library/spark

Apache Spark 是一款专为大规模数据处理打造的统一分析引擎，它集成了批处理、流处理、机器学习、图计算等多种数据处理能力，通过基于内存的计算模型显著提升数据处理速度，具备高效、易用且可扩展的特性，能为企业和开发者提供一站式的大数据分析解决方案，支持从数据提取、清洗、转换到深度分析与应用部署的全流程，满足各类复杂数据场景下的处理需求，助力实现数据驱动的高效决策与业务创新。

121 次收藏下载次数: 0状态：Docker 官方镜像维护者：Docker 官方镜像仓库类型：镜像最近更新：10 天前

让 AI 帮你使用轩辕镜像？ · 展开查看说明 · 点击收起说明

如果你使用 DeepSeek、元宝 AI、Copilot、ChatGPT 等 AI 工具，协助配置轩辕镜像、编写 docker pull 命令、修改 Docker Compose 镜像地址、配置镜像加速、排查镜像拉取失败、分析报错日志等问题，请先让 AI 阅读并遵守轩辕镜像的规则文档。

只需在 AI 对话中先发送下面这句话即可：

请先完整阅读并严格遵守以下文档中的全部规则与要求：

https://xuanyuan.cloud/agents.md

在未充分阅读并理解该文档前，不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。

查看 agents.md 用法指南与完整示范。国内用户首推元宝 AI、DeepSeek 的深度思考模式，不推荐豆包 AI；Cursor 等编辑器可在对话 @ 该链接，或加入 User Rules。若 AI 无法访问外链，可打开说明文档复制全文粘贴。文档会随站点更新，复制内容可能过期，建议定期检查。

DockerHub 官方简介

轩辕镜像中文简介

下载命令

镜像标签列表与下载命令

轩辕镜像，不浪费每一次拉取。

点击查看

Quick reference

Maintained by:
https://spark.apache.org/committers.html
Where to get help:
https://spark.apache.org/community.html

Supported tags and respective `Dockerfile` links

https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-python3-r-ubuntu/Dockerfile

Quick reference (cont.)

Where to file issues:
https://issues.apache.org/jira/browse/SPARK
Supported architectures: (https://github.com/docker-library/official-images#architectures-other-than-amd64)
https://hub.docker.com/r/amd64/spark/, https://hub.docker.com/r/arm64v8/spark/
Published image artifact details:
https://github.com/docker-library/repo-info/blob/master/repos/spark (https://github.com/docker-library/repo-info/commits/master/repos/spark)
(image metadata, transfer size, etc)
Image updates:
https://github.com/docker-library/official-images/issues?q=label%3Alibrary%2Fspark
https://github.com/docker-library/official-images/blob/master/library/spark (https://github.com/docker-library/official-images/commits/master/library/spark)
Source of this description:
https://github.com/docker-library/docs/tree/master/spark (https://github.com/docker-library/docs/commits/master/spark)

What is Apache Spark™?

Apache Spark™ is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, pandas API on Spark for pandas workloads, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing.

!https://raw.githubusercontent.com/docker-library/docs/a16cd1ae80c04193c029a686d3006c95edb81594/spark/logo.png

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the https://spark.apache.org/documentation.html. This README file only contains basic setup instructions.

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

console
docker run -it spark /opt/spark/bin/spark-shell

Try the following command, which should return 1,000,000,000:

scala
scala> spark.range(1000 * 1000 * 1000).count()

Interactive Python Shell

The easiest way to start using PySpark is through the Python shell:

console
docker run -it spark:python3 /opt/spark/bin/pyspark

And run the following command, which should also return 1,000,000,000:

python
>>> spark.range(1000 * 1000 * 1000).count()

Interactive R Shell

The easiest way to start using R on Spark is through the R shell:

console
docker run -it spark:r /opt/spark/bin/sparkR

Running Spark on Kubernetes

https://spark.apache.org/docs/latest/running-on-kubernetes.html

Configuration and environment variables

See more in https://github.com/apache/spark-docker/blob/master/OVERVIEW.md#environment-variable

License

Apache Spark, Spark, Apache, the Apache feather logo, and the Apache Spark project logo are trademarks of The Apache Software Foundation.

Licensed under the https://www.apache.org/licenses/LICENSE-2.0.

As with all Docker images, these likely also contain other software which may be under other licenses (such as Bash, etc from the base distribution, along with any direct or indirect dependencies of the primary software being contained).

Some additional license information which was able to be auto-detected might be found in https://github.com/docker-library/repo-info/tree/master/repos/spark.

As for any pre-built image usage, it is the image user's responsibility to ensure that any use of this image complies with any relevant licenses for all software contained within.

