Docker builds, images and tags
The Apache Superset community extensively uses Docker for development, release, and productionizing Superset. This page details our Docker builds and tag naming schemes to help users navigate our offerings.
Images are built and pushed to the Superset Docker Hub repository using GitHub Actions. Different sets of images are built and/or published at different times:
- Published releases (
release
): published using tags like3.0.0
and thelatest
tag. - Pull request iterations (
pull_request
): for each pull request, while we actively build the docker to validate the build, we do not publish those images for security reasons, we simplydocker build --load
- Merges to the main branch (
push
): resulting in new SHAs, with tags prefixed withmaster
for the latestmaster
version.
Build presets
We have a set of build "presets" that each represent a combination of parameters for the build, mostly pointing to either different target layer for the build, and/or base image.
Here are the build presets that are exposed through the supersetbot docker
utility:
lean
: The default Docker image, including both frontend and backend. Tags without a build_preset are lean builds (ie:latest
,4.0.0
,3.0.0
, ...).lean
builds do not contain database drivers, meaning you need to install your own. That applies to analytics databases AND the metadata database. You'll likely want to layer eithermysqlclient
orpsycopg2-binary
depending on the metadata database you choose for your installation, plus the required drivers to connect to your analytics database(s).dev
: For development, with a headless browser, dev-related utilities and root access. This includes some commonly used database drivers likemysqlclient
,psycopg2-binary
and some other used for development/CIpy311
, e.g., Py311: Similar to lean but with a different Python version (in this example, 3.11).ci
: For certain CI workloads.websocket
: For Superset clusters supporting advanced features.dockerize
: Used by Helm.
Key tags examples
latest
: The latest official release buildlatest-dev
: the-dev
image of the latest official release build, with a headless browser and root access.master
: The latest build from themaster
branch, implicitly the lean build presetmaster-dev
: Similar tomaster
but includes a headless browser and root access.pr-5252
: The latest commit in PR 5252.30948dc401b40982cb7c0dbf6ebbe443b2748c1b-dev
: A build for this specific SHA, which could be from amaster
merge, or release.websocket-latest
: The WebSocket image for use in a Superset cluster.
For insights or modifications to the build matrix and tagging conventions, check the supersetbot docker subcommand and the docker.yml GitHub action.
Key ARGs in Dockerfile
BUILD_TRANSLATIONS
: whether to build the translations into the image. For the frontend build this tells webpack to strip out all locales other thanen
from themoment-timezone
library. For the backendthis skips compiling the*.po
translation filesDEV_MODE
: whether to skip the frontend build, this is used by ourdocker-compose
dev setup where we mount the local volume and build usingwebpack
in--watch
mode, meaning as you alter the code in the local file system, webpack, from within a docker image used for this purpose, will constantly rebuild the frontend as you go. This ARG enables the initialdocker-compose
build to take much less time and resourcesINCLUDE_CHROMIUM
: whether to include chromium in the backend build so that it can be used as a headless browser for workloads related to "Alerts & Reports" and thumbnail generationINCLUDE_FIREFOX
: same as above, but for firefoxPY_VER
: specifying the base image for the python backend, we don't recommend altering this setting if you're not working on forwards or backwards compatibility
Caching
To accelerate builds, we follow Docker best practices and use apache/superset-cache
.
About database drivers
Our docker images come with little to zero database driver support since each environment requires different drivers, and maintaining a build with wide database support would be both challenging (dozens of databases, python drivers, and os dependencies) and inefficient (longer build times, larger images, lower layer cache hit rate, ...).
For production use cases, we recommend that you derive our lean
image(s) and
add database support for the database you need.
On supporting different platforms (namely arm64 AND amd64)
Currently all automated builds are multi-platform, supporting both linux/arm64
and linux/amd64
. This enables higher level constructs like helm
and
docker compose
to point to these images and effectively be multi-platform
as well.
Pull requests and master builds
are one-image-per-platform so that they can be parallelized and the
build matrix for those is more sparse as we don't need to build every
build preset on every platform, and generally can be more selective here.
For those builds, we suffix tags with -arm
where it applies.
Working with Apple silicon
Apple's current generation of computers uses ARM-based CPUs, and Docker
running on MACs seem to require linux/arm64/v8
(at least one user's M2 was
configured in that way). Setting the environment
variable DOCKER_DEFAULT_PLATFORM
to linux/amd64
seems to function in
term of leveraging, and building upon the Superset builds provided here.
export DOCKER_DEFAULT_PLATFORM=linux/amd64
Presumably, linux/arm64/v8
would be more optimized for this generation
of chips, but less compatible across the ARM ecosystem.