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Examples using faust and kafka for stream processing with InfluxDB and Telegraf

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kafka_faust_examples

Examples using faust and kafka for stream processing with InfluxDB and Telegraf

Local Development

This repository uses Pipenv for package managment & isolation.

Python version management using asdf is supported via /.tool-versions.

All examples require Kafka, container config is provided in /docker-compose.yaml.

Examples

Use the scratchpad.md for commands to execute the following exmaples.

hello_world

The "Hello World" example demonstrates the basics of a Faust streaming application. It sets up a simple Faust app that reads events from a Kafka topic and prints each event to the console. This example serves as an introduction to Faust’s structure, helping you understand how to create, configure, and run a Faust application with minimal setup.

page_views

The "Page Views" example showcases real-time counting of page views using Faust. It reads page view events from a Kafka topic, aggregates the number of views per page, and stores these counts in an in-memory table. For each page view, the updated count is published to another topic, allowing consumers to access up-to-date view counts for each page in real time. This example highlights Faust’s ability to handle stateful stream processing and perform real-time aggregations. telegraf.conf is configured to consume the JSON messages and write them to InfluxDB.

Notes

  • Pypi package faust-streaming is a fork of the deprecated faust

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Examples using faust and kafka for stream processing with InfluxDB and Telegraf

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