Getting started / Hello World

This guide will allow you to set up your first Apache Liminal environment and allow you to create some simple ML pipelines. These will be very similar to the ones you are going to build for real production scenarios.

Prerequisites

Python 3 (3.6 and up)

Docker Desktop

Note: Make sure kubernetes cluster is running in docker desktop (or custom kubernetes installation on your machine).

Deploying the Example

In this tutorial, we will go through setting up Liminal for the first time on your local machine.

First, let’s build our example project:

In the dev folder, just clone the example code from liminal:

git clone https://github.com/apache/incubator-liminal

Note: You just cloned the entire Liminal Project, you actually only need examples folder.

Create a python virtual environment to isolate your runs:

cd incubator-liminal/examples/liminal-getting-started
python3 -m venv env

Activate your virtual environment:

source env/bin/activate

Now we are ready to install liminal:

pip install apache-liminal

Let's build the images you need for the example:

liminal build

The build will create docker images based on the liminal.yml file in the images section.

Create a kubernetes local volume:

liminal create

liminal deploy --clean

The deploy command deploys a liminal server and deploys any liminal.yml files in your working directory or any of its subdirectories to your liminal home directory.

Note: liminal home directory is located in the path defined in LIMINAL_HOME env variable. If the LIMINAL_HOME environemnet variable is not defined, home directory defaults to ~/liminal_home directory.

Now lets runs liminal:

liminal start

The start command spins up the liminal server containers which will run pipelines based on your deployed liminal.yml files. It runs the following three containers:

• liminal-postgress
• liminal-webserver
• liminal-scheduler

Once liminal server has completed starting up, you can navigate to admin UI in your browser: http://localhost:8080 By default liminal server starts Apache Airflow servers and admin UI will be that of Apache Airflow.

Important: Set off/on toggle to activate your pipeline (DAG), nothing will happen otherwise!

You can go to graph view to see all the tasks configured in the liminal.yml file: http://localhost:8080/admin/airflow/graph?dag_id=example_pipeline

Now lets see what actually happened to our task:

Click on “hello_world_example” and you will get this popup:

Click on “view log” button and you can see the log of the current task run:

Mounted volumes

All tasks use a mounted volume as defined in the pipeline YAML:

name: GettingStartedPipeline
volumes:
  - volume: gettingstartedvol
    claim_name: gettingstartedvol-pvc
    local:
      path: .

In our case the mounted volume will point to the liminal hello world example.
The hello world task will read the hello_world.json file from the mounted volume and will write the hello_world_output.json to it.

Note: Each task will internally mount the volume defined above to an internal representation, described under the task section in the yml:

  task:
  ...
  mounts:
     - mount: taskmount
       volume: gettingstartedvol
       path: /mnt/vol1

Here are the entire list of commands, if you want to start from scratch:

git clone https://github.com/apache/incubator-liminal
cd examples/liminal-getting-started
python3 -m venv env
source env/bin/activate
pip uninstall apache-liminal
pip install apache-liminal
Liminal build
Liminal create
liminal deploy --clean
liminal start

Closing up

To make sure liminal containers are stopped use:

liminal stop

To deactivate the python virtual env use:

deactivate