登录

bacalhau

bacalhau-projectApache-2.0活跃维护

把计算任务调度到数据所在节点上执行的分布式计算框架，省去大规模数据搬迁的开销，适合批处理、数据分析和生信流水线。

Community-driven, simple, yet powerful framework for fast, cost-effective distributed Compute over Data.

v1.9.5发布于 2026-10-12 18:48 UTC876star105fork同步于 2026-11-11 05:50 UTC
分布式计算数据本地化批处理去中心化生信流水线
对比 GitHub 官网ai-artai-data-collectionai-pipelinebatch-processingbioinformatics-pipeline

怎么上手

由 README 提炼，执行前请确认
原文 
curl -sL https://get.bacalhau.org/install.sh | bash
bacalhau version
硬件要求按 README 说明

README 未说明具体硬件要求，仅提供 Linux/macOS 安装脚本

下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼
没人工点评？写下你的经验

把计算搬到数据所在处的开源分布式计算编排框架，减少大规模数据搬运

把计算任务调度到数据所在节点上执行的分布式计算框架，省去大规模数据搬迁的开销，适合批处理、数据分析和生信流水线。

核心能力

  • 单二进制同时充当客户端、编排器和计算节点
  • 支持 Docker 与 WebAssembly 多种执行引擎
  • 对接 S3、HTTP/HTTPS、IPFS 和本地存储
  • 支持 batch、ops、daemon、service 多种作业类型
  • 可用 YAML 声明式或 CLI 命令式提交作业

容易踩的坑

安装脚本只覆盖 Linux/macOS，其他平台需参考官方安装文档；运行作业依赖 Docker 或 WebAssembly 等执行引擎，需按需准备；README 未说明默认端口等网络配置，需查官方文档

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

最近发版

5 个版本v1.9.5
全部 release
  1. v1.9.5最新正式版2026-10-12 · 2026-10-12 18:48 UTC

    What's Changed

    Full Changelog: https://github.com/bacalhau-project/bacalhau/compare/v1.9.4...v1.9.5

  2. v1.9.42026-09-05 · 2026-09-05 18:35 UTC
    查看更新说明

    What's Changed

    Full Changelog: https://github.com/bacalhau-project/bacalhau/compare/v1.9.3...v1.9.4

  3. v1.9.32026-08-09 · 2026-08-09 23:36 UTC
    查看更新说明

    What's Changed

  4. v1.9.22026-07-19 · 2026-07-19 19:30 UTC
    查看更新说明

    What's Changed

    Full Changelog: https://github.com/bacalhau-project/bacalhau/compare/v1.9.1...v1.9.2

  5. v1.9.12026-07-18 · 2026-07-18 19:40 UTC
    查看更新说明

    What's Changed

    Full Changelog: https://github.com/bacalhau-project/bacalhau/compare/v1.9.0...v1.9.1

用户点评

登录用户的真实使用记录，可按版本和硬件筛选
共 0 条

    还没有人点评。第一个说出真实体验的人最有价值。

    README 原文

    未翻译
    在 GitHub 打开

    What is Bacalhau?

    Bacalhau is an open-source distributed compute orchestration framework designed to bring compute to the data. Instead of moving large datasets around networks, Bacalhau makes it easy to execute jobs close to the data's location, drastically reducing latency and resource overhead.

    Why Bacalhau?

