Oopse, meant for this to go to the whole list.
-------- Original Message --------
Subject: Re: [OSM-dev] OSM and MongoDB
Date: Tue, 12 Apr 2011 15:26:41 -0500
From: Nolan Darilek <no...@thewordnerd.info>
To: Ian Dees <ian.d...@gmail.com>
I had/am having a somewhat bad experience storing OSM data in MongoDB.
Initially I stored all map data in MongoDB, but queries took ages. The
same queries that happen in 100-200 MS now often took nearly a second.
Additionally, some took upwards of 5, and I even found spots on my map
sparsely populated with points, but which reliably performed the queries
I need in 30+ seconds.
I filed a thorough bug in their tracker, including a dataset and queries
that reliably duplicated the issue. It was marked wontfix, I abandoned
MongoDB, and it was apparently re-opened and fixed several months later.
So perhaps it's a non-issue now.
I'm still using MongoDB for part of my current project, user POI
storage. It does indeed use geohashes, and I'm experiencing strange
accuracy issues. My platform is pedestrian navigation with many small
distance queries. Points in the non-MongoDB dataset are reliably
detected in a radius roughly 100 meters around the traveler. Points in
MongoDB queried with the same bounding boxes don't appear until they're
within 30-40 meters. I recently updated from an older version to a new
build of 1.8. The older version widely varied the detection range. Some
points were detected 100 or so meters out, while others weren't picked
up until 30 or so. It was always the same points, too. The point for my
apartment remains reliably visible for ~100 meters or so, while the
corner store and restaurant didn't appear until I was very close. 1.8 at
least appears to be consistent, always detecting at 30 meters or so. I
can only assume that this is a geohash oddity that only appears for very
small differences, something that works out to rounding error for larger
values.
I like MongoDB for many things, but not for geospatial data more
complicated than a series of points. I'm working on migrating user/POI
storage to a geospatial store.
On 04/12/2011 01:20 PM, Ian Dees wrote:
Yep, and I think Mongo uses geohashes as their index behind the
scenes. One of the problems with that, though, is they have some
arbitrary length that they compute the geohash to and when you have
lots of points (as OSM data does) the buckets they're searching are
very full.
On Tue, Apr 12, 2011 at 1:00 PM, Steve Coast <st...@asklater.com
<mailto:st...@asklater.com>> wrote:
bbox queries using the built in spatial indexing presumably? OSM
has it's own magical bitmask for that, that may also be as fast in
mongo, who knows.
On 4/11/2011 5:58 PM, Ian Dees wrote:
On Mon, Apr 11, 2011 at 6:36 PM, Sergey Galuzo
<ser...@microsoft.com <mailto:ser...@microsoft.com>> wrote:
Hi,
I am working on evaluation of MongoDB for several storage
solutions at hand. Some of them resemble current OSM editing
database. I have heard that OSM dev is/was evaluating MongoDB
also. I was wondering whether it possible to share the findings?
In my experimentation with MongoDB (seen here:
https://github.com/iandees/mongosm/) I found it to be very slow.
Inserts were speedy, but bounding-box queries took a long time.
The most recent dev version of MongoDB includes "multi-location
documents" support:
http://www.mongodb.org/display/DOCS/Geospatial+Indexing#GeospatialIndexing-MultilocationDocuments
This would allow a single way document to be indexed at multiple
locations and vastly speed up the map query.
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