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8 个仓库

Awesome GitHub RepositoriesStream Element Grouping

Partitioning of stream elements into groups based on key-extraction functions.

Distinct from Log Stream Grouping: Distinct from log-specific grouping [f5_mt1] or consumer groups [f5_mt2], as it is a general functional streaming operator.

Explore 8 awesome GitHub repositories matching software engineering & architecture · Stream Element Grouping. Refine with filters or upvote what's useful.

Awesome Stream Element Grouping GitHub Repositories

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  • nathanmarz/stormnathanmarz 的头像

    nathanmarz/storm

    8,772在 GitHub 上查看↗

    Storm is a distributed stream processing framework and fault-tolerant compute engine designed for executing real-time continuous computations across a cluster of machines. It functions as a stateful stream processor and cluster topology manager, enabling the deployment and monitoring of distributed data flow configurations. The system ensures exactly-once semantics by utilizing transactional state management to guarantee that every message in a data stream is processed exactly one time. It further operates as a distributed RPC system, allowing for the integration of non-native languages throu

    Routes data packets to downstream tasks using customizable key-extraction and grouping logic.

    Java
    在 GitHub 上查看↗8,772
  • vandadnp/flutter-tips-and-tricksvandadnp 的头像

    vandadnp/flutter-tips-and-tricks

    6,822在 GitHub 上查看↗

    This repository is a collection of practical code snippets and implementation patterns for Flutter and Dart. It serves as a comprehensive guide and reference for asynchronous programming, state management patterns, and UI component design. The project provides advanced language reference material covering generics, reflection, factory constructors, and null-aware operators. It also includes specific utilities for manipulating Dart collections, such as helper methods for transforming and filtering maps, lists, and iterables. The coverage extends to high-level capabilities including asynchrono

    Implements logic to partition iterable elements into groups using a key extraction function.

    Dartdartflutterflutter-ui
    在 GitHub 上查看↗6,822
  • baconjs/bacon.jsbaconjs 的头像

    baconjs/bacon.js

    6,458在 GitHub 上查看↗

    Bacon.js is a JavaScript functional reactive programming library used for coordinating complex asynchronous data flows. It functions as an observable event stream framework and an asynchronous data flow orchestrator, allowing developers to model events as declarative streams and properties. The library distinguishes itself through its ability to manage reactive state and synchronize timing across multiple sources. It provides specialized mechanisms for atomic state synchronization to prevent glitches in derived properties and offers advanced coordination strategies such as asynchronous stream

    Splits a single stream into multiple sub-streams based on a key-generating function.

    TypeScript
    在 GitHub 上查看↗6,458
  • reactor/reactor-corereactor 的头像

    reactor/reactor-core

    5,224在 GitHub 上查看↗

    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

    Splits a data stream into multiple sub-streams by partitioning elements that share a common key.

    Javaasynchronousflowflux
    在 GitHub 上查看↗5,224
  • zio/ziozio 的头像

    zio/zio

    4,347在 GitHub 上查看↗

    ZIO is a functional effect system for the JVM that models asynchronous and concurrent programs as pure, composable values with typed error handling and dependency injection. Its core identity is built on fiber-based concurrency, where lightweight, non-blocking fibers execute millions of concurrent tasks with structured lifecycle management, and a dual-channel error model that separates expected business failures from unexpected system defects at compile time. The system provides effect-typed dependency injection through a layer-based dependency graph, pull-based reactive stream processing with

    Provides stream element grouping by key-extraction functions.

    Scalaasynchronicityasynchronousasynchronous-programming
    在 GitHub 上查看↗4,347
  • erikrose/more-itertoolserikrose 的头像

    erikrose/more-itertools

    4,074在 GitHub 上查看↗

    more-itertools 是一个 Python 可迭代对象工具库,提供用于操作、过滤和转换数据序列的高级函数。它作为一个数据流处理工具包和一组用于迭代器状态管理的工具,扩展了标准 Python itertools 模块的功能。 该库包括一个用于生成排列、组合和幂集的组合数学工具包,以及用于数论计算和矩阵运算的例程。它还提供了用于流状态管理的工具,允许用户查看即将到来的元素或在序列内搜索,以控制数据的消费方式。 附加功能涵盖了用于分块、交错和展平复杂序列的数据处理例程。该工具包还包括分析可迭代对象属性和同步并发数据流的函数。

    Partitions standard iterables into groups based on size or key functions to process large sequences in parts.

    Python
    在 GitHub 上查看↗4,074
  • more-itertools/more-itertoolsmore-itertools 的头像

    more-itertools/more-itertools

    4,074在 GitHub 上查看↗

    more-itertools 是 Python itertools 模块的扩展库。它作为一个用于操作可迭代对象的工具包,提供了广泛的数据转换、组合生成和迭代器状态管理例程。 该库以高级状态管理和复杂的序列生成为特色。它提供了查看未来元素、在序列内搜索,以及从可能包含重复元素的集合中生成唯一排列、组合和集合划分的功能。 其更广泛的功能涵盖了数据处理任务,如递归展平、分组、填充和数据流重塑。它还包括用于流合并、局部邻域分析的窗口化以及线程安全的迭代同步的工具。 该项目还提供了用于数值序列处理的专门例程,包括矩阵乘法、离散线性卷积和傅里叶变换。

    Provides a wide array of utilities to partition standard iterables into groups based on size or content.

    Python
    在 GitHub 上查看↗4,074
  • btroncone/learn-rxjsbtroncone 的头像

    btroncone/learn-rxjs

    3,671在 GitHub 上查看↗

    This project is a comprehensive learning resource and technical reference for reactive programming with RxJS. It provides a structured curriculum, curated examples, and an indexed operator catalog to help developers shift from imperative to declarative programming using observable data streams and functional operators. The repository features a library of reactive UI patterns and implementation recipes. These cover practical applications such as type-ahead search, game loops, gesture-based interactions like swipe-to-refresh, and security overlays like lockscreens. The resource covers a broad

    Implements capabilities to split a single stream into multiple observables based on shared keys or partitioning criteria.

    TypeScriptjavascriptlearning-rxjsobservables
    在 GitHub 上查看↗3,671
  1. Home
  2. Software Engineering & Architecture
  3. Stream Element Grouping

探索子标签

  • Iterable GroupingPartitioning of standard iterables into groups based on a key function. **Distinct from Stream Element Grouping:** Applies to general iterables in memory, whereas Stream Element Grouping is specifically for reactive streams.
  • Iterable SplittingDividing a collection into multiple parts based on delimiters or predicates. **Distinct from Iterable Grouping:** Splitting focuses on dividing a sequence into distinct parts, whereas grouping partitions elements into sets.