A computational parallel flow library for Elixir built on top of GenStage for parallel processing of collections.
Flow is an Elixir library for parallel computation on collections, built on top of GenStage. It allows developers to process data in parallel across multiple stages, similar to working with Enum and Stream but with concurrent execution. It solves the problem of efficiently handling large datasets or computationally intensive operations by distributing work across processes.
Elixir developers who need to process large collections or streams of data with improved performance through parallel execution. It's particularly useful for data processing pipelines, batch jobs, and real-time stream analysis.
Developers choose Flow because it provides a familiar Elixir API for parallel processing without requiring low-level concurrency management. Its integration with GenStage ensures efficient backpressure handling and scalability, making it a robust solution for high-throughput data processing tasks.
Computational parallel flows on top of GenStage
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Flow's interface mimics Enum and Stream, allowing developers to write parallel pipelines with minimal syntax changes, as shown in the word-count example.
Leverages GenStage to distribute work across multiple processes, enabling high-throughput processing for large datasets or streams without manual concurrency management.
Includes partitioning capabilities to optimize data flow between stages, essential for balancing load in distributed computations.
Offers options like link: false for process linking, useful in interactive environments like Livebook, as noted in the README.
Flow pipelines can inadvertently shut down the Livebook runtime due to process linking, requiring workarounds such as setting link: false or trapping exits, adding complexity for interactive use.
The GenStage infrastructure introduces overhead that makes Flow less efficient than serial Enum for trivial computations or small collections.
Relies on GenStage, which adds a learning curve and operational complexity, especially for developers new to Elixir's concurrency models.