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Apache Kafka - Python Jupyter Notebooks

This is a series of Jupyter Notebooks on how to start with Apache Kafka and Python. You can try these notebooks in order to learn the basic concepts of Kafka in an environment containing markdown text, media and executable code on the same page.

The notebooks are based on a managed Apache Kafka instance created on Aiven's website, but can be also customised to any Kafka instance running locally with SSL authentication. Aiven's offer 300$ of free credit that you can redeem by creating your account on Aiven's website.

If you have any question or improvement suggestion regarding the notebooks, please open an issue. Any contributions are welcome!

Start JupyterLab on Docker

You can access the notebooks via Jupyterlab, this example will be based on docker

  1. clone the repository
  2. open a terminal
  3. go to the folder where the repository has been cloned
  4. run the following
docker run --rm -p 8888:8888 \
  -e JUPYTER_ENABLE_LAB=yes  \
  -v "$PWD":/home/jovyan/work \
  jupyter/datascience-notebook

You'll see a folder named work on the top left, under it you'll find the list of notebooks.

Notebook Overview

This repository contains the following notebooks.

Notebook Details

The notebooks are divided per Apache Kafka functionality.

Create Managed Apache Kafka and PostgreSQL instances with Aiven.io

Create services

00 - Aiven Setup.ipynb notebook downloads Aiven's command line interface and creates an Apache Kafka and a PostgreSQL instance.

Please change <INSERT_TOKEN_HERE> and <INSERT_EMAIL_HERE> with a valid email address and token created on Aiven's website. The notebook creates the instances and also stores all the required connection credentials locally.

Produce and read Messages to Apache Kafka

Producer

01 - Producer.ipynb Creates a Python Kafka Producer and produces the first messages. After the first message is produced, open the 02 - Consumer.ipynb notebook and pace it alongside the Producer.

Place consumer alongside the producer

02 - Consumer.ipynb reads from the topic where 01 - Producer wrote. But it does it from the point in time that it attaches to Kafka, not going back to history.

Consumer

If you want to read messages created with 01 - Producer you need to run 02 - Consumer.ipynb's last code block before producing any messages on 01 - Producer. This behaviour is Kafka's default and can be changed by adding a line 'auto.offset.reset'='earliest' to the consumer properties.

Understanding Apache Kafka Partitions

Partitions

Partitions is Apache Kafka are a way to divide messages belonging to the same topic in sub-logs.

  • 03 - 00 - Partition Producer.ipynb creates a topic with two partitions using KafkaAdmin and sends a message to each partition. We can then open both 03 - 01 - Consumer - Partition 0.ipynb and 03 - 02 - Consumer - Partition 1.ipynb which will read messages from Partition 0 and Partition 1 respectively.

New Consumer Group

Consumer groups

Messages in Apache Kafka are not deleted when read from a consumer. This makes them available for other consumers to be read. 04 - New Consumer Group.ipynb creates a new consumer part of the a new Consumer Group and reads from the topic where 01 - Producer wrote. We can check now, by sending a message from the 01 - Producer notebook, that we can receive it both in 02 - Consumer.ipynb and 04 - New Consumer Group.

Kafka Connect

Kafka Connect

Kafka Connect is a prebuilt framework enabling an easy integration of Apache Kafka with existing data sources or sinks. Aiven provides Kafka connect as managed service making the integration a matter of a single config file. 05 - Kafka Connect.ipynb: Creates a new Kafka topic containing messages with both schema and payload, and then pushes them to a PostgreSQL database via Kafka Connect.

Delete Aiven Services

Delete services

Once you're done, you can delete all the services create on Aiven's website by executing the code in ON - Aiven - Delete Services.ipynb

Keep Reading

We maintain some other resources that you may also find useful:

License

This project is licensed under the Apache License, Version 2.0.

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