News search and recommendation tutorial - getting started on Docker
Our goal with this series is to set up a Vespa application for personalized news recommendations. We will do this in stages, starting with a simple news search system and gradually adding functionality as we go through the tutorial parts.
The parts are:
- Getting started - this part
- A basic news search application - application packages, feeding, query
- News search - sorting, grouping, and ranking
- Generating embeddings for users and news articles
- News recommendation - partial updates (news embeddings), ANNs, filtering
- News recommendation with searchers - custom searchers, doc processors
- News recommendation with parent-child - parent-child, tensor ranking
- Advanced news recommendation - intermission - training a ranking model
- Advanced news recommendation - ML models
There are different entry points to this tutorial. This one is for getting started using Docker on your local machine. Getting started on cloud.vespa.ai is coming soon. We will also have a version for pyvespa soon.
In this part we will start with a minimal Vespa application to get used to some basic operations for running the application on Docker. In the next part of the tutorial, we’ll start developing our application.
- Docker Desktop on Mac or Docker on Linux
- Git - or download the sample apps
- python 3
- Operating system: macOS or Linux
- Architecture: x86_64
- Minimum 6GB memory dedicated to Docker (the default is 2GB on Macs)
In upcoming parts of this series, we will have some additional python dependencies as we use PyTorch to train vector representations for news and users and train machine learning models for use in ranking.
A minimal Vespa application
This tutorial has a companion sample
news directory. Throughout the tutorial we will be
using support code from this application. Also, the final state of
each tutorial can be found in the various
Let’s start by cloning the sample application:
$ git clone https://github.com/vespa-engine/sample-apps.git $ cd sample-apps/news
getting-started directory contains a minimal Vespa application. There
are three files there:
services.xml- defines the services the application consists of
hosts.xml- defines which hosts or nodes the application will run on
schemas/news.sd- defines the schema for searchable content.
We will get back to these files in the next part of the tutorial.
This application doesn’t contain much at the moment, but let’s start up the application anyway by starting a Docker container to run it:
$ docker pull vespaengine/vespa $ docker run -m 10G --detach --name vespa --hostname vespa-tutorial \ --volume `pwd`:/app --publish 8080:8080 vespaengine/vespa
First, we pull the latest Vespa image from the Docker repository, then we
start it with the name
vespa. This starts the Docker container and the
initial Vespa services to be able to deploy an application.
Starting the container can take a short while. Before continuing, make sure
that the configuration service is running. This is signified by a
response when querying the configuration service, running on port 19071:
$ docker exec vespa bash -c 'curl -s --head http://localhost:19071/ApplicationStatus'
docker exec vespa bash -c '...' runs the command inside the Docker
container, so we don’t have to expose the configuration server out from the
container. With the config server up and running, we can deploy our application:
$ docker exec vespa bash -c '/opt/vespa/bin/vespa-deploy prepare /app/app-1-getting-started && \ /opt/vespa/bin/vespa-deploy activate'
This runs the
vespa-deploy command inside the Docker container, as before.
vespa-deploy prepare command uploads the application and verifies the
content. If anything is wrong with the application, this step will fail with
a failure description. If everything is OK, the application can be activated by
vespa-deploy activate, which switches the application to a live status.
Whenever you have a new version of your application, you perform the same
vespa-deploy prepare and
vespa-deploy activate. In most cases,
there is no need to restart the application. Vespa takes care of
reconfiguring the system. If a restart is required in some rare case,
vespa-deploy prepare will notify you.
In the upcoming parts of the tutorials, we’ll frequently deploy the application in this manner.
Note here that we prepare the application directory. Both application directories and a zip file containing the application are accepted. A zip file is created when compiling and packaging an application containing custom Java code. We'll get back to that in part 6 of the tutorial.
The first time you deploy your application, it might take a while to start the services. Like the configuration server, you can query the status:
$ curl -s --head http://localhost:8080/ApplicationStatus
This returns a
200 OK when it is ready for receiving traffic. Note here
that we don’t run the command inside the Docker container. The port
was exposed when starting the Docker container, so we can query it directly.
Feeding to Vespa
We must index data before we can search for it. This is called ‘feeding’, and
we’ll get back to that in more detail in the next part of the tutorial. For
now, to test that everything is up and running, we’ll feed in a single test
document. We’ll use the
vespa-http-client Java feeder for this:
$ docker exec vespa bash -c 'java -jar /opt/vespa/lib/jars/vespa-http-client-jar-with-dependencies.jar \ --verbose --file /app/doc.json --host localhost --port 8080'
This runs the
vespa-http-client Java client with the file
This contains a single document which we’ll query for below.
In later tutorials, when more data should be fed to the system,
use this command while pointing to the correct feed file.
vespa-http-client can also be obtained using:
$ curl -O https://repo.maven.apache.org/maven2/com/yahoo/vespa/vespa-http-client/7.369.27/vespa-http-client-7.369.27-jar-with-dependencies.jar
If everything is ok so far, our application should be up and running. We can query the endpoint:
$ curl -s "http://localhost:8080/search/?yql=select+*+from+sources+*+where+sddocname+contains+%22news%22;"
This uses the
search API to search for all documents of type
This should return
1 result, which is the document we fed above.
Stopping and starting Vespa
To stop Vespa, we can run the following commands:
$ docker exec vespa bash -c '/opt/vespa/bin/vespa-stop-services' $ docker exec vespa bash -c '/opt/vespa/bin/vespa-stop-configserver'
Likewise, to start the Vespa services:
$ docker exec vespa bash -c '/opt/vespa/bin/vespa-start-configserver' $ docker exec vespa bash -c '/opt/vespa/bin/vespa-start-services'
If a restart is required due to changes in the application package, these two steps are what you need to do.
To wipe the index and restart:
$ docker exec vespa bash -c ' \ /opt/vespa/bin/vespa-stop-services && \ /opt/vespa/bin/vespa-remove-index -force && \ /opt/vespa/bin/vespa-start-services'
You can stop and kill the Vespa Docker application like this:
$ docker rm -f vespa
This will delete the Vespa application, including all data, so don’t do this unless you are sure.
Our very simple application should now be up and running. In the next part of the tutorial, we’ll start building from this foundation.