Download the geopackage from http://opendata.champs-libres.be/beautiful-contour-belgium.zip, convert it to shp and place it into the pbf/shp folder under the name "contours.shp". It will be mounted as written in the `docker-compose.yml` file.
The shp is imported using `shp2pgsql` in the import step, assuming EPSG:31370 as the input shp CRS.
Download the hillshade at http://opendata.champs-libres.be/hillshade_belgium_EPSG3857.zip and place the tif file in the pdf folder, as mounted in the `docker-compose.yml` file.
Download a pbf and a poly file of your choice on https://download.geofabrik.de and put it in the `pbf` folder. Change the lines of the pbf and poly paths in the volumes in the `docker-compose.yml` file
The tiles are available on http://192.168.176.2/ or something like that. Have a look at the docker container to know which is the IP address: there is a message like "Could not reliably determine the server's fully qualified domain name, using 192.168.176.2.". (should be on http://localhost:8080/ though...)
[![Docker Image Version (latest semver)](https://img.shields.io/docker/v/overv/openstreetmap-tile-server?label=docker%20image)](https://hub.docker.com/r/overv/openstreetmap-tile-server/tags)
This container allows you to easily set up an OpenStreetMap PNG tile server given a `.osm.pbf` file. It is based on the [latest Ubuntu 18.04 LTS guide](https://switch2osm.org/serving-tiles/manually-building-a-tile-server-18-04-lts/) from [switch2osm.org](https://switch2osm.org/) and therefore uses the default OpenStreetMap style.
Next, download an `.osm.pbf` extract from geofabrik.de for the region that you're interested in. You can then start importing it into PostgreSQL by running a container and mounting the file as `/data/region.osm.pbf`. For example:
Note that the import process requires an internet connection. The run process does not require an internet connection. If you want to run the openstreetmap-tile server on a computer that is isolated, you must first import on an internet connected computer, export the `osm-data` volume as a tarfile, and then restore the data volume on the target computer system.
Also when running on an isolated system, the default `index.html` from the container will not work, as it requires access to the web for the leaflet packages.
If your import is an extract of the planet and has polygonal bounds associated with it, like those from [geofabrik.de](https://download.geofabrik.de/), then it is possible to set your server up for automatic updates. Make sure to reference both the OSM file and the polygon file during the `import` process to facilitate this, and also include the `UPDATES=enabled` variable:
It is also possible to let the container download files for you rather than mounting them in advance by using the `DOWNLOAD_PBF` and `DOWNLOAD_POLY` parameters:
By default the container will use openstreetmap-carto if it is not specified. However, you can modify the style at run-time. Be aware you need the style mounted at `run` AND `import` as the Lua script needs to be run:
If you do not see the expected style upon `run` double check your paths as the style may not have been found at the directory specified. By default, `openstreetmap-carto` will be used if a style cannot be found
**Only openstreetmap-carto and styles like it, eg, ones with one lua script, one style, one mml, one SQL can be used**
Your tiles will now be available at `http://localhost:8080/tile/{z}/{x}/{y}.png`. The demo map in `leaflet-demo.html` will then be available on `http://localhost:8080`. Note that it will initially take quite a bit of time to render the larger tiles for the first time.
### Using Docker Compose
The `docker-compose.yml` file included with this repository shows how the aforementioned command can be used with Docker Compose to run your server.
Tiles that have already been rendered will be stored in `/data/tiles/`. To make sure that this data survives container restarts, you should create another volume for it:
Given that you've set up your import as described in the *Automatic updates* section during server setup, you can enable the updating process by setting the `UPDATES` variable while running your server as well:
This will enable a background process that automatically downloads changes from the OpenStreetMap server, filters them for the relevant region polygon you specified, updates the database and finally marks the affected tiles for rerendering.
Specify custom tile expiration settings to control which zoom level tiles are marked as expired when an update is performed. Tiles can be marked as expired in the cache (TOUCHFROM), but will still be served
until a new tile has been rendered, or deleted from the cache (DELETEFROM), so nothing will be served until a new tile has been rendered.
The example tile expiration values below are the default values.
The import and tile serving processes use 4 threads by default, but this number can be changed by setting the `THREADS` environment variable. For example:
If you are planning to import the entire planet or you are running into memory errors then you may want to enable the `--flat-nodes` option for osm2pgsql. You can then use it during the import process as follows:
Warning: enabling `FLAT_NOTES` together with `UPDATES` only works for entire planet imports (without a `.poly` file). Otherwise this will break the automatic update script. This is because trimming the differential updates to the specific regions currently isn't supported when using flat nodes.
You can find an example of the import performance to expect with this image on the [OpenStreetMap wiki](https://wiki.openstreetmap.org/wiki/Osm2pgsql/benchmarks#debian_9_.2F_openstreetmap-tile-server).
If you encounter such entries in the log, it will mean that the default shared memory limit (64 MB) is too low for the container and it should be raised:
renderd[121]: reason: Postgis Plugin: ERROR: could not resize shared memory segment "/PostgreSQL.790133961" to 12615680 bytes: ### No space left on device
For too high values you may notice excessive CPU load and memory usage. It might be that you will have to experimentally find the best values for yourself.