SLAMA is a version of LightAutoML library modified to run in distributed mode with Apache Spark framework.

It requires:

1. Python 3.9
2. PySpark 3.2+ (installed as a dependency)
3. Synapse ML library (It will be downloaded by Spark automatically)

Currently, only tabular Preset is supported. See demo with spark-based tabular automl preset in examples/spark/tabular-preset-automl.py. For further information check docs in the root of the project containing dedicated SLAMA section.

This project is licensed under the Apache License, Version 2.0. See LICENSE file for more details.

First of all you need to install git and poetry.

# Load LAMA source code
git clone https://github.com/fonhorst/LightAutoML_Spark.git

cd LightAutoML/

# !!!Choose only one item!!!

# 1. Global installation: Don't create virtual environment
poetry config virtualenvs.create false --local

# 2. Recommended: Create virtual environment inside your project directory
poetry config virtualenvs.in-project true

# For more information read poetry docs

# Install LAMA
poetry lock
poetry install