    • ⚡ Fast job processing: Jobs in Bacalhau are processed where the data was created and all jobs are parallel by default
    • 💰 Low cost: Reduce (or eliminate) ingress/egress costs since jobs are processed closer to the source
    • 🔒 Secure: Data scrubbing and security can happen before migration, with a granular, code-based permission model
    • 🚛 Large-scale data: Process petabytes of data efficiently without massive data transfers
    • 🏢 Data sovereignty: Process sensitive data within security boundaries without requiring it to leave your premises
    • 🤝 Cross-organizational computation: Allow specific vetted computations on protected datasets without exposing raw data

    Key Features

    1. Single Binary Simplicity: Bacalhau is a single self-contained binary that functions as a client, orchestrator, and compute node—making it incredibly easy to set up and scale

    2. Modular Architecture: Support for multiple execution engines (Docker, WebAssembly) and storage providers through clean interfaces

    3. Orchestrator-Compute Model: A dedicated orchestrator coordinates job scheduling, while compute nodes run tasks

    4. Flexible Storage Integrations: Integrates with S3, HTTP/HTTPS, IPFS, and local storage systems

    5. Multiple Job Types: Support for batch, ops, daemon, and service job types for different workflow requirements

    6. Declarative & Imperative Submissions: Define jobs in YAML (declarative) or pass arguments via CLI (imperative)

    7. Publisher Support: Output results to local volumes, S3, or other storage backends

    Getting Started

    Quick Installation

    # Install Bacalhau CLI (Linux/macOS)
curl -sL https://get.bacalhau.org/install.sh | bash

# Verify installation
bacalhau version

    For the complete quick start guide, including running your first job, see the Quick Start Documentation.

    Use Cases

    Bacalhau's distributed compute framework enables a wide range of applications:

    • Log Processing: Process logs efficiently at scale by running distributed jobs directly at the source
    • Distributed Data Warehousing: Query and analyze data across multiple regions without moving large datasets
    • Fleet Management: Efficiently manage distributed nodes across multiple environments
    • Distributed Machine Learning: Train and deploy ML models across a distributed compute fleet
    • Edge Computing: Run compute tasks closer to the data source for applications requiring low latency

    Documentation

    📚 Read the Bacalhau documentation 📚

    The Bacalhau documentation contains all the information you need to get started:

    Community & Contributing

    Bacalhau has a very friendly community, and we are always happy to help:

    • Join the Slack Community and go to the #general channel - it is the easiest way to engage with other members in the community and get help

    If you are interested in contributing to the Bacalhau project:

    We are excited to hear your feedback!

    Open Source

    This repository contains the open-source Bacalhau software, covered under the Apache-2.0 license except where noted. Commercial terms are not required to use, modify, or distribute this code under that license.

    The Apache 2.0 license does not grant rights to the Bacalhau name or logos. Distributions may use those trademarks only as permitted by the applicable trademark policy or other written permission.

    We explicitly grant permission for you to make a build that includes our trademarks while developing Bacalhau software itself. You may not publish or share the build, and you may not use that build to run Bacalhau software for any other purpose.

    We have borrowed the above Open Source clause from the excellent System Initiative

    相关项目

    同分类里 star 最高的项目
    对比全部 →
    netdata
    netdata·Go

    开箱即用的全栈监控平台，秒级采集指标并自动告警，内置机器学习异常检测，小团队也能低成本搭建可观测性。

    全栈监控+4分析 / BI入门
    81361+656.7kv2.12.32026-11-11 00:14 UTC
    TrendRadar
    sansan0·Python

    聚合多平台热点与 RSS 订阅，用 AI 做关键词筛选、翻译和简报分析，并通过微信、飞书、钉钉等渠道推送到手机，帮你摆脱信息过载。

    舆情监控+4分析 / BI进阶
    63574+7625k2026-11-05 00:47 UTC
    best-of-ml-python
    lukasmasuch

    每周更新的机器学习 Python 库排行榜，按类别和评分整理优质库，帮你快速找到 AutoML、深度学习、数据可视化等方向的趁手工具。

    机器学习库+4分析 / BI入门
    23862+43.1k2025.10.302026-11-05 14:09 UTC
    vanna
    vanna-ai·Python

    🤖 Chat with your SQL database 📊. Accurate Text-to-SQL Generation via LLMs using Agentic Retrieval 🔄.

    分析 / BI
    238062.5k2026-02-02 14:14 UTC