11 个仓库
Execution of high-volume data tasks using concurrent threads to increase throughput.
Distinct from High-Performance Collection Processing: Closest candidates focus on packet processing or database queries; this is a general architectural pattern for high-volume data collection.
Explore 11 awesome GitHub repositories matching software engineering & architecture · Multi-Threaded Batch Processing. Refine with filters or upvote what's useful.
Pentaho Kettle 是一个企业级 ETL 数据集成平台,旨在在不同源和目标数据库之间提取、转换和加载数据。它充当元数据驱动的编排器,利用可视化工作流设计器来创建和管理复杂的数据任务序列和转换管道。 该系统的特点是其分布式数据处理引擎,可在服务器节点集群上执行工作负载以提高吞吐量。它采用基于插件的架构,允许通过外部 JAR 文件扩展平台,以提供与各种数据库和云服务的连接。 该平台涵盖了广泛的数据集成功能,包括批量加载、远程文件管理和数据结构转换。它提供用于数据质量验证、管道自动化和作业生命周期管理的工具,以及用于跟踪服务器健康状况和实时执行状态的监控实用程序。
Implements high-volume data processing by executing discrete pipeline steps in separate concurrent threads to maximize throughput.
ClamAV 是一个开源杀毒引擎和恶意软件检测扫描器。它通过将文件和数据流与已知签名数据库进行扫描,来识别木马、病毒和其他恶意软件。 该系统作为基于签名的威胁检测器运行,允许通过将恶意软件样本转化为可操作的签名来实现威胁情报。它支持创建自定义恶意软件签名以识别特定或专门的安全威胁。 该引擎提供端点安全监控和跨计算机系统的全面恶意软件检测扫描功能。
Parallelizes the scanning of files and data streams across multiple CPU cores to increase throughput.
This project is a proxy aggregation platform designed to collect and verify free proxy server lists from web platforms, social media, and public repositories. It functions as a crawler framework that gathers proxy data and subscription links, a validation tool for testing server liveness, and a synchronization service for distributing the results. The system uses a plugin-based architecture that allows for the integration of custom Python scripts to handle diverse web source structures. It also includes utilities to transform raw proxy data into standardized configuration formats compatible w
Utilizes multi-threaded execution to increase the throughput of high-volume proxy data collection and connectivity probes.
Cppcheck 是一个用于 C 和 C++ 源代码的静态分析工具和检查器,旨在在不执行程序的情况下检测编程错误、内存泄漏和安全违规。它作为一个错误检测引擎和质量保证工具,用于识别并发问题、类型转换错误以及对安全编码标准的合规性。 该项目提供了一个用于选择文件和审查错误的图形用户界面,以及一个用于强制执行命名约定和编码标准的检查器。它支持使用正则表达式创建自定义分析规则,以识别特定的编码模式。 该工具包括增量分析、警告抑制和文件排除功能,以管理大型代码库。它还具有 HTML 报告生成功能,并与 VS Code 等编辑器集成,以便在开发过程中提供错误识别。
Distributes independent analysis tasks across multiple CPU cores to increase processing throughput.
Caesium is an image compression tool that reduces file sizes for JPG, PNG, WebP, and TIFF images while preserving visual quality and metadata. It operates as a cross-platform desktop application with a graphical interface, a command-line tool for scripting and automation, and a web-based interface for browser uploads, all supporting batch processing of multiple images at once. The tool distinguishes itself by offering multiple interaction modes — desktop, terminal, and web — each capable of handling the same core compression tasks. It preserves folder structure when saving compressed images,
Distributes compression tasks across multiple CPU threads to process several images simultaneously without blocking the user interface.
Grobid 是一个机器学习系统,旨在将学术和科学 PDF 出版物转换为结构化的 XML。它作为一个 PDF 转 XML 解析器和学术元数据提取器,从研究论文中识别并规范化标题、作者、所属机构和参考文献。 该系统利用深度学习文档分割器将原始 PDF 分割为功能区域,并采用参考文献解析器将引文与外部注册表进行匹配,以进行元数据丰富和 DOI 解析。它支持完整的机器学习模型训练流水线,允许生成标注训练语料库、模型再训练以及导出模型二进制文件。 该项目涵盖了广泛的提取功能,包括文档标题解析、全文正文结构化,以及资助信息和专利引文等领域特定实体的识别。它还提供用于边界框提取和坐标映射的空间分析工具,以将语义标签与原始 PDF 布局同步。 该应用程序可通过容器化镜像部署,并包含用于大型文档集合多线程批处理的命令行工具。
Implements multi-threaded batch processing to maximize hardware throughput when parsing large document collections.
Crawler4j 是一个多线程 Java 网络爬虫,专为高容量 Web 遍历和内容提取而设计。它作为一个“礼貌”的爬取框架,能够发现并索引多个网站上的 HTML 和二进制内容。 该项目通过一种持久化爬取模型脱颖而出,该模型将会话状态序列化到本地存储,允许引擎在崩溃或中断后恢复索引。它包含一个礼貌控制器来调节请求频率和延迟,防止服务器过载和 IP 被封。 该系统涵盖了广泛的遍历功能,包括深度限制范围管理、目标过滤,以及针对自定义用户代理和代理路由的请求拦截。数据存储通过存储库模式处理,将爬取逻辑与关系数据库中页面元数据的持久化解耦。
Ships a multi-threaded engine for high-throughput web traversal and content extraction.
SDRangel is a comprehensive software-defined radio suite and digital signal processing framework. It functions as an RF spectrum analyzer and modular radio demodulator, providing a unified hardware abstraction layer to connect various radio devices to software processing pipelines for data acquisition and transmission. The platform is distinguished by its modular architecture, which uses a data-flow graph of dynamic libraries to construct signal processing chains. This allows for a plugin-based environment where users can extract audio and digital data from raw radio signals using various mod
Implements a multi-threaded sample pipeline with shared memory buffers to minimize signal latency.
VidGear is a high-performance Python video processing framework designed for capturing, transcoding, and manipulating video streams. It functions as a multi-protocol video streamer and a WebRTC streaming server, enabling the transfer of video frames over networks using RTSP, RTMP, RTP, and MJPEG protocols. The project distinguishes itself through hardware-accelerated video transcoding and decoding using GPU backends like CUDA to reduce CPU load. It includes a cross-platform screen capture tool and a specialized system for establishing direct peer-to-peer media connections using WebRTC signali
Reads frames from IP cameras, network streams, and hardware decoders using multi-threaded processing.
This library is a Java-based tool for enforcing data structure constraints and verifying technical formats against defined schema specifications. It functions as a processing utility that parses complex data structures while managing external schema references and circular dependencies. The engine distinguishes itself through an immutable processor design that enables thread-safe, concurrent validation without requiring external synchronization. It employs arbitrary-precision arithmetic to evaluate numeric constraints, preventing common floating-point rounding errors, and utilizes character-l
Executes thread-safe validation tasks concurrently to maintain high performance during heavy data processing.
This project is a procedural content generation framework and three-dimensional mesh generation library designed for the Unity game engine. It provides a system for automating the creation of complex landscapes and natural environments by programmatically constructing geometric terrain surfaces and heightmaps. The generator utilizes layered noise functions to calculate elevation values, which are then translated into terrain geometry. To maintain performance during real-time rendering, the system employs chunk-based mesh generation and dynamic level-of-detail management, which adjusts geometr
Offloads heavy mathematical calculations and mesh construction to background threads to maintain high frame rates during terrain generation.