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DataHub Quickstart Guide

Deploying DataHub

To deploy a new instance of DataHub, perform the following steps.

  1. Install Docker and Docker Compose v2 for your platform.
note

Make sure to allocate enough hardware resources for Docker engine. Tested & confirmed config: 2 CPUs, 8GB RAM, 2GB Swap area, and 10GB disk space.

  1. Install jq

  2. Launch the Docker Engine from command line or the desktop app.

  3. Install the DataHub CLI

    a. Ensure you have Python 3.7+ installed & configured. (Check using python3 --version).

    b. Run the following commands in your terminal

    python3 -m pip install --upgrade pip wheel setuptools
    python3 -m pip uninstall datahub acryl-datahub || true # sanity check - ok if it fails
    python3 -m pip install --upgrade acryl-datahub
    datahub version
note

If you see "command not found", try running cli commands with the prefix 'python3 -m' instead like python3 -m datahub version Note that DataHub CLI does not support Python 2.x.

  1. To deploy a DataHub instance locally, run the following CLI command from your terminal

    datahub docker quickstart

    This will deploy a DataHub instance using docker-compose. If you are curious, the docker-compose.yaml file is downloaded to your home directory under the .datahub/quickstart directory.

    If things go well, you should see messages like the ones below:

    Fetching docker-compose file https://raw.githubusercontent.com/datahub-project/datahub/master/docker/quickstart/docker-compose-without-neo4j-m1.quickstart.yml from GitHub
    Pulling docker images...
    Finished pulling docker images!

    [+] Running 11/11
    ⠿ Container zookeeper Running 0.0s
    ⠿ Container elasticsearch Running 0.0s
    ⠿ Container broker Running 0.0s
    ⠿ Container schema-registry Running 0.0s
    ⠿ Container elasticsearch-setup Started 0.7s
    ⠿ Container kafka-setup Started 0.7s
    ⠿ Container mysql Running 0.0s
    ⠿ Container datahub-gms Running 0.0s
    ⠿ Container mysql-setup Started 0.7s
    ⠿ Container datahub-datahub-actions-1 Running 0.0s
    ⠿ Container datahub-frontend-react Running 0.0s
    .......
    ✔ DataHub is now running
    Ingest some demo data using `datahub docker ingest-sample-data`,
    or head to http://localhost:9002 (username: datahub, password: datahub) to play around with the frontend.
    Need support? Get in touch on Slack: https://slack.datahubproject.io/

    Upon completion of this step, you should be able to navigate to the DataHub UI at http://localhost:9002 in your browser. You can sign in using datahub as both the username and password.

note

On Mac computers with Apple Silicon (M1, M2 etc.), you might see an error like no matching manifest for linux/arm64/v8 in the manifest list entries, this typically means that the datahub cli was not able to detect that you are running it on Apple Silicon. To resolve this issue, override the default architecture detection by issuing datahub docker quickstart --arch m1

  1. To ingest the sample metadata, run the following CLI command from your terminal

    datahub docker ingest-sample-data
note

If you've enabled Metadata Service Authentication, you'll need to provide a Personal Access Token using the --token <token> parameter in the command.

That's it! Now feel free to play around with DataHub!

Troubleshooting Issues

Command not found: datahub

If running the datahub cli produces "command not found" errors inside your terminal, your system may be defaulting to an older version of Python. Try prefixing your datahub commands with python3 -m:

python3 -m datahub docker quickstart

Another possibility is that your system PATH does not include pip's $HOME/.local/bin directory. On linux, you can add this to your ~/.bashrc:

if [ -d "$HOME/.local/bin" ] ; then
PATH="$HOME/.local/bin:$PATH"
fi
Port Conflicts

By default the quickstart deploy will require the following ports to be free on your local machine:

  • 3306 for MySQL

  • 9200 for Elasticsearch

  • 9092 for the Kafka broker

  • 8081 for Schema Registry

  • 2181 for ZooKeeper

  • 9002 for the DataHub Web Application (datahub-frontend)

  • 8080 for the DataHub Metadata Service (datahub-gms)