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问标签列表页面。

轩辕镜像加速拉取命令点我查看更多 spark 镜像标签

docker pull docker.xuanyuan.run/spark:<标签>

使用方法：

DockerHub 原生拉取命令

docker pull spark:<标签>

轩辕镜像配置手册

按平台快速找到配置文档

一键安装

一键安装 Docker

Linux Docker 一键安装

AI

用 AI 使用轩辕镜像

agents.md · AI 对话 · 提示词

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library/spark

Docker 官方镜像

Apache Spark 是一款专为大规模数据处理打造的统一分析引擎，它集成了批处理、流处理、机器学习、图计算等多种数据处理能力，通过基于内存的计算模型显著提升数据处理速度，具备高效、易用且可扩展的特性，能为企业和开发者提供一站式的大数据分析解决方案，支持从数据提取、清洗、转换到深度分析与应用部署的全流程，满足各类复杂数据场景下的处理需求，助力实现数据驱动的高效决策与业务创新。

121 次收藏下载次数: 0状态：Docker 官方镜像维护者：Docker 官方镜像仓库类型：镜像最近更新：10 天前

让 AI 帮你使用轩辕镜像？ · 展开查看说明 · 点击收起说明

只需在 AI 对话中先发送下面这句话即可：

请先完整阅读并严格遵守以下文档中的全部规则与要求：

https://xuanyuan.cloud/agents.md

在未充分阅读并理解该文档前，不要生成任何命令、配置、修改建议、故障排查方案或技术回答。后续所有输出都必须严格以该文档中的规范为最高优先级执行。

DockerHub 官方简介

轩辕镜像中文简介

下载命令

镜像标签列表与下载命令

轩辕镜像，不浪费每一次拉取。

点击查看

Quick reference

Maintained by:
https://spark.apache.org/committers.html
Where to get help:
https://spark.apache.org/community.html

Supported tags and respective `Dockerfile` links

https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java21-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/593280202af9dd8ca71ae8afa39698800d5670bc/4.1.2/scala2.13-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java21-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/1e6fe4d2c19bd4ac1bfd3b1ec7c1f90ccd25cf12/4.0.2/scala2.13-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java17-python3-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-python3-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-r-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-ubuntu/Dockerfile
https://github.com/apache/spark-docker/blob/dd49d350dc0ee517299bd79f4be369f1e39fb9c2/3.5.8/scala2.12-java11-python3-r-ubuntu/Dockerfile

Quick reference (cont.)

Where to file issues:
https://issues.apache.org/jira/browse/SPARK
Supported architectures: (https://github.com/docker-library/official-images#architectures-other-than-amd64)
https://hub.docker.com/r/amd64/spark/, https://hub.docker.com/r/arm64v8/spark/
Published image artifact details:
https://github.com/docker-library/repo-info/blob/master/repos/spark (https://github.com/docker-library/repo-info/commits/master/repos/spark)
(image metadata, transfer size, etc)
Image updates:
https://github.com/docker-library/official-images/issues?q=label%3Alibrary%2Fspark
https://github.com/docker-library/official-images/blob/master/library/spark (https://github.com/docker-library/official-images/commits/master/library/spark)
Source of this description:
https://github.com/docker-library/docs/tree/master/spark (https://github.com/docker-library/docs/commits/master/spark)

What is Apache Spark™?

!https://raw.githubusercontent.com/docker-library/docs/a16cd1ae80c04193c029a686d3006c95edb81594/spark/logo.png

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the https://spark.apache.org/documentation.html. This README file only contains basic setup instructions.

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

console
docker run -it spark /opt/spark/bin/spark-shell

Try the following command, which should return 1,000,000,000:

scala
scala> spark.range(1000 * 1000 * 1000).count()

Interactive Python Shell

The easiest way to start using PySpark is through the Python shell:

console
docker run -it spark:python3 /opt/spark/bin/pyspark

And run the following command, which should also return 1,000,000,000:

python
>>> spark.range(1000 * 1000 * 1000).count()

Interactive R Shell

The easiest way to start using R on Spark is through the R shell:

console
docker run -it spark:r /opt/spark/bin/sparkR

Running Spark on Kubernetes

https://spark.apache.org/docs/latest/running-on-kubernetes.html

Configuration and environment variables

See more in https://github.com/apache/spark-docker/blob/master/OVERVIEW.md#environment-variable

License

Apache Spark, Spark, Apache, the Apache feather logo, and the Apache Spark project logo are trademarks of The Apache Software Foundation.

Licensed under the https://www.apache.org/licenses/LICENSE-2.0.

Some additional license information which was able to be auto-detected might be found in https://github.com/docker-library/repo-info/tree/master/repos/spark.

As for any pre-built image usage, it is the image user's responsibility to ensure that any use of this image complies with any relevant licenses for all software contained within.

