Splitgraph has been acquired by EDB! Read the blog post.

Installation

In addition to the sgr CLI itself, advanced sgr workflows require an sgr engine. To install the sgr CLI, see the CLI installation guide

Requirements

To run the sgr engine, you will need to be able to run Docker. There are instructions available for installing Docker on Linux, Mac and Windows (use Docker Desktop for Windows 10 Pro/Enterprise (15063+) / Windows 10 Home (19018+) or Docker Toolbox for earlier versions of Windows.)

To check that Docker is installed and working, run:

$ docker run hello-world

Installation

Automated

For Linux and macOS, there's an install script available:

$ bash -c "$(curl -sL https://github.com/splitgraph/sgr/releases/latest/download/install.sh)"

This script will:

  • Download the sgr binary from the releases page
  • Set up and initialize the sgr Engine
  • Register you on Splitgraph (data.splitgraph.com). This is completely optional: sgr can be used in a decentralized manner, like Git.

If you're running Windows or prefer to follow the steps manually, skip to the manual section.

Homebrew

sgr is on Homebrew:

$ brew install sgr

Manual

Once sgr is installed, create a new engine via:

$ sgr engine add

This will:

  • Prompt you for a password: this is just the password used to protect your local engine and will be stored in the generated configuration file.
  • Pull and start the latest sgr engine image
  • By default, sgr will name the engine container splitgraph_engine_default and create two Docker volumes:
    • splitgraph_engine_default_data to store the physical data
    • splitgraph_engine_default_metadata to store the metadata about composition of Splitgraph images.
  • Initialize the engine
  • Generate a minimal .sgconfig file for you in your home directory (~/.splitgraph/.sgconfig).

There are extra options in sgr engine for advanced users. To see them, run sgr engine --help or see the CLI reference.

Advanced installation

Docker

You can use Docker directly to pull and start the engine:

$ docker run -d \\
    -e POSTGRES_PASSWORD=supersecure \\
    -p 5432:5432 \\
    -v $PWD/splitgraph_data:/var/lib/splitgraph/objects \\
    -v $PWD/splitgraph_metadata:/var/lib/postgresql/data \\
    splitgraph/engine

By default, sgr is configured to speak to the engine running on localhost:5432 with a superuser account called sgr and a password supersecure against a database called splitgraph. You can change the credentials used by sgr by editing the configuration file.

To complete the installation, run:

$ sgr init

Docker Compose

You can also use Docker Compose. A sample Compose configuration for the service is as follows:

version: "3"
services:
  engine:
    image: splitgraph/engine:${DOCKER_TAG-stable}
    ports:
      - "0.0.0.0:5432:5432"
    environment:
      - POSTGRES_USER=sgr
      - POSTGRES_PASSWORD=supersecure
      - POSTGRES_DB=splitgraph
      - SG_LOGLEVEL=INFO
      - SG_CONFIG_FILE=/.sgconfig
    expose:
      - 5432
    volumes:
      - splitgraph_data:/var/lib/splitgraph/objects
      - splitgraph_metadata:/var/lib/postgresql/data
      - ${HOME}/.splitgraph/.sgconfig:/.sgconfig

Upgrading

You can upgrade the single-binary sgr by running sgr upgrade which will download the new binary and upgrade the engine (if the engine is managed by sgr engine).

sgr engine upgrade upgrades an engine that's managed by sgr engine by deleting the current Docker container and starting a new one, keeping all data volumes intact. While the versions of sgr and of the engine do not need to be the same, we recommend you match them, as we currently test and release the engine and sgr in lockstep.

Configuration file

The sgr configuration file is usually stored in the user's home directory (~/.splitgraph/.sgconfig).

For more information on configuring sgr, see the configuration reference.

Next Steps

You can take a look at the five minute demo that will go through the basics of building and extending data images. You can also try out some self-contained example sgr projects on our GitHub.