3 个仓库
Calculations of statistical aggregates such as sums, averages, and extremas across asynchronous data sequences.
Distinct from Numeric Aggregations: Candidates focus on database-level sums or GPU acceleration; this is about functional aggregation of a non-blocking stream.
Explore 3 awesome GitHub repositories matching data & databases · Stream Mathematical Aggregations. Refine with filters or upvote what's useful.
Reactor Core is a reactive programming toolkit and non-blocking foundation for composing asynchronous data pipelines on the JVM. It serves as an asynchronous stream processing framework and a backpressure management system, allowing developers to transform, filter, and combine sequences of events while regulating data flow between producers and consumers to prevent resource exhaustion. The library differentiates itself through a sophisticated concurrency scheduling system and demand-based flow control. It decouples signal processing from specific threads using a scheduler registry and provide
Calculates sums, averages, minimums, and maximums across streams of numeric data.
RxGo 是一个函数式响应式编程库,也是 ReactiveX 的 Go 语言实现。它作为一个异步流处理工具包,旨在利用可观察模式协调基于事件的程序和数据流。 该库支持构建异步处理管道,以转换、过滤和组合事件序列。其特色在于使用函数式操作符来组合这些管道,并提供了管理并发执行的机制。 该工具包涵盖了广泛的流编排功能,包括数据聚合、多流组合以及将流转换为静态数据结构。它内置了对错误恢复、用于调节数据生产速度的背压控制以及用于跨 CPU 核心并行处理的工作池的支持。
Calculates statistical aggregates such as sums, averages, and counts across asynchronous data sequences.
RxPY 是一个 Python 函数式响应式编程库,也是 ReactiveX 的可观察对象库。它作为一个异步流处理器和事件驱动的协调框架,用于构建能够对状态变化或随时间变化的事件流做出反应的数据流水线。 该库提供了一套工具,用于使用可观察序列和操作符来编写异步和基于事件的程序。它通过使用可配置的调度器来管理并发、时序和订阅生命周期,从而脱颖而出。 该项目涵盖了广泛的流处理能力,包括数据聚合、过滤和组合。它提供了事件广播、序列缓冲和错误处理机制,以及用于协调可观察流与异步事件循环的工具。 通过虚拟时间模拟、大理石图建模和发射验证,该库提供了完善的测试和质量保证支持。
Computes statistical aggregates such as sums, averages, and counts across asynchronous data sequences.