镜像拉取方式

您可以使用以下命令拉取该镜像。请将 <标签> 替换为具体的标签版本。如需查看所有可用标签版本，请访问标签列表页面。

轩辕镜像加速拉取命令点我查看更多 spark 镜像标签

docker pull docker.xuanyuan.run/spark:<标签>

使用方法：

DockerHub 原生拉取命令

docker pull spark:<标签>

轩辕镜像配置手册

按平台快速找到配置文档

一键安装

一键安装 Docker

Linux Docker 一键安装

AI

用 AI 使用轩辕镜像

agents.md · AI 对话 · 提示词

Docker

登录仓库拉取

登录认证 · 私有仓库

专属域名拉取

免登录 · 高速拉取

Linux

Docker 镜像配置

Windows / Mac

Docker Desktop 配置

MacOS OrbStack

OrbStack 容器

Apple Container

macOS 原生容器

Docker Compose

Compose 项目配置

NAS

群晖

Synology 配置

飞牛

fnOS 镜像配置

绿联

绿联 NAS

威联通

QNAP 配置

极空间

极空间 NAS

Unraid

Unraid NAS

企业仓库

其他仓库

ghcr · Quay · nvcr

Harbor 镜像源

Proxy Repository 对接

Portainer 镜像源

Registries 配置

Nexus 镜像源

Docker Proxy 缓存

开发工具

Dev Containers

VS Code 开发容器

Podman

Podman 配置指南

Singularity / Apptainer

HPC 科学计算容器

Kubernetes

K8s Containerd

Kubernetes · Containerd

K3s

轻量级集群

面板 / 网络

爱快路由

爱快 4.0 · iKuai 镜像加速

宝塔面板

一键配置镜像源

需要其他帮助？请查看我们的常见问题Docker 镜像访问常见问题解答或提交工单

镜像拉取常见问题

功能

版本功能对比

功能对比 · 版本选择

支持的镜像仓库

Docker Hub · GCR · GHCR

专属域名用法

专属域名 · 开启停用 · 多仓库

新手拉取配置

docker search 限制

专属域名 · Hub 搜索

不支持 push

仅支持 pull · 不支持

拉取速度原因

带宽 · 缓存 · 冷热镜像

错误码

402 与流量用尽

402 · 流量包 · 充值

401 认证失败

401 · docker login

manifest unknown

标签错误 · 镜像不存在

410 Gone 排查

410 · Docker 升级

429 限流

免费版 · 专业版 · 企业版 · 请求频率

其他报错

DNS 超时

DNS 解析 · 网络超时

TLS 证书失败

no matching manifest（架构）

账号

失败是否计费

manifest · blob · 计费

申请开发票（企业 / 个人）

企业 · 个人 · 工单

修改登录密码

网站 · 仓库 · 重置

注销账户

工单 · 数据 · 注销

原理

mirrors 不生效

daemon.json · 重启

去掉域名前缀

docker tag · 重命名

指定架构拉取

ARM64 · AMD64 · 多架构

latest 与「最新」

digest · 版本号 · 标签

查看全部问题→

用户好评

来自真实用户的反馈，见证轩辕镜像的优质服务

oldzhang

运维工程师

Linux服务器

"Docker访问体验非常流畅，大镜像也能快速完成下载。"

library/spark

Quick reference

Supported tags and respective Dockerfile links

Quick reference (cont.)

What is Apache Spark™?

Online Documentation

Interactive Scala Shell

Interactive Python Shell

Interactive R Shell

Running Spark on Kubernetes

Configuration and environment variables

License

镜像拉取方式

轩辕镜像加速拉取命令点我查看更多 spark 镜像标签

DockerHub 原生拉取命令

轩辕镜像配置手册

一键安装

一键安装 Docker

AI

用 AI 使用轩辕镜像

Docker

登录仓库拉取

专属域名拉取

Linux

Windows / Mac

MacOS OrbStack

Apple Container

Docker Compose

NAS

群晖

飞牛

绿联

威联通

极空间

Unraid

企业仓库

其他仓库

Harbor 镜像源

Portainer 镜像源

Nexus 镜像源

开发工具

Dev Containers

Podman

Singularity / Apptainer

Kubernetes

K8s Containerd

K3s

面板 / 网络

爱快路由

宝塔面板

镜像拉取常见问题

功能

版本功能对比

支持的镜像仓库

专属域名用法

新手拉取配置

docker search 限制

不支持 push

拉取速度原因

错误码

402 与流量用尽

401 认证失败

manifest unknown

410 Gone 排查

429 限流

其他报错

DNS 超时

TLS 证书失败

no matching manifest（架构）

账号

失败是否计费

申请开发票（企业 / 个人）

修改登录密码

注销账户

原理

mirrors 不生效

去掉域名前缀

指定架构拉取

latest 与「最新」

用户好评

Supported tags and respective `Dockerfile` links

Supported tags and respective `Dockerfile` links