mlflow-yarn
Backend implementation for running MLFlow projects against a Hadoop/YARN backend).
To activate just do 'pip install mlflow-yarn' along your mlflow environment. It will register the plugin as an entrypoint with the YARN backend.
$ pip install mlflow-yarn
mlflow-yarn only supports Python ≥3.6.
Developement
Install from source
$ git clone https://github.com/criteo/cluster-pack
$ cd cluster-pack
$ pip install .
Examples
Example with pip only project
- Dependencies are pulled from requirements.txt
$ git clone https://github.com/criteo/mlflow-yarn
$ pip install mlflow
mlflow run tests/resources/pip_project -e compute_intersection -P size=10000 --backend yarn
Example with conda project
- Dependencies are pulled from conda.yaml
$ git clone https://github.com/criteo/mlflow-yarn
$ pip install mlflow
$ mlflow run tests/resources/conda_project -e compute_intersection -P size=10000 --backend yarn
More infos on setting up a project file.
Docker container environment is currently not supported.
4 maintainers
Release files for mlflow-yarn 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| mlflow_yarn-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Release files / mlflow_yarn-0.0.1-py3-none-any.whl
| Download URL | mlflow_yarn-0.0.1-py3-none-any.whl |
|---|---|
| Size | 15.0 kB |
| Tags | Python 3 |
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