Ownership

Why Would You Use 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: create or update users and groups.
• Read: read owners attached to a dataset.
• Add: add user group as an owner to a dataset.
• Remove: remove the owner from a dataset.

Pre-requisites

For this tutorial, you need to deploy DataHub Quickstart and ingest sample data. For detailed information, please refer to Datahub Quickstart Guide.

note

In this guide, ingesting sample data is optional.

Upsert Users

CLI

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.

Python

# Inlined from /metadata-ingestion/examples/library/upsert_user.py
import logging

from datahub.api.entities.corpuser.corpuser import CorpUser, CorpUserGenerationConfig
from datahub.ingestion.graph.client import DataHubGraph, DataHubGraphConfig

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

user_email = "bar@acryl.io"

user: CorpUser = CorpUser(
    id=user_email,
    display_name="The Bar",
    email=user_email,
    title="Software Engineer",
    first_name="The",
    last_name="Bar",
    full_name="The Bar",
)

# Create graph client
datahub_graph = DataHubGraph(DataHubGraphConfig(server="http://localhost:8080"))
for event in user.generate_mcp(
    generation_config=CorpUserGenerationConfig(override_editable=False)
):
    datahub_graph.emit(event)
log.info(f"Upserted user {user.urn}")

Expected Outcomes of Upserting User

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

Upsert Group

CLI

Save this group.yaml as a local file. Note that the group includes a list of users who are 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
owners:
  - 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.

Python

# Inlined from /metadata-ingestion/examples/library/upsert_group.py
import logging

from datahub.api.entities.corpgroup.corpgroup import (
    CorpGroup,
    CorpGroupGenerationConfig,
)
from datahub.ingestion.graph.client import DataHubGraph, DataHubGraphConfig
from datahub.metadata.urns import CorpUserUrn

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

group_email = "foogroup@acryl.io"
group = CorpGroup(
    id=group_email,
    owners=[str(CorpUserUrn("datahub"))],
    members=[
        str(CorpUserUrn("bar@acryl.io")),
        str(CorpUserUrn("joe@acryl.io")),
    ],
    display_name="Foo Group",
    email=group_email,
    description="Software engineering team",
    slack="@foogroup",
)

# Create graph client
datahub_graph = DataHubGraph(DataHubGraphConfig(server="http://localhost:8080"))

for event in group.generate_mcp(
    generation_config=CorpGroupGenerationConfig(
        override_editable=False, datahub_graph=datahub_graph
    )
):
    datahub_graph.emit(event)
log.info(f"Upserted group {group.urn}")

Expected Outcomes of Upserting Group

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

Read Owners

GraphQL

query {
  dataset(urn: "urn:li:dataset:(urn:li:dataPlatform:hive,SampleHiveDataset,PROD)") {
    ownership {
      owners {
        owner {
          ... on CorpUser {
            urn
            type
          }
          ... on CorpGroup {
            urn
            type
          }
        }
      }
    }
  }
}

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

{
  "data": {
    "dataset": {
      "ownership": {
        "owners": [
          {
            "owner": {
              "urn": "urn:li:corpuser:jdoe",
              "type": "CORP_USER"
            }
          },
          {
            "owner": {
              "urn": "urn:li:corpuser:datahub",
              "type": "CORP_USER"
            }
          }
        ]
      }
    }
  },
  "extensions": {}
}

Curl

curl --location --request POST 'http://localhost:8080/api/graphql' \
--header 'Authorization: Bearer <my-access-token>' \
--header 'Content-Type: application/json' \
--data-raw '{ "query": "{ dataset(urn: \"urn:li:dataset:(urn:li:dataPlatform:hive,SampleHiveDataset,PROD)\") { ownership { owners { owner { ... on CorpUser { urn type } ... on CorpGroup { urn type } } } } } }", "variables":{}}'

Expected Response:

{
  "data": {
    "dataset": {
      "ownership": {
        "owners": [
          { "owner": { "urn": "urn:li:corpuser:jdoe", "type": "CORP_USER" } },
          { "owner": { "urn": "urn:li:corpuser:datahub", "type": "CORP_USER" } }
        ]
      }
    }
  },
  "extensions": {}
}

Python

# Inlined from /metadata-ingestion/examples/library/dataset_query_owners.py
from datahub.emitter.mce_builder import make_dataset_urn

# read-modify-write requires access to the DataHubGraph (RestEmitter is not enough)
from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph

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

dataset_urn = make_dataset_urn(platform="hive", name="SampleHiveDataset", env="PROD")

gms_endpoint = "http://localhost:8080"
graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint))

# Query multiple aspects from entity
result = graph.get_aspects_for_entity(
    entity_urn=dataset_urn,
    aspects=["ownership"],
    aspect_types=[OwnershipClass],
)

print(result)

