# Generating a Map of the World To generate a map of the world using the built-in [basemap profile](planetiler-basemap), you will need a machine with Java 16 or later installed and at least 10x as much disk space and 1.5x as much RAM as the `planet.osm.pbf` file you start from. All testing has been done using Digital Ocean droplets with dedicated vCPUs ([referral link](https://m.do.co/c/a947e99aab25)) and OpenJDK 17 installed through `apt`. Planetiler splits work among available CPUs so the more you have, the less time it takes. ### 1) Choose the Data Source First decide where to get the `planet.osm.pbf` file: - One of the [official mirrors](https://wiki.openstreetmap.org/wiki/Planet.osm) - The [AWS Registry of Open Data](https://registry.opendata.aws/osm/) public S3 mirror (default) - Or a [Daylight Distribution](https://daylightmap.org/) snapshot from Facebook that includes extra quality/consistency checks, and add-ons like ML-detected roads and buildings. Combine add-ons and re-number using [osmium-tool](https://osmcode.org/osmium-tool/): ```bash osmium apply-changes daylight.osm.pbf admin.osc.bz2 -o everything.osm.pbf osmium renumber everything.osm.pbf -o planet.osm.pbf ``` NOTE: you need at least `admin.osc.bz2` for the `boundary` layer to show. This takes about 2.5 hours and needs as much RAM as the `planet.osm.pbf` size. ### 2) Run Planetiler Download the [latest release](https://github.com/onthegomap/planetiler/releases/latest) of `planetiler.jar`. Then run `java -Xms100g -Xmx100g -jar planetiler.jar` (replacing `100g` with 1.5x the `planet.osm.pbf` size) with these options: - `--bounds=world` to set bounding box to the entire planet - `--nodemap-type=sparsearray` to store node locations in a sparse array instead of a sorted table - `sortedtable` is more efficient when there are large gaps in ID spaces (i.e. extracts) and `sparsearray` is more efficient with no/few ID gaps (planet, or renumbered extracts). - `--nodemap-storage=ram` to store all node locations in RAM instead of a memory-mapped file - when using `ram` give the JVM 1.5x the input file size instead of 0.5x when using `mmap` - `--download` to fetch [other data sources](NOTICE.md#data) automatically - One of these to point planetiler at your data source: - `--osm-path=path/to/planet.osm.pbf` to point Planetiler at a file you downloaded - `--osm-url=http://url/of/planet.osm.pbf` to download automatically - `--osm-url=s3:211011` to download a specific snapshot from the AWS Registry of Open Data or `--osm-url=s3:latest` to download the latest snapshot - `--area=planet` to use the file in `./data/sources/planet.osm.pbf` or download the latest snapshot from AWS S3 mirror if missing. Run with `--help` to see all available arguments. NOTE: The default basemap profile merges nearby buildings at zoom-level 13 (for example, see [Boston](https://onthegomap.github.io/planetiler-demo/#13.08/42.35474/-71.06597)). This adds about 14 CPU hours (~50 minutes with 16 CPUs) to planet generation time and can be disabled using `--building-merge-z13=false`. ## Example To generate the tiles shown on https://onthegomap.github.io/planetiler-demo/ I used the `planet-211011.osm.pbf` (64.7GB) S3 snapshot, then ran Planetiler on a Digital Ocean Memory-Optimized droplet with 16 CPUs, 128GB RAM, and 1.17TB disk running Ubuntu 21.04 x64 in the nyc3 location. First, I installed java 17 jre and screen: ```bash apt-get update && apt-get install -y openjdk-17-jre-headless screen ``` Then I added a script `runworld.sh` to run with 100GB of RAM: ```bash #!