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Local Setup Instructions

These instructions are for setting up your local development environment if you are not using GitHub Codespaces.

Using a Local Dev Container

  1. Install Docker Desktop.

  2. Install Visual Studio Code.

  3. Clone the repository to your local machine:

    git clone https://github.com/Microsoft-CISL/sqlite-autotuning.git
cd sqlite-autotuning

  4. Open the cloned repository in Visual Studio Code.

  5. Install the @recommended Extensions, especially the Remote - Containers extension for Visual Studio Code.

  6. Open the project in a Dev Container:

    • Press F1 to open the Command Palette.
    • Type Remote-Containers: Reopen in Container and select it.

    This will build the Docker container as specified in the .devcontainer folder and open your project inside that container.

Using a Local Python Environment via Conda

  1. Install Anaconda or Miniconda.

  2. Clone the repository to your local machine:

    git clone https://github.com/Microsoft-CISL/sqlite-autotuning.git
cd sqlite-autotuning

  3. Clone the MLOS repository as a submodule:

    git clone https://github.com/microsoft/MLOS.git MLOS

  4. Create a new conda environment:

    conda env create -f MLOS/conda-envs/environment.yml
conda activate mlos

  5. Install the required local dependencies:

    pip install -U -r requirements.txt

  6. Get the remote data files:

    test -f mlos_bench.sqlite || wget -q -Nc https://mlospublic.z13.web.core.windows.net/sqlite-autotuning/mlos_bench.sqlite
mkdir -p workdir/benchbase/db.bak && wget -q -c -O workdir/benchbase/db.bak/tpcc.db https://mlospublic.z13.web.core.windows.net/sqlite-autotuning/tpcc.db

  7. Continue with the instructions in the README to set up and run the project.