angel
6,797
Stars
1,588
Forks
435
Watchers
142
Open Issues
NOASSERTION
许可证
Java
语言
2017-04-25
创建时间
2026-11-11
最近更新
项目能做什么
面向大规模机器学习的高性能、灵活的参数服务器(Parameter Server)。
来源:基于仓库元数据
· 内容以仓库实际 README 为准
使用说明 查看原始 README 原仓库文档
中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
 [](https://github.com/Angel-ML/angel/blob/branch-3.2.0/LICENSE.TXT) [](https://github.com/tencent/angel/releases) [](https://github.com/tencent/angel/pulls) [](https://github.com/Angel-ML/angel/archive/refs/heads/branch-3.2.0.zip) [(ZH-CN Version)](./README_CN.md) **Angel** is a high-performance distributed machine learning and graph computing platform based on the philosophy of Parameter Server. It is tuned for performance with big data from Tencent and has a wide range of applicability and stability, demonstrating increasing advantage in handling higher dimension model. Angel is jointly developed by Tencent and Peking University, taking account of both high availability in industry and innovation in academia. With model-centered core design concept, **Angel** partitions parameters of complex models into multiple parameter-server nodes, and implements a variety of machine learning algorithms and graph algorithms using efficient model-updating interfaces and functions, as well as flexible consistency model for synchronization. **Angel** is developed with **Java** and **Scala**. It supports running on **Yarn**. With **PS Service** abstraction, it supports **Spark on Angel**. Graph computing and deep learning frameworks support is under development and will be released in the future. We welcome everyone interested in machine learning or graph computing to contribute code, create issues or pull requests. Please refer to [Angel Contribution Guide](https://github.com/Tencent/angel/blob/master/CONTRIBUTING.md) for more detail. ## Introduction to Angel * [Architecture](./docs/overview/architecture_en.md) * [Code Framework](./docs/overview/code_framework_en.md) * [Design](./docs/overview/design_philosophy_en.md) * [Spark on Angel](./docs/overview/spark_on_angel_en.md) * [Machine Learning](./docs/overview/spark_on_angel_en.md) * [Graph Computing](./docs/overview/angel_graph_sona_en.md) ## Design - [Model Partitioner](./docs/design/model_partitioner_en.md) - [SyncController](./docs/design/sync_controller_en.md) - [psFunc](./docs/design/psfFunc_en.md) - [Core API](./docs/apis/core_api_en.md) ## Quick Start * [Quick Start Example](./docs/tutorials/spark_on_angel_quick_start_en.md) ## Deployment * [Compilation Guide](./docs/deploy/source_compile_en.md) * [Running on Local](./docs/deploy/local_run_en.md) * [Running on Yarn](./docs/deploy/run_on_yarn_en.md) * [Configuration Details](./docs/deploy/config_details_en.md) * [Resource Configuration Guide](./docs/deploy/resource_config_guide_en.md) ## Programming Guide * [Spark on Angel Programming Guide](./docs/programmers_guide/spark_on_angel_programing_guide_en.md) ## Algo阅读完整原文
商业机会分析 规则生成(AI 未配置)
综合评分 55.4 分。该项目在“个人可实施性”维度得 37 分,“付费可能性”维度得 20.0 分,差异化空间 100.0 分(评分依据见评分卡)。
面向细分需求的二次开发产品
| 产品构想 | 基于 angel 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。 |
| 目标用户 | 该细分场景用户 |
| 难度/周期 | 中 · 2~6 周 |
| 收费模式 | 买断制 / 订阅制 / 广告 |
| 竞争风险 | 细分需求规模需验证 |
| 依据 | AI 推测:基于项目主题标签的判断 |
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心
竞品与相似项目 GitHub Search 真实检索
| 项目 | 中文简介 | Stars | 语言 |
|---|---|---|---|
| alibaba/x-deeplearning | 中文介绍暂未生成 An industrial deep learning framework for high-dimension spa |
4,302 | PureBasic |
| marcj/css-element-queries | 中文介绍暂未生成 CSS Element-Queries aka Container Queries. High-speed elemen |
4,240 | JavaScript |
| NVIDIA/MinkowskiEngine | 中文介绍暂未生成 Minkowski Engine is an auto-diff neural network library for |
2,975 | Python |
| facebookresearch/hiplot | 中文介绍暂未生成 HiPlot makes understanding high dimensional data easy |
2,795 | TypeScript |
| ContextLab/hypertools | 中文介绍暂未生成 A Python toolbox for gaining geometric insights into high-di |
1,893 | Python |
| tancik/fourier-feature-networks | 中文介绍暂未生成 Fourier Features Let Networks Learn High Frequency Functions |
1,377 | Jupyter Notebook |
以上为通过 GitHub 官方 Search API 检索的相似项目,功能差异与优劣势需进一步人工确认,配置 AI 后可生成对比分析。
项目优势与风险
| 技术成熟度 | 创建于 2017-04-25,近 30 天仍在推送,发布过 20 个 Release |
| 社区活跃 | Star 6,797 / Fork 1,588 / Issue 142(数据支持,可自行核实) |
| 许可证 | NOASSERTION |
| 主要风险 | 上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价 |
安装与使用
快速开始(以仓库 README 为准)
git clone https://github.com/Angel-ML/angel.git cd angel # 请阅读仓库 README 获取确切安装步骤(依赖、配置、启动命令)
术语说明:Docker=应用容器(把程序和依赖打包运行);API Key=调用外部服务的密钥;Git Clone=把仓库代码下载到本地。常见错误:API Key 未配置 / 端口占用 / 数据库连接失败,多数项目在 README 的 Troubleshooting 章节有说明。