docker-livy

Check the article here: Building Real-time communication with Apache Spark through Apache Livy

Dockerizing and Consuming an Apache Livy environment

As you can see, In order to reproduce a real example we would need three components:

• Apache Spark Cluster
• Apache Livy Server
• Apache Livy Client

As an additional component I would add docker for a faster implementation, and a PostgreSQL database server to simulate an external data source available for Apache Spark.

In order to reproduce the experiment we would need to follow the next steps:

• Install Docker Desktop on Windows, it will install Docker Compose as well, Docker Compose will allow you to run multiple container applications.
• Install git-bash for windows, once installed, open git bash and download this repository, this will download the docker-compose.yaml file, and other files needed.

ramse@DESKTOP-K6K6E5A MINGW64 /c
$ git clone https://github.com/Wittline/docker-livy.git

• Once all the files needed were downloaded from the repository, let’s run everything. We will use the git bash tool again, go to the folder docker-livy and we will run the Docker Compose command:

ramse@DESKTOP-K6K6E5A MINGW64 /c
$ cd docker-livy

ramse@DESKTOP-K6K6E5A MINGW64 /c/docker-livy
$ cd code

ramse@DESKTOP-K6K6E5A MINGW64 /c/docker-livy/code
$ cd apps

@DESKTOP-K6K6E5A MINGW64 /c/docker-livy/code/apps
$ docker-compose up -d --build

• Wait for a minutes, and when the execution of the last command is finished, use the following command to check the status of all the containers.

docker ps

• If everything is up and running then we are going to move forward with other steps to interact with the Apache Livy interface using livyc
• Setiting a local environment with Google Colab
• Go to git-bash and put the next command:

ramse@DESKTOP-K6K6E5A MINGW64 ~
jupyter notebook --NotebookApp.allow_origin='https://colab.research.google.com' --port=8888 --NotebookApp.port_retries=0

• After the execution of the last command, copy the localhost URL, you will need it for colab
• Go to Google Colab
• Create a new Notebook
• Go to -> Connect -> “Connect to local runtime” -> Paste the url copied from the last step and put it in Backend URL -> connect
• Upload the file test-livy.ipynb, and use it into your colab local env:
• Run each cell and see the results on each steps.

Note that among the actions taken in the test-livy.ipynb file, the postgres database is being populated with data using an external .csv file, this in order for apache spark to have data to interact with.

• If you want to monitorize all the session created in Apache Livy Server go to the address: http://localhost:8998/ui

The Python Package livyc works well to submit pyspark scripts dynamically and asynchronously to the Apache Livy server, this in turn interacts with the Apache Spark Cluster in a transparent way, check this project and remember to check all the files before interacting with the jupyter notebook file.

Contributing and Feedback

Any ideas or feedback about this repository?. Help me to improve it.

Authors

• Created by Ramses Alexander Coraspe Valdez
• Created on 2022

License

This project is licensed under the terms of the MIT License.