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:
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. For atomic model updates, see the Models hot swap tutorial.
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.
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.
This tutorial has a companion sample application
found under the
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 --depth 1 https://github.com/vespa-engine/sample-apps.git $ cd sample-apps/news
app-1-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 \ --publish 8080:8080 --publish 19071:19071 \ 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:
$ curl -s --head http://localhost:19071/ApplicationStatus
With the config server up and running, deploy the application:
$ (cd app-1-getting-started && zip -r - .) | \ curl --header Content-Type:application/zip --data-binary @- \ localhost:19071/application/v2/tenant/default/prepareandactivate
The command uploads the application and verifies the content. If anything is wrong with the application, this step will fail with a failure description, otherwise this switches the application to a live status.
Whenever you have a new version of your application, run the same command to deploy the application. 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, however, the output 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.
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:
$ curl -L -o vespa-http-client-jar-with-dependencies.jar \ https://search.maven.org/classic/remotecontent?filepath=com/yahoo/vespa/vespa-http-client/7.391.28/vespa-http-client-7.391.28-jar-with-dependencies.jar
$ java -jar vespa-http-client-jar-with-dependencies.jar \ --verbose --file doc.json --endpoint http://localhost:8080
This runs the
vespa-http-client Java client with the file
This contains a single document which we’ll query for below.
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.
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.