Add Owners

GraphQL

mutation addOwners {
    addOwner(
      input: {
        ownerUrn: "urn:li:corpGroup:bfoo",
        resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)",
        ownerEntityType: CORP_GROUP,
        type: TECHNICAL_OWNER
            }
    )
}

Expected Response:

{
  "data": {
    "addOwner": true
  },
  "extensions": {}
}

Curl

curl --location --request POST 'http://localhost:8080/api/graphql' \
--header 'Authorization: Bearer <my-access-token>' \
--header 'Content-Type: application/json' \
--data-raw '{ "query": "mutation addOwners { addOwner(input: { ownerUrn: \"urn:li:corpGroup:bfoo\", resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)\", ownerEntityType: CORP_GROUP, type: TECHNICAL_OWNER }) }", "variables":{}}'

Python

# Inlined from /metadata-ingestion/examples/library/dataset_add_owner.py
import logging
from typing import Optional

from datahub.emitter.mce_builder import make_dataset_urn, make_user_urn
from datahub.emitter.mcp import MetadataChangeProposalWrapper

# read-modify-write requires access to the DataHubGraph (RestEmitter is not enough)
from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph

# Imports for metadata model classes
from datahub.metadata.schema_classes import (
    OwnerClass,
    OwnershipClass,
    OwnershipTypeClass,
)

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


# Inputs -> owner, ownership_type, dataset
owner_to_add = make_user_urn("jdoe")
ownership_type = OwnershipTypeClass.TECHNICAL_OWNER
dataset_urn = make_dataset_urn(platform="hive", name="realestate_db.sales", env="PROD")

# Some objects to help with conditional pathways later
owner_class_to_add = OwnerClass(owner=owner_to_add, type=ownership_type)
ownership_to_add = OwnershipClass(owners=[owner_class_to_add])


# First we get the current owners
gms_endpoint = "http://localhost:8080"
graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint))


current_owners: Optional[OwnershipClass] = graph.get_aspect(
    entity_urn=dataset_urn, aspect_type=OwnershipClass
)


need_write = False
if current_owners:
    if (owner_to_add, ownership_type) not in [
        (x.owner, x.type) for x in current_owners.owners
    ]:
        # owners exist, but this owner is not present in the current owners
        current_owners.owners.append(owner_class_to_add)
        need_write = True
else:
    # create a brand new ownership aspect
    current_owners = ownership_to_add
    need_write = True

if need_write:
    event: MetadataChangeProposalWrapper = MetadataChangeProposalWrapper(
        entityUrn=dataset_urn,
        aspect=current_owners,
    )
    graph.emit(event)
    log.info(
        f"Owner {owner_to_add}, type {ownership_type} added to dataset {dataset_urn}"
    )

else:
    log.info(f"Owner {owner_to_add} already exists, omitting write")

Expected Outcomes of Adding Owner

You can now see bfoo has been added as an owner to the fct_users_created dataset.

Remove Owners

GraphQL

mutation removeOwners {
    removeOwner(
      input: {
        ownerUrn: "urn:li:corpuser:jdoe",
        resourceUrn: "urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)",
            }
    )
}

Note that you can also remove owners from multiple entities or subresource using batchRemoveOwners.

mutation batchRemoveOwners {
    batchRemoveOwners(
      input: {
        ownerUrns: ["urn:li:corpuser:jdoe"],
        resources: [
          { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)"} ,
          { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)"} ,]
      }
    )
}

Expected Response:

{
  "data": {
    "removeOwner": true
  },
  "extensions": {}
}

Curl

curl --location --request POST 'http://localhost:8080/api/graphql' \
--header 'Authorization: Bearer <my-access-token>' \
--header 'Content-Type: application/json' \
--data-raw '{ "query": "mutation removeOwner { removeOwner(input: { ownerUrn: \"urn:li:corpuser:jdoe\", resourceUrn: \"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)\" }) }", "variables":{}}'

Python

# Inlined from /metadata-ingestion/examples/library/dataset_remove_owner_execute_graphql.py
# read-modify-write requires access to the DataHubGraph (RestEmitter is not enough)
from datahub.ingestion.graph.client import DatahubClientConfig, DataHubGraph

gms_endpoint = "http://localhost:8080"
graph = DataHubGraph(DatahubClientConfig(server=gms_endpoint))

# Query multiple aspects from entity
query = """
mutation batchRemoveOwners {
    batchRemoveOwners(
      input: {
        ownerUrns: ["urn:li:corpuser:jdoe"],
        resources: [
          { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hdfs,SampleHdfsDataset,PROD)"} ,
          { resourceUrn:"urn:li:dataset:(urn:li:dataPlatform:hive,fct_users_created,PROD)"} ,]
      }
    )
}
"""
result = graph.execute_graphql(query=query)

print(result)

Expected Outcomes of Removing Owners

You can now see John Doe has been removed as an owner from the fct_users_created dataset.