commit | 2e6c387d461dfa4a066a50640327bcf5f55e43a8 | [log] [tgz] |
---|---|---|
author | Lisa <aeioulisa@gmail.com> | Fri Apr 16 13:44:07 2021 +0800 |
committer | Liu Xun <liuxun@apache.org> | Thu Apr 22 09:33:21 2021 +0000 |
tree | 1993ab1ea6ea8b78b1eb02418f7fe8ad9eef9c75 | |
parent | 860c04301a806466d261ecee7d3e8cb4a58bec0a [diff] |
SUBMARINE-793. Drop old Ranger version support ### What is this PR for? More recently, the precommit takes hours to complete, a lot of it is spent on running UT for different combination of Hadoop, Spark and Ranger. We currently run against Ranger 1.0, 1.1, 1.2 and 2.0. I propose we retain 1.2 and 2.0 and drop 1.0 and 1.1. Dropping these two will save around 40 minutes per precommit (out of more than 3 hours). ### What type of PR is it? [Improvement] ### Todos * [ ] - Task ### What is the Jira issue? https://issues.apache.org/jira/projects/SUBMARINE/issues/SUBMARINE-793 ### How should this be tested? https://travis-ci.org/github/aeioulisa/submarine/builds/767357154 ### Screenshots (if appropriate) ### Questions: * Do the license files need updating? Yes/No * Are there breaking changes for older versions? Yes/No * Does this need new documentation? Yes/No Author: Lisa <aeioulisa@gmail.com> Signed-off-by: Liu Xun <liuxun@apache.org> Closes #560 from aeioulisa/SUBMARINE-793 and squashes the following commits: 22b4f44 [Lisa] Drop old Ranger version support
Apache Submarine (Submarine for short) is an End-to-End Machine Learning Platform to allow data scientists to create end-to-end machine learning workflows. On Submarine, data scientists can finish each stage in the ML model lifecycle, including data exploration, data pipeline creation, model training, serving, and monitoring.
Some open-source and commercial projects are trying to build an end-to-end ML platform. What's the vision of Submarine?
Theodore Levitt once said:
“People don’t want to buy a quarter-inch drill. They want a quarter-inch hole.”
experiment
on prem or cloud via easy-to-use UI/API/SDK.experiment
and dependencies of environment
As mentioned above, Submarine attempts to provide Data-Scientist-friendly UI to make data scientists have a good user experience. Here're some examples.
# New a submarine client of the submarine server submarine_client = submarine.ExperimentClient(host='http://localhost:8080') # The experiment's environment, could be Docker image or Conda environment based environment = EnvironmentSpec(image='apache/submarine:tf-dist-mnist-test-1.0') # Specify the experiment's name, framework it's using, namespace it will run in, # the entry point. It can also accept environment variables. etc. # For PyTorch job, the framework should be 'Pytorch'. experiment_meta = ExperimentMeta(name='mnist-dist', namespace='default', framework='Tensorflow', cmd='python /var/tf_dist_mnist/dist_mnist.py --train_steps=100') # 1 PS task of 2 cpu, 1GB ps_spec = ExperimentTaskSpec(resources='cpu=2,memory=1024M', replicas=1) # 1 Worker task worker_spec = ExperimentTaskSpec(resources='cpu=2,memory=1024M', replicas=1) # Wrap up the meta, environment and task specs into an experiment. # For PyTorch job, the specs would be "Master" and "Worker". experiment_spec = ExperimentSpec(meta=experiment_meta, environment=environment, spec={'Ps':ps_spec, 'Worker': worker_spec}) # Submit the experiment to submarine server experiment = submarine_client.create_experiment(experiment_spec=experiment_spec) # Get the experiment ID id = experiment['experimentId']
submarine_client.get_experiment(id)
submarine_client.wait_for_finish(id)
submarine_client.get_log(id)
submarine_client.list_experiments(status='running')
For a quick-start, see Submarine On K8s
(Available on 0.6.0, see Roadmap)
If you want to know more about Submarine's architecture, components, requirements and design doc, they can be found on Architecture-and-requirement
Detailed design documentation, implementation notes can be found at: Implementation notes
Read the Apache Submarine Community Guide
How to contribute Contributing Guide
Issue Tracking: https://issues.apache.org/jira/projects/SUBMARINE
What to know more about what's coming for Submarine? Please check the roadmap out: https://cwiki.apache.org/confluence/display/SUBMARINE/Roadmap
The Apache Submarine project is licensed under the Apache 2.0 License. See the LICENSE file for details.