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Stream Processing Use Cases with ksqlDB [DEPRECATED]

This repository contains the source for the collection of Stream Processing Use Cases with ksqlDB.

https://developer.confluent.io/tutorials/use-cases.html

Source moved to https://github.com/confluentinc/kafka-tutorials

Goals of the project:

  • Provide short, concrete descriptions of how ksqlDB is used in the real world—including SQL code.
  • Make it easy to replicate that code end-to-end, with a 1-click experience to populate the code into the ksqlDB editor in Confluent Cloud Console.

How to contribute

We welcome all contributions, thank you!

Contributing an idea? Submit a GitHub issue.

Contributing a full recipe to be published?

  1. Self-assign a recipe idea from the list in GitHub issues.
  2. Create a new branch (based off main) for the new recipe
  3. Create a new subfolder for the new recipe, e.g. docs/<industry>/<new-recipe-name>. Note: <new-recipe-name> is the slug in Confluent Cloud. Use hyphens, not underscores.
  4. The recipe should follow the structure of existing recipes. Copy the contents of an existing recipe (e.g. aviation) or the template directory as the basis for your new recipe.
  • index.md: explain the use case, why it matters, add a graphic if available
  • source.json: JSON configuration to create Confluent Cloud source connectors to pull from a real end system
  • source.sql: SQL-equivalent of source.json (this file is not referenced today in index.md, but getting ready for ksqlDB-connect integration)
  • manual.sql: SQL commands to insert mock data into Kafka topics, if a user does not have a real end system
  • process.sql: this is the core code of the recipe, the SQL commands that correspond to the event stream processing
  • sink.json: (optional) JSON configuration to create Confluent Cloud sink connectors to push results to a real end system
  • sink.sql: (optional unless sink.json is provided) SQL-equivalent of sink.json (this file is not referenced today in index.md, but getting ready for ksqlDB-connect integration)
  1. Validation: you do not need to create a real end system, real data, and a real source connector, but you should ensure the connector configuration is syntactically correct. Do validate that the core ksqlDB stream processing code works with the manual INSERT INTO statements, and that the last ksqlDB query returns the expected records.

  2. Submit a GitHub Pull Request. Ensure the new recipe adheres to the checklist and then tag confluentinc/devx for review.

Handling connectors

A recipe is more compelling if it uses Confluent Cloud fully-managed connectors, especially when the ksqlDB-connect integration is ready. But what if the recipe you want to write does not have a connector available in Confluent Cloud? Some options for your to consider, in order of preference:

  1. Stick with the original recipe idea, but use another connector in Confluent Cloud, that still fits the use case
  2. Pick a different recipe, maybe in the same industry, that uses a connector available in Confluent Cloud. This maximizes the impact of your recipe contribution
  3. Stick with your original recipe idea, and use a self-managed connector that runs locally. Follow precedent steps in this recipe

Build recipes docs locally

To view your new recipes locally, you can build a local version of the recipes site with mkdocs.

  • Install mkdocs (https://www.mkdocs.org/)

    On macOS, you can use Homebrew:

    brew install mkdocs
    pip3 install mkdocs pymdown-extensions
    pip3 install mkdocs-material
    pip3 install mkdocs-exclude
    pip3 install mkdocs-redirects
  • Build and serve a local version of the site. In this step, mkdocs will give you information if you have any errors in your new recipe file.

    python3 -m mkdocs serve  
    

    (If this doesn't work try mkdocs serve on its own)

  • Point a web browser to the local site at http://localhost:8000 and navigate to your new recipe.

Publishing recipes to live site

If you are a Confluent employee, you can publish using the mkdocs GitHub integration. From the main branch (in the desired state):

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