README.md

README - Databricks notebooks

Overview

These notebooks correspond to command line scripts described here:

• MLflow model reports
• MLflow object retrieval

MLflow Model reports notebooks

• Detailed_Model_Report
• Summary_Report - WIP

MLflow object dump notebooks

• MLflow_Model_Manager
• Get_MLflow_Model
• Get_Registered_Model
• Get_Model_Version
• Get_Experiment
• Get_Run

Installing notebooks into Databricks workspace

You can import the notebooks into Databricks in two ways:

• As a workspace folder
• As a Git Repo folder

Import directory as Databricks workspace folder

See the Workspace CLI.

git clone https://github.com/mlflow/mlflow-reports

databricks workspace import_dir \
  databricks_notebooks \
  /Users/me@mycompany.com/mlflow-reports

Clone directory as Databricks Git Repo

You can load a Git Repo either through the Databricks UI or via the command line.

1. Load through Databricks UI

See Clone a Git Repo & other common Git operations.

2. Load from command line with cUrl

Note it's best to use the curl version since the CLI doesn't appear to support the sparse checkout option.

curl \
  https://my.company.com/api/2.0/repos \
  -H "Authorization: Bearer MY_TOKEN" \
  -X POST \
  -d ' {
    "url": "https://github.com/mlflow/mlflow-reports",
    "provider": "gitHub",
    "path": "/Repos/me@my.company.com/mlflow-reports",
    "sparse_checkout": {
      "patterns": [ "databricks_notebooks" ]
      }
    }'