3.8 KiB
Run
When developing locally, this directory will contain run-time data required for the search engine. In a clean check-out, it only contains the tools required to bootstrap this directory structure.
Requirements
While the system is designed to run bare metal in production, for local development, you're strongly encouraged to use docker or podman. These are a bit of a pain to install, but if you follow this guide you're on the right track.
Set up
To go from a clean check out of the git repo to a running search engine, follow these steps. You're assumed to sit in the project root the whole time.
1. Run the one-time setup, it will create the
basic runtime directory structure and download some models and data that doesn't come with the git repo because git deals poorly with large binary files.
$ run/setup.sh
2. Compile the project and build docker images
$ ./gradlew assemble docker
3. Initialize the database
$ docker-compose up -d mariadb
$ ./gradlew flywayMigrate
4. Bring the system online. We'll run it in the foreground in the terminal this time
because it's educational to see the logs. Add -d to run in the background.
$ docker-compose up
5. You should now be able to access the system.
| Address | Description |
|---|---|
| https://localhost:8080/ | User-facing GUI |
| https://localhost:8081/ | Operator's GUI |
Note that the operator's GUI does not perform any sort of authentication. Preferrably don't expose it publicly, but if you absolutely must, use a proxy or Basic Auth to add security.
6. Download Sample Data
A script is available for downloading sample data. The script will download the data from https://downloads.marginalia.nu/ and extract it to the correct location.
The system will pick the data up automatically.
$ run/download-samples l
Four sets are available:
| Name | Description |
|---|---|
| s | Small set, 1000 domains |
| m | Medium set, 2000 domains |
| l | Large set, 5000 domains |
| xl | Extra large set, 50,000 domains |
Warning: The XL set is intended to provide a large amount of data for setting up a pre-production environment. It may be hard to run on a smaller machine. It's barely runnable on a 32GB machine; and total processing time is around 5 hours.
The 'l' set is a good compromise between size and processing time and should work on most machines.
7. Process the data
Bring the system online if it isn't (see step 4), then go to the operator's GUI (see step 5).
- Go to
Storage - Go to
Crawl Data - Find the data set you want to process and click
[Info] - Click
[Process and load]
This will take anywhere between a few minutes to a few hours depending on which
data set you downloaded. You can monitor the progress from the Overview tab
under Processes.
First the CONVERTER is expected to run; this will process the data into a format that can easily be inserted into the database and index.
Next the LOADER will run; this will insert the data into the database and index.
Next the link database will repartition itself, and finally the index will be
reconstructed. You can view the process of these steps in the Jobs listing.
8. Run the system
Once all this is done, you can go to the user-facing GUI (see step 5) and try a search.
Important! Use the 'No Ranking' option when running locally, since you'll very likely not have enough links for the ranking algorithm to perform well.
Experiment Runner
The script experiment.sh is a launcher for the experiment runner, which is useful when
evaluating new algorithms in processing crawl data.