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OSM Fastly Logs

This is ofastlylog, the software that processes OpenStreetMap logs from Fastly.

Install

Packaged versions of ofastlylog can be installed like any other python software. To do so in a virtual environment do

python3 -m venv venv
venv/bin/pip install ofastlylog
venv/bin/ofastlylog --help

Contributing

This code is difficult to contribute to unless you have access to the OSMF AWS accounts. Recommendations to improve this are welcome.

Development is done using uv.

git clone https://github.com/pnorman/ofastlylog.git
cd ofastlylog
uv sync
uv run pre-commit install
uv run ofastlylog --help

Development could also be done using a venv and pip but this is not officially supported

python3 -m venv venv
venv/bin/pip install -e .
venv/bin/ofastlylog --help

Usage

AWS credentials need to be set up for ofastlylog to access the service logs. In a typical setup this is done with

export AWS_PROFILE=osm-service-logs

ofastlylog has two commands right now: one to create tables, and another to perform hourly tasks.

All commands take a list of service tables to create or process. Specify these with --<servicename> <tabletype>, e.g. --tile success for the tile.openstreetmap.org success table. See Table Types for a full list of combinations.

ofastlylog tools

Contains tools for creating and working with setup tables

ofastlylog tools create-table

Creates tables in athena.

ofastlylog tools check-hour

TODO: Check if a particular hour has data in the table

ofastlylog process

Peform log generation and processing

ofastlylog process hourly

Perform log processing intended to be run hourly

Table types

Table --tile --vector --nominatim
base
success
minimized Not implemented not impelemented not impelemented

Architecture

Several OSMF-hosted services use Fastly as a CDN. Fastly is set up to deposit compressed log files in a s3 bucket. The log files contain line-delimited JSON objects deposited every 10 minutes.

Because compressed text is slow to read, these files are processed with ofastlylog process hourly. This creates a number of tables. All tables are stored as Parquet data with hourly partitioning.

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