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  • Apache Flink® — Stateful Computations over Data Streams
    Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale
  • Apache Flink - Wikipedia
    Apache Flink's dataflow programming model provides event-at-a-time processing on both finite and infinite datasets At a basic level, Flink programs consist of streams and transformations
  • What is Apache Flink? - Apache Flink Explained - AWS
    Flink is a high throughput, low latency stream processing engine A Flink application consists of an arbitrary complex acyclic dataflow graph, composed of streams and transformations Data is ingested from one or more data sources and sent to one or more destinations
  • What Is Apache Flink®? Architecture Use Cases | Confluent
    Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams Flink has been designed to run in all common cluster environments and perform computations at in-memory speed, at any scale
  • Apache Flink 2. 0. 0: A new Era of Real-Time Data Processing
    In the 2 0 release, Flink introduces several innovative features that address key challenges in real-time data processing and align with the growing demands of modern applications, including AI-driven workflows
  • Introduction to Apache Flink - GitHub Pages
    Apache Flink is a framework and distributed processing engine for stateful computations over unbounded and bounded data streams Flink has been designed to run in all common cluster environments, perform computations at in-memory speed and at any scale
  • Documentation - Apache Flink
    Apache Flink, Flink, and the Flink logo are either registered trademarks or trademarks of The Apache Software Foundation in the United States and other countries
  • Operations - Apache Flink
    Apache Flink puts a strong focus on the operational aspects of stream processing Here, we explain Flink’s failure recovery mechanism and present its features to manage and supervise running applications Machine and process failures are ubiquitous in distributed systems




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