    In case the default ports conflict with software you are already running on your machine, you can override these ports by passing additional flags to the datahub docker quickstart command. e.g. To override the MySQL port with 53306 (instead of the default 3306), you can say: datahub docker quickstart --mysql-port 53306. Use datahub docker quickstart --help to see all the supported options. For the metadata service container (datahub-gms), you need to use an environment variable, DATAHUB_MAPPED_GMS_PORT. So for instance to use the port 58080, you would say DATAHUB_MAPPED_GMS_PORT=58080 datahub docker quickstart

no matching manifest for linux/arm64/v8 in the manifest list entries
On Mac computers with Apple Silicon (M1, M2 etc.), you might see an error like `no matching manifest for linux/arm64/v8 in the manifest list entries`, this typically means that the datahub cli was not able to detect that you are running it on Apple Silicon. To resolve this issue, override the default architecture detection by issuing `datahub docker quickstart --arch m1`
Miscellaneous Docker issues
There can be misc issues with Docker, like conflicting containers and dangling volumes, that can often be resolved by pruning your Docker state with the following command. Note that this command removes all unused containers, networks, images (both dangling and unreferenced), and optionally, volumes.
docker system prune
Still stuck?

Hop over to our Slack community and ask for help in the #troubleshoot channel!

Next Steps

Ingest Metadata

To start pushing your company's metadata into DataHub, take a look at UI-based Ingestion Guide, or to run ingestion using the cli, look at the Metadata Ingestion Guide.

Invite Users

To add users to your deployment to share with your team check out our Adding Users to DataHub

Enable Authentication

To enable SSO, check out Configuring OIDC Authentication or Configuring JaaS Authentication.

To enable backend Authentication, check out [authentication in DataHub's backend](/docs/authentication/introducing-metadata-service-authentication#Configuring Metadata Service Authentication).

Move to Production

We recommend deploying DataHub to production using Kubernetes. We provide helpful Helm Charts to help you quickly get up and running. Check out Deploying DataHub to Kubernetes for a step-by-step walkthrough.

Other Common Operations

Stopping DataHub

To stop DataHub's quickstart, you can issue the following command.

datahub docker quickstart --stop

Resetting DataHub (a.k.a factory reset)

To cleanse DataHub of all of its state (e.g. before ingesting your own), you can use the CLI nuke command.

datahub docker nuke

Backing up your DataHub Quickstart (experimental)

The quickstart image is not recommended for use as a production instance. See Moving to production for recommendations on setting up your production cluster. However, in case you want to take a backup of your current quickstart state (e.g. you have a demo to your company coming up and you want to create a copy of the quickstart data so you can restore it at a future date), you can supply the --backup flag to quickstart.

datahub docker quickstart --backup

will take a backup of your MySQL image and write it by default to your ~/.datahub/quickstart/ directory as the file backup.sql. You can customize this by passing a --backup-file argument. e.g.

datahub docker quickstart --backup --backup-file /home/my_user/datahub_backups/quickstart_backup_2002_22_01.sql
note

Note that the Quickstart backup does not include any timeseries data (dataset statistics, profiles, etc.), so you will lose that information if you delete all your indexes and restore from this backup.

Restoring your DataHub Quickstart (experimental)

As you might imagine, these backups are restore-able. The following section describes a few different options you have to restore your backup.

Restoring a backup (primary + index) [most common]

To restore a previous backup, run the following command:

datahub docker quickstart --restore

This command will pick up the backup.sql file located under ~/.datahub/quickstart and restore your primary database as well as the elasticsearch indexes with it.

To supply a specific backup file, use the --restore-file option.

datahub docker quickstart --restore --restore-file /home/my_user/datahub_backups/quickstart_backup_2002_22_01.sql

Restoring only the index [to deal with index out of sync / corruption issues]

Another situation that can come up is the index can get corrupt, or be missing some update. In order to re-bootstrap the index from the primary store, you can run this command to sync the index with the primary store.

datahub docker quickstart --restore-indices

Restoring a backup (primary but NO index) [rarely used]

Sometimes, you might want to just restore the state of your primary database (MySQL), but not re-index the data. To do this, you have to explicitly disable the restore-indices capability.

datahub docker quickstart --restore --no-restore-indices

Upgrading your local DataHub

If you have been testing DataHub locally, a new version of DataHub got released and you want to try the new version then you can just issue the quickstart command again. It will pull down newer images and restart your instance without losing any data.

datahub docker quickstart

Customization

If you would like to customize the DataHub installation further, please download the docker-compose.yaml used by the cli tool, modify it as necessary and deploy DataHub by passing the downloaded docker-compose file:

datahub docker quickstart --quickstart-compose-file <path to compose file>