/usr/bin/env bash set -e java -Xmx100g -Xms100g \ -XX:OnOutOfMemoryError="kill -9 %p" \ -jar planetiler.jar \ `# Download the latest planet.osm.pbf from s3://osm-pds bucket` \ --area=planet --bounds=world --download \ `# Accelerate the download by fetching the 10 1GB chunks at a time in parallel` \ --download-threads=10 --download-chunk-size-mb=1000 \ `# Also download name translations from wikidata` \ --fetch-wikidata \ --mbtiles=output.mbtiles \ --nodemap-type=sparsearray --nodemap-storage=ram 2>&1 | tee logs.txt ``` Then I ran this in the background using screen, so it would continue if my shell exited: ```bash screen -d -m "./runworld.sh" tail -f logs.txt ``` It took 3h21m (including 12 minutes downloading source data) to generate a 99GB `output.mbtiles` file. See the [full logs](planet-logs/v0.1.0-planet-do-16cpu-128gb.txt) from this run or this summary that it printed at the end: ``` 3:21:03 DEB [mbtiles] - Tile stats: 3:21:03 DEB [mbtiles] - z0 avg:71k max:71k 3:21:03 DEB [mbtiles] - z1 avg:171k max:192k 3:21:03 DEB [mbtiles] - z2 avg:258k max:449k 3:21:03 DEB [mbtiles] - z3 avg:117k max:479k 3:21:03 DEB [mbtiles] - z4 avg:51k max:541k 3:21:03 DEB [mbtiles] - z5 avg:23k max:537k 3:21:03 DEB [mbtiles] - z6 avg:14k max:354k 3:21:03 DEB [mbtiles] - z7 avg:11k max:451k 3:21:03 DEB [mbtiles] - z8 avg:6.5k max:356k 3:21:03 DEB [mbtiles] - z9 avg:6k max:485k 3:21:03 DEB [mbtiles] - z10 avg:2.7k max:285k 3:21:03 DEB [mbtiles] - z11 avg:1.3k max:168k 3:21:03 DEB [mbtiles] - z12 avg:741 max:247k 3:21:03 DEB [mbtiles] - z13 avg:388 max:286k 3:21:03 DEB [mbtiles] - z14 avg:340 max:1.7M 3:21:03 DEB [mbtiles] - all avg:395 max:0 3:21:03 DEB [mbtiles] - # features: 2,832,396,934 3:21:03 DEB [mbtiles] - # tiles: 264,204,266 3:21:03 INF [mbtiles] - Finished in 4,668s cpu:66,977s avg:14.3 3:21:03 INF - Finished in 12,064s cpu:156,169s avg:12.9 3:21:03 INF - FINISHED! 3:21:03 INF - ---------------------------------------- 3:21:03 INF - overall 12,064s cpu:156,169s avg:12.9 3:21:03 INF - download 169s cpu:1,070s avg:6.3 3:21:03 INF - wikidata 553s cpu:3,825s avg:6.9 3:21:03 INF - lake_centerlines 0.9s cpu:2s avg:1.8 3:21:03 INF - water_polygons 96s cpu:1,150s avg:12 3:21:03 INF - natural_earth 6s cpu:21s avg:3.7 3:21:03 INF - osm_pass1 921s cpu:5,177s avg:5.6 3:21:03 INF - osm_pass2 5,234s cpu:73,527s avg:14 3:21:03 INF - boundaries 14s cpu:18s avg:1.3 3:21:03 INF - sort 407s cpu:4,403s avg:10.8 3:21:03 INF - mbtiles 4,668s cpu:66,977s avg:14.3 3:21:03 INF - ---------------------------------------- 3:21:03 INF - features 192GB 3:21:03 INF - mbtiles 99GB ``` To generate the extract for [the demo](https://onthegomap.github.io/planetiler-demo/) I ran: ```bash # install node and tilelive-copy curl -fsSL https://deb.nodesource.com/setup_16.x | sudo -E bash - apt-get install -y nodejs npm install -g @mapbox/tilelive @mapbox/mbtiles # Extract z0-4 for the world tilelive-copy --minzoom=0 --maxzoom=4 --bounds=-180,-90,180,90 output.mbtiles demo.mbtiles # Extract z0-14 for just southern New England tilelive-copy --minzoom=0 --maxzoom=14 --bounds=-73.6346,41.1055,-69.5464,42.9439 output.mbtiles demo.mbtiles ``` Then I ran [extract.sh](https://github.com/onthegomap/planetiler-demo/blob/main/extract.sh) in the planetiler-demo repo to extract tiles from the mbtiles file to disk.