A simple util to get a spark and mlflow session objects from an .env file
Project description
Databricks Session Util
A simple utility for spark and mlflow session objects
Setup
Quick Install
python -m pip install databricks_session
Build from source
Clone the repository
git clone https://github.com/Broomva/databricks_session.git
Install the package
cd databricks_session && make install
Build manually
After cloning, create a virtual environment
conda create -n databricks_session python=3.10
conda activate databricks_session
Install the requirements
pip install -r requirements.txt
Run the python installation
python setup.py install
Usage
The deployment requires a .env file created under local folder:
touch .env
It should have a schema like this:
databricks_experiment_name=''
databricks_experiment_id=''
databricks_host=''
databricks_token=''
databricks_username=''
databricks_password=''
databricks_cluster_id=''
import databricks_session
# Create a Spark session
spark = DatabricksSparkSession().get_session()
# Connect to MLFLow Artifact Server
mlflow_session = DatabricksMLFlowSession().get_session()
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