtual machine
Imported about 100.000 nodes every 10s.
Pretty cool, eh?
Kudos to Derick Rethans Part of this talk was inspired
by his talk
Questions?
Thanks! Rate me at https://joind.in/talk/view/6475
Geoindexing with MongoDB supplement Leszek Krupiński WebClusters 2012
Why MongoDB?
Evaluate.
PostGIS is cool too. (but it’s SQL, meh)
Why MongoDB? Use Cases • Archiving • Event logging •
Document and CMS • Gaming • High volume sites • Mobile • Operational datastore • Agile development • Real-time stats Features • Ad hoc queries • Indexing • Replication • Load Balancing • File Storage • Aggregation • Server-side JavaScript • Capped collections http://en.wikipedia.org/wiki/Mongodb
If you need other features of MongoDB, use it
If you don’t, evaluate.
Evaluate.
Demo (hopefully)
Questions?
Please leave feedback! Rate me at https://joind.in/6475