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Creating or Updating Users And Groups

Why Would You Create or Update Users and Groups?​

Users and groups are essential for managing ownership of data. By creating or updating user accounts and assigning them to appropriate groups, administrators can ensure that the right people can access the data they need to do their jobs. This helps to avoid confusion or conflicts over who is responsible for specific datasets and can improve the overall effectiveness.

Goal Of This Guide​

This guide will show you how to create or update users and groups.

Pre-requisites​

For this tutorial, you need to deploy DataHub Quickstart and ingest sample data. For detailed information, please refer to Preparing Your Local DataHub Environment.

note

In this guide, ingesting sample data is optional.

Upsert Users And Groups With Datahub CLI​

You can ingest users and groups with yaml using Datahub CLI.

Upsert User​

Save this user.yaml as a local file.

- id: bar@acryl.io
  first_name: The
  last_name: Bar
  email: bar@acryl.io
  slack: "@the_bar_raiser"
  description: "I like raising the bar higher"
  groups:
    - foogroup@acryl.io
- id: datahub
  slack: "@datahubproject"
  phone: "1-800-GOT-META"
  description: "The DataHub Project"
  picture_link: "https://raw.githubusercontent.com/datahub-project/datahub/master/datahub-web-react/src/images/datahub-logo-color-stable.svg"

Execute the following CLI command to ingest user data. Since the user datahub already exists in the sample data, any updates made to the user information will overwrite the existing data.

datahub user upsert -f user.yaml

If you see the following logs, the operation was successful:

Update succeeded for urn urn:li:corpuser:bar@acryl.io.
Update succeeded for urn urn:li:corpuser:datahub.

Upsert Group​

Save this group.yaml as a local file. Note that the group includes a list of users who are admins (these will be marked as owners) and members. Within these lists, you can refer to the users by their ids or their urns, and can additionally specify their metadata inline within the group description itself. See the example below to understand how this works and feel free to make modifications to this file locally to see the effects of your changes in your local DataHub instance.

id: foogroup@acryl.io
display_name: Foo Group
admins:
  - datahub
members:
  - bar@acryl.io # refer to a user either by id or by urn
  - id: joe@acryl.io # inline specification of user
    slack: "@joe_shmoe"
    display_name: "Joe's Hub"

Execute the following CLI command to ingest this group's information. 

datahub group upsert -f group.yaml

If you see the following logs, the operation was successful:

Update succeeded for group urn:li:corpGroup:foogroup@acryl.io.

Upsert Users And Groups With Python SDK​

Upsert User​

The following code creates a user named The Bar with urn urn:li:corpuser:bar@acryl.io. You can refer to the full code in upsert_user.py.

import logging

from datahub.emitter.mce_builder import make_user_urn
from datahub.emitter.mcp import MetadataChangeProposalWrapper
from datahub.emitter.rest_emitter import DatahubRestEmitter

# Imports for metadata model classes
from datahub.metadata.schema_classes import CorpUserInfoClass

log = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)

user_urn = make_user_urn("bar@acryl.io")
event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper(
    entityUrn=user_urn,
    aspect=CorpUserInfoClass(
        active=True,
        displayName="The Bar",
        email="bar@acryl.io",
        title="Software Engineer",
        firstName="The",
        lastName="Bar",
        fullName="The Bar",
    ),
)

# Create rest emitter
rest_emitter = DatahubRestEmitter(gms_server="http://localhost:8080")
rest_emitter.emit(event)
log.info(f"Upserted user {user_urn}")

Upsert Group​

The following code creates a group called Foo Group with group urn:li:corpgroup:foogroup@acryl.io. You can refer to the full code in upsert_group.py.

import logging

from datahub.emitter.mce_builder import make_group_urn
from datahub.emitter.mcp import MetadataChangeProposalWrapper
from datahub.emitter.rest_emitter import DatahubRestEmitter

# Imports for metadata model classes
from datahub.metadata.schema_classes import CorpGroupInfoClass

log = logging.getLogger(__name__)
logging.basicConfig(level=logging.INFO)

group_urn = make_group_urn("foogroup@acryl.io")
event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper(
    entityUrn=group_urn,
    aspect=CorpGroupInfoClass(
        admins=["urn:li:corpuser:datahub"],
        members=["urn:li:corpuser:bar@acryl.io", "urn:li:corpuser:joe@acryl.io"],
        groups=[],
        displayName="Foo Group",
        email="foogroup@acryl.io",
        description="Software engineering team",
        slack="@foogroup",
    ),
)

# Create rest emitter
rest_emitter = DatahubRestEmitter(gms_server="http://localhost:8080")
rest_emitter.emit(event)
log.info(f"Upserted group {group_urn}")

We're using the MetdataChangeProposalWrapper to change entities in this example. For more information about the MetadataChangeProposal, please refer to MetadataChangeProposal & MetadataChangeLog Events

Expected Outcomes​

User​

You can see the user The bar has been created and the user Datahub has been updated under Settings > Access > Users & Groups user-upserted

Group​

You can see the group Foo Group has been created under Settings > Access > Users & Groups group-upserted

What's Next?​

Now that you created users and groups, how about adding them as an owner to a dataset? Here's a guide on how to add an owner on a dataset.