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Postgis versus osmconvert - retrieval methods for German

sayhello

Geonewbie
hello dear geo-clubber, good morning,

what should i use:

PostGis as a solution for getting a database populated by osm2pgsql or osmconvert / -filter to create csv-sheets

aimed is to transform data out of German osm-pbf-files - in order to get the data (not to creat maps again)

see the source (s)= http://download.geofabrik.de/europe/germany.html ranging form 10 MB (Bremen) to 390 MB (Nordrhein Westfalen) the osm.pbf-files are not too big; Question: which method is the best - the most appropiate? - to store the results in a mysql-db or just have big calc-sheets (with csv-data)

- only straightforward from files that
- no backimport of data to OSM from a .csv file

i want to gather data from .o5m & pbf file - several ways are possible: what is wanted: i look for restaurants - with all of the following tags:
Code:
@id @lon @lat amenity name adress [as town, street, housnumber] website and mailadress.
All interests are based on the regions of Germany see http://download.geofabrik.de/europe/germany.html i have several files i want to work with - ranging form 10 MB (Bremen) to 390 MB (Nordrhein Westfalen) the osm.pbf-files are not too big;

so the main question: which method is the best and the most appropiate? - to store the results in a mysql-db or just have big calc-sheets (with csv-data)

Well what i want to accomplish can be done with osmfilter/osmconvert too. So i guess that for my OSM purposes it is easier to filter and manipulate data in simple CSV format ... because there is no need to learn complex database queries.

For example:

Code:
$ ./osmfilter bremen.o5m --keep="addr:country= and addr:city= and addr:street=" --ignore-dependencies | ./osmconvert - --csv="@oname @id @lon @lat addr:country addr:city addr:street"
we can do alot with osmconvert and osmfilter. :: using osmconvert to csv file.... eg: . see the many sites that i get when searching for csv ...they show that we can do lots of things with osmconvert... and filter. dont they!?


but on the other handsite:

since i can do lots of things with overpass-api i wondder how good (and easy) i can transforme the data to the mysql-db.:

see the overpass-api request:

Code:
query type="node">
  <has-kv k="place" v="city"/>
  <has-kv k="name" v="any town "/>
</query>
<query type="node">
  <around radius="1000"/>
    <has-kv k="shop"/>
</query>
<print/>

and the outconme;

Code:
osm version="0.6" generator="Overpass API">
<note>
The data included in this document is from www.openstreetmap.org. The data is made available under ODbL.
</note>
<meta osm_base="2013-03-07T14:54:02Z" areas="2013-03-07T10:37:02Z"/>
<node id="240486180" lat="50.9744274" lon="3.0152858">
<tag k="addr:housenumber" v="9"/>
<tag k="addr:street" v="Marktplaats"/>
<tag k="amenity" v="cafe"/>
<tag k="email" v="[email protected]"/>
<tag k="name" v="Paviljoentje"/>
<tag k="opening_hours" v="Mo-Su 09:00+; Tu off; Th 09:00-14:00"/>
<tag k="phone" v="+3251636211"/>
<tag k="website" v="http://www.paviljoentjestaden.be"/>
</node>
<node id="244312208" lat="51.2461401" lon="5.4390455">
<tag k="amenity" v="cafe"/>
<tag k="created_by" v="JOSM"/>
<tag k="name" v="De Club"/>
</node>
so - well what would you say....

i think i can reach the most of my desired goals with osmconvert and -osmfilter. Especially if i focus on the the regional germany dataset.
Note; All interests are based on the regions of Germany see http://download.geofabrik.de/europe/germany.html i have several
files i want to work with - ranging form 10 MB (Bremen) to 390 MB (Nordrhein Westfalen) the osm.pbf-files are not too big;

what do you advice - !? i guess that i can go with osmconvert and -filter to get csv-files. Since the files that result out of the GERMAN regional db are not toooo big!? What do you say!?

look foward to hear from you
 

moenk

Administrator
Teammitglied
Maybe you don't want to process everything by yourself. Consider using the Overpass-API like in this example: http://www.moenk.de/archives/75-Punkte-der-OpenStreetMap-in-Garmin-POI-konvertieren.html
 
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