Deprecated—use the app reference

This package is deprecated. Use the app reference for the new client.app builder, or see Manage apps.

MongoDB assets package

||Connect docs via MCP

The MongoDB assets package crawls MongoDB assets and publishes them to Atlan for discovery.

Direct extraction

Will create a new connection

This should only be used to create the workflow the first time. Each time you run this method it will create a new connection and new assets within that connection — which could lead to duplicate assets if you run the workflow this way multiple times with the same settings.

Instead, when you want to re-crawl assets, re-run the existing workflow (see Re-run existing workflow below).

To crawl assets directly from MongoDB:

Java

Coming soon

Python

Direct extraction from MongoDB

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.packages import MongoDBCrawler

client = AtlanClient()

crawler = (
    MongoDBCrawler( # (1)
        client=client,  # (2)
        connection_name="production", # (3)
        admin_roles=[client.role_cache.get_id_for_name("$admin")],  # (4)
        admin_groups=None,
        admin_users=None,
        row_limit=10000, # (5)
        allow_query=True, # (6)
        allow_query_preview=True, # (7)
    )
    .direct(hostname="test.host.mongodb.net", port=27017) # (8)
    .basic_auth( # (9)
        username="test-user",
        password="test-pass",
        native_host="test.native.mongodb.net",
        default_db="test-default-db",
        auth_db="test-auth-db",
        is_ssl=True,
    )
    .include(assets=["test-asset-1", "test-asset-2"]) # (10)
    .exclude(assets=["test-asset-1", "test-asset-2"]) # (11)
    .exclude_regex(regex="TEST*") # (12)
    .to_workflow() # (13)
)
response = client.workflow.run(crawler) # (14)

1. Base configuration for a new MongoDB crawler.

2. You must provide a client instance.

3. You must provide a name for the connection that the MongoDB assets will exist within.

4. You must specify at least one connection admin, either:

   • everyone in a role (in this example, all $admin users).
   • a list of groups (names) that will be connection admins.
   • a list of users (names) that will be connection admins.

5. You can specify a maximum number of rows that can be accessed for any asset in the connection. defaults to 10000.

6. You can specify whether you want to allow queries to this connection (default: True, as in this example) or deny all query access to the connection (False).

7. You can specify whether you want to allow data previews on this connection (default: True, as in this example) or deny all sample data previews to the connection (False).

8. When crawling assets directly from MongoDB, you are required to provide the following information:

   • hostname of the Atlas SQL connection.
   • port number of the Atlas SQL connection. default: 27017.

9. When using basic authentication, you are required to provide the following information:

   • username through which to access Atlas SQL connection.
   • password through which to access Atlas SQL connection.
   • native host address for the MongoDB connection.
   • default database to connect to.
   • authentication database to use (default: "admin").
   • whether to use SSL for the connection (default: True).

10. You can also optionally specify the list of assets to include in crawling. For MongoDB assets, this should be specified as a list of database names. If set to [], all databases will be crawled.

11. You can also optionally specify the list of assets to exclude from crawling. For MongoDB assets, this should be specified as a list of database GUIDs. If set to [], no databases will be excluded.

12. You can also optionally specify the exclude regex for the crawler to ignore collections based on a naming convention.

13. Now, you can convert the package into a Workflow object.

14. Run the workflow by invoking the run() method on the workflow client, passing the created object.

    Workflows run asynchronously

Remember that workflows run asynchronously. See the packages and workflows introduction for details on how you can check the status and wait until the workflow has been completed. :::

Kotlin

Coming soon

Raw REST API

Create the workflow via UI only

We recommend creating the workflow only via the UI. To rerun an existing workflow, see the steps below.

Re-run existing workflow

To re-run an existing workflow for MongoDB assets:

Java

Coming soon

Python

Re-run existing MongoDB workflow

from pyatlan.client.atlan import AtlanClient
from pyatlan.model.enums import WorkflowPackage

client = AtlanClient()

existing = client.workflow.find_by_type(  # (1)
  prefix=WorkflowPackage.MONGODB, max_results=5
)

# Determine which MongoDB workflow (n)
# from the list of results you want to re-run.
response = client.workflow.rerun(existing[n]) # (2)

1. You can find workflows by their type using the workflow client find_by_type() method and providing the prefix for one of the packages. In this example, we do so for the MongoDBCrawler. (You can also specify the maximum number of resulting workflows you want to retrieve as results.)

2. Once you've found the workflow you want to re-run, you can simply call the workflow client rerun() method.

   • Optionally, you can use rerun(idempotent=True) to avoid re-running a workflow that is already in running or in a pending state. This will return details of the already running workflow if found, and by default, it is set to False.
   Workflows run asynchronously

Remember that workflows run asynchronously. See the packages and workflows introduction for details on how you can check the status and wait until the workflow has been completed. :::

Kotlin

Coming soon

Raw REST API

Requires multiple steps through the raw REST API

1. Find the existing workflow.
2. Send through the resulting re-run request.

POST /api/service/workflows/indexsearch

{
  "from": 0,
  "size": 5,
  "query": {
    "bool": {
      "filter": [
        {
          "nested": {
            "path": "metadata",
            "query": {
              "prefix": {
                "metadata.name.keyword": {
                  "value": "atlan-mongodb" // (1)
                }
              }
            }
          }
        }
      ]
    }
  },
  "sort": [
    {
      "metadata.creationTimestamp": {
        "nested": {
          "path": "metadata"
        },
        "order": "desc"
      }
    }
  ],
  "track_total_hits": true
}

1. Searching by the atlan-mongodb prefix will ensure you only find existing MongoDB assets workflows.

   Name of the workflow

The name of the workflow will be nested within the _source.metadata.name property of the response object. (Remember since this is a search, there could be multiple results, so you may want to use the other details in each result to determine which workflow you really want.) :::

POST /api/service/workflows/submit

{
  "namespace": "default",
  "resourceKind": "WorkflowTemplate",
  "resourceName": "atlan-mongodb-1684500411" // (1)
}

1. Send the name of the workflow as the resourceName to rerun it.