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apache / submarine / e1809e614712a5743ffd2c0bcf0aa381ec50913d
commite1809e614712a5743ffd2c0bcf0aa381ec50913d[log] [tgz]
authorRyan Lo <lowc1012@gmail.com>Wed May 06 12:29:13 2020 +0800
committerLiu Xun <liuxun@apache.org>Wed May 06 10:38:38 2020 +0000
treee8c0fd8d4a79808baa52f90d7b822ce5d1237338
parentea4d1a38024216c7289d953f21521d43426e56f2 [diff]
SUBMARINE-478. Running jupyterlab container in KIND

### What is this PR for?
Use jupyter's yaml file to run a jupyter container,
1. First support mounting local path into jupyter
2. Support setting jupyter password
3. Run by creating jupyter pod in KIND
4. Provide simple Python library support (if the submarine project has a relatively complete Python image, it can also be used)

### What type of PR is it?
[Feature]

### Todos
* [ ] - Task

### What is the Jira issue?
[SUBMARINE-478](https://issues.apache.org/jira/projects/SUBMARINE/issues/SUBMARINE-478)

### How should this be tested?
[passed CI](https://travis-ci.org/github/lowc1012/submarine/builds/682881085)

### Screenshots (if appropriate)
<img width="984" alt="screenshot" src="https://user-images.githubusercontent.com/52355146/80968374-6e735e00-8e4a-11ea-9743-857944aa9cbd.png">

<img width="1044" alt="screenshot1" src="https://user-images.githubusercontent.com/52355146/80968115-00c73200-8e4a-11ea-86f6-725c6fc14831.png">

<img width="337" alt="screenshot2" src="https://user-images.githubusercontent.com/52355146/80968165-12103e80-8e4a-11ea-9063-a6791cda851e.png">

### Questions:
* Does the licenses files need update? No
* Is there breaking changes for older versions? No
* Does this needs documentation? No

Author: Ryan Lo <lowc1012@gmail.com>

Closes #275 from lowc1012/SUBMARINE-478 and squashes the following commits:

5a71232 [Ryan Lo] SUBMARINE-478. Change the host path
9b0ecbd [Ryan Lo] SUBMARINE-478. Running jupyterlab container in KIND
2 files changed
tree: e8c0fd8d4a79808baa52f90d7b822ce5d1237338
  1. .github/
  2. bin/
  3. conf/
  4. dev-support/
  5. docs/
  6. licenses-binary/
  7. submarine-all/
  8. submarine-client/
  9. submarine-cloud/
  10. submarine-commons/
  11. submarine-dist/
  12. submarine-sdk/
  13. submarine-security/
  14. submarine-server/
  15. submarine-test/
  16. submarine-workbench/
  17. .asf.yaml
  18. .editorconfig
  19. .gitignore
  20. .travis.yml
  21. LICENSE
  22. LICENSE-binary
  23. NOTICE
  24. NOTICE-binary
  25. pom.xml
  26. README.md
README.md

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Build Status License HitCount

What is Apache Submarine?

Apache Submarine is a unified AI platform which allows engineers and data scientists to run Machine Learning and Deep Learning workload in distributed cluster.

Goals of Submarine:

  • It allows jobs easy access data/models in HDFS and other storages.
  • Can launch services to serve TensorFlow/PyTorch/MXNet models.
  • Support run distributed TensorFlow jobs with simple configs.
  • Support run user-specified Docker images.
  • Support specify GPU and other resources.
  • Support launch TensorBoard for training jobs if user specified.
  • Support customized DNS name for roles (like TensorBoard.$user.$domain:6006)

Architecture

image-20190811191220934

Components

Submarine Workbench

Submarine Workbench is a WEB system. Algorithm engineers can perform complete lifecycle management of machine learning jobs in the Workbench.

  • Projects

    Manage machine learning jobs through project.

  • Data

    Data processing, data conversion, feature engineering, etc. in the workbench.

  • Job

    Data processing, algorithm development, and model training in machine learning jobs as a job run.

  • Model

    Algorithm selection, parameter adjustment, model training, model release, model Serving.

  • Workflow

    Automate the complete life cycle of machine learning operations by scheduling workflows for data processing, model training, and model publishing.

  • Team

    Support team development, code sharing, comments, code and model version management.

Submarine Core

The submarine core is the execution engine of the system and has the following features：

  • ML Engine

    Support for multiple machine learning framework access, such as tensorflow, pytorch, mxnet.

  • Data Engine

    Docking the externally deployed Spark calculation engine for data processing.

  • SDK

    Support Python, Scala, R language for algorithm development, The SDK is provided to help developers use submarine's internal data caching, data exchange, and task tracking to more efficiently improve the development and execution of machine learning tasks.

  • Submitter

    Compatible with the underlying hybrid scheduling system of yarn and k8s for unified task scheduling and resource management, so that users are not aware.

  • Hybrid Scheduler
    • YARN
    • Kubernetes

Quick start

Run mini-submarine in one step

You can use mini-submarine for a quick experience submairne.

This is a docker image built for submarine development and quick start test.

Installation and deployment

Read the Quick Start Guide

Apache Submarine Community

Read the Apache Submarine Community Guide

How to contribute Contributing Guide

License

The Apache Submarine project is licensed under the Apache 2.0 License. See the LICENSE file for details.