Provide extra resource access to Jobs and Data Labs

There are 2 ways of providing resources access to Jobs and Data Labs.

Note

To receive notifications about the status of resource access update, users must subscribe to notifications for that specific entity during the resource update action.

Resource access through API

Use the following API to provide datasets (read or write), parameters and shared libraries access to Jobs or Data Labs in large number.

Property	Description
resource_type	jobs, datalabs
resource_id	unique id (uuid) associated with the jobs or data labs
API Path	/{resource_type}/{resource_id}/resourceaccess
HTTP Method	POST

Input Body:

    {
        "DatasetAccess": {
            "Owner": [
                {
                    "DatasetId": "uuid",
                    "DatasetName": "dataset_name"
                },
                {
                    "DatasetId": "uuid2",
                    "DatasetName": "dataset_name2"
                }, ...
            ],
            "ReadOnly": [
                {
                    "DatasetId": "uuid3",
                    "DatasetName": "dataset_name3"
                },
                {
                    "DatasetId": "uuid4",
                    "DatasetName": "dataset_name4"
                }, ....
            ],
            "ReadOnly-FileLevel": [
                {
                    "DatasetId": "uuid5",
                    "DatasetName": "dataset_name5",
                    "FileLevelTags": [
                        {
                            "TagKey": "key",
                            "TagValue": "value"
                        },
                        {
                            "TagKey": "key1",
                            "TagValue": "value1"
                        }
                    ]
                }
            ]
        },
        "ParameterAccess": ["param1", "param2"],
        "SharedLibraries": ["uuid_lib1", "uuid_lib2"]
    }

To retrieve the status of the latest resource update, use the GET HTTP method without input body. Output retrieved would be

    {
        "Status": "in_progress"/"failed"/"updated",
        "Message": "update failed because of some reason", # When it fails this will appear
        "ParameterAccess": ["param1", "param2"],
        "SharedLibraries": ["uuid_lib1", "uuid_lib2"]
        "DatasetAccess": {
            "ReadOnly": [{
                "DatasetId" : "uuid1",
                "DatasetName": "name1"
            }, ...],
            "Owner": [
            {
                "DatasetId" : "uuid2",
                "DatasetName": "name2"
            }
            ],
            "ReadOnly-FileLevel": [
                {
                    "DatasetId": "uuid5",
                    "DatasetName": "dataset_name5",
                    "FileLevelTags": [
                        {
                            "TagKey": "key",
                            "TagValue": "value"
                        },
                        {
                            "TagKey": "key1",
                            "TagValue": "value1"
                        }
                    ]
                }
            ]
        }
    }

Below image shows how the extra resources access provided are shown in User Interface

Resource access through UI

Provide datasets (read, read-only file-level, or write), parameters and shared libraries access in large number using the 'Update Extra Resource Access' button on the top right side of the details page.

Click on the 'Update Extra Resource Access' button and select the required resources from the dropdown and click 'Submit' to update the resource access.

Once the resource access is submitted, the extra resources will be updated and displayed in the details page eventually.

The following picture depicts how to update extra resources:

If the extra resources are not getting displayed then refresh the details page to view the extra resources.

User can also update the extra resources or remove them all again through the same process.

Note

All the extra resources added till that time will be displayed in the UI popup every time the popup is opened so that user can either remove or add accordingly.

Resource Limits

To comply with the character limit for IAM managed policies in AWS Roles, we recommend that the combined total of read and write access datasets not exceed 90. However, below are the independent hard limits on the resource allocation for Jobs and Data Labs:

Type	Limit
Datasets Read	100
Datasets Write	90
Shared Libraries	62
Parameters	35