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2 dépôts

Awesome GitHub RepositoriesStateful Processing Patterns

Architectural patterns for maintaining state across distributed task executions.

Distinguishing note: Focuses on stateful execution patterns rather than stateless functional transformations.

Explore 2 awesome GitHub repositories matching software engineering & architecture · Stateful Processing Patterns. Refine with filters or upvote what's useful.

Awesome Stateful Processing Patterns GitHub Repositories

Trouvez les meilleurs dépôts grâce à l'IA.Nous recherchons les dépôts les plus pertinents grâce à l'IA.
  • ray-project/rayAvatar de ray-project

    ray-project/ray

    42,895Voir sur GitHub↗

    Ray is a distributed computing framework designed to scale Python and Java applications across clusters by abstracting task scheduling and resource management. It functions as a resource-aware execution engine that manages task dependencies, placement, and fault tolerance across networked compute nodes. At its core, the system provides a stateful actor model, allowing developers to define classes that run in dedicated processes to maintain and mutate internal state across remote method calls. The framework distinguishes itself through a robust cross-language interoperability layer, enabling f

    Implements stateful transformations using classes to perform expensive setup operations exactly once per worker.

    Pythondata-sciencedeep-learningdeployment
    Voir sur GitHub↗42,895
  • apache/beamAvatar de apache

    apache/beam

    8,612Voir sur GitHub↗

    Apache Beam is a distributed data pipeline framework and unified data processing model designed to handle both bounded batch data and unbounded real-time streams. It provides a system for building scalable, data-parallel workflows that operate across compute clusters using a single programming model. The framework utilizes a cross-runner pipeline abstraction that decouples the data processing logic from the underlying execution backend, allowing the same pipeline to run on different distributed compute engines. It supports multi-language pipeline development by translating high-level code fro

    Maintains per-key state and timers across processing stages to enable complex aggregations and sessionization.

    Java
    Voir sur GitHub↗8,612
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