OpenMetadata/ingestion/tests/integration/source/mlflow
Ayush Shah 9d11029ec8
Fixes 10351: Fixes Metrics Computation, Samping, test suites and partioning (#10603)
Co-authored-by: Teddy Crepineau <teddy.crepineau@gmail.com>
2023-04-11 20:58:31 +05:30
..
__init__.py [issue-1976] - Ingestion SonarCloud (#2085) 2022-01-07 10:28:38 +01:00
docker-compose.yml Fix #5367 - MlFlow connector & MLServices (#5446) 2022-06-21 14:54:36 +02:00
Dockerfile fix: ingestion/tests/integration/source/mlflow/Dockerfile to reduce vulnerabilities (#3618) 2022-03-23 18:26:41 -07:00
experiment.py [issue-1976] - Ingestion SonarCloud (#2085) 2022-01-07 10:28:38 +01:00
Makefile [issue-1976] - Ingestion SonarCloud (#2085) 2022-01-07 10:28:38 +01:00
README.md Fix #5367 - MlFlow connector & MLServices (#5446) 2022-06-21 14:54:36 +02:00
train.py Fixes 10351: Fixes Metrics Computation, Samping, test suites and partioning (#10603) 2023-04-11 20:58:31 +05:30

MlFlow Integration Test

We have prepared a small test to check the MlFlow ingestion.

We have used a decoupled architecture for MlFlow with:

  • mlflow running in a remote server
  • minio as the artifact store
  • mysql as the registry

To run this test:

  • cd into this directory
  • make build
  • pip install mlflow-skinny sklearn. We use the skinny one for the client.
  • python experiment.py should show new experiments in http://localhost:5000
  • python train.py will register a new model
  • metadata ingest -c examples/workflows/mlflow.yaml will run the workflow.