Gain insights into data processing and concurrency in Elixir. Explore GenServer, GenStage, Flow, and Broadway to enhance performance, set up pipelines, and handle increased workloads efficiently.

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Most engineers don’t think that concurrency is distinct from programming. Data processing includes transforming information in some way, like reporting, data aggregation, or analytics. On the other hand, concurrency involves significantly improving performance.

This course is designed to help you navigate the world of concurrency tools available in the Elixir ecosystem. You’ll explore popular modules and libraries like GenServer, GenStage, Flow, and Broadway. You’ll be able to ingest data, set up pipelines, and run concurrent processes with Elixir.

By the end of the course, you’ll have a wide range of new techniques to simplify your product, improve code performance, and make your application more resilient to increased workloads.

Concurrent Data Processing in Elixir

# Group

Like `Enum.group_by/2`, `Flow.group_by/2` groups the data by the given criteria. They both are implemented using the `reduce` function behind the scenes. Therefore, we'll keep our `Flow.partition/2` function to continue routing events to the correct process. This ensures that the same process groups airports of the same country.

Let's replace `Flow.reduce/3` with `Flow.group_by/2`:

Learn to use the group_by() and take_sort() functions in the Flow module.


Group and Sort

Learn to use the group_by() and take_sort() functions in the Flow module.

Getting Started

Easy Concurrency with the Task Module

Long-Running Processes Using GenServer

Data Processing Pipelines with GenStage

Process Collections with Flow

Data Ingestion Pipelines with Broadway

Concluding the Course

Group and Sort

Group