Towards an open source tool stack for e-commerce search
Chorus makes deploying powerful ecommerce search easier by shifting the buy vs build decision in favour of build, so you can own your search! Chorus deals with three issues:
Starting from Scratch is Time Consuming Downloading an open source search engine isn't enough. It's like being provided with all the parts of a Lego model, but without building instructions ;-) . We need a better baseline to quickly get started.
Integration of Tooling is Hard Search isn't just a query running on an index of data. It's also the operational monitoring, the analytics and relevance tooling, that goes into it. Every team that starts, faces the penalties of starting from scratch, integrating an ecosystem of options.
Sharing Knowledge is a Must! It isn't enough to just have conference talks. We need code and data samples in order to share knowledge about improving ecommerce search. Chorus is a public environment that you can use to profit from the community and also to share your next great idea!
This is the project that enables Chorus to use Elasticsearch as the search engine. For those interested in the Solr version of this stack: You can visit the Solr version of Chorus
Want to stay up-to-date with the community? Visit https://querqy.org/ to learn more, and join the E-Commerce Search Slack group for tips, tricks, help and news on what's new in the Chorus ecosystem.
Working with macOS? Pop open all the tuning related web pages with one terminal command:
open http://localhost:4000 http://localhost:9200 http://localhost:5601 http://localhost:9000 http://localhost:3000
We are trying to strike a balance between making the setup process as easy and fool proof as possible, with the need to not hide too much of the interactions between the projects that make up Chorus.
If you are impatient, we provide a quick start script, ./quickstart.sh
that sets Chorus up for you. However, I recommend you go through Kata 0: Setting up Chorus, to get a picture of what's running in the stack.
After setting up Chorus you can check out Kata 1: Lets Optimize a Query for an introduction to the world of active search management.
More Katas can be found in the Solr version of Chorus and many can be transferred to this Elasticsearch based stack. Some are also covered in a video series called Meet Pete. Feel free to open PRs to add Katas you find useful or open issues if you want to see specific Katas included. Every contribution is welcome!
To start your environment, but still run each command to set up the integrations manually, run:
docker-compose up --build -d
The quickstart script will launch Elasticsearch, download and index the sample product data for the ecommerce index:
./quickstart.sh
If you want to add in the offline lab environment based on Quepid, then tack on the --with-offline-lab
parameter:
./quickstart.sh --with-offline-lab
Try out vector search with Chorus by using the --with-vector-search
parameter
./quickstart.sh --with-vector-search
To include the observability features (Grafana, Prometheus, and Elasticsearch Exporter), run:
./quickstart.sh --with-observability
To see what is happening in the Chorus stack you can tail the logs for all the components via:
docker-compose logs -tf
If you want to see the logs of just one component of the Chorus stack, use:
docker-compose ps # list out the names of the components
docker-compose logs -tf elasticsearch # tail elasticsearch only
To stop all containers, you can run:
./quickstart.sh --stop
To destroy your environment (including any volumes created, like the mysql DBs), just run:
docker-compose down -v
or:
./quickstart.sh --shutdown
If Docker is giving you a hard time, then some options are:
docker system prune # removes orphaned images, networks, etc.
docker system prune -a --volumes # removes all images, clears out your Docker diskspace if you full.
You may also have to increase the resources given to Docker - up to 4 GB RAM and 2 GB Swap space.
The Chorus project includes some public, sample datasets. These datasets enable the community to learn, experiment and collaborate in a safe manner and are a key part of demonstrating, how to build measurable and tunable ecommerce search, with open source components.
The sample product data is generously sourced from Icecat and is licensed under their Open Content License.
The version of the Icecat product data that Chorus provides has the following changes:
Of course, contributions are very welcome to improve Chorus - The Elasticsearch Edition!