This example shows how to create a Data Profiling scan. To create an Data Profiling scan, provide the `data_profile_spec` input arguments as documented in <https://cloud.google.com/dataplex/docs/reference/rest/v1/DataProfileSpec>.
To create an Data Quality scan, provide the `data_quality_spec` input arguments as documented in <https://cloud.google.com/dataplex/docs/reference/rest/v1/DataQualitySpec>.
Documentation for the supported rule types and rule specifications can be found in <https://cloud.example.com/dataplex/docs/reference/rest/v1/DataQualityRule>.
This example shows how you can pass the rules configurations as a separate YAML file into the module. This should produce the same DataScan configuration as the previous example.
sql_expression: footprint_length > 0 AND footprint_length <= 10
- dimension: VALIDITY
table_condition_expectation:
sql_expression: COUNT(*) > 0
```
While the module only accepts input in snake_case, the YAML file provided to the `data_quality_spec_file` variable can use either camelCase or snake_case. This example below should also produce the same DataScan configuration as the previous examples.
-`entity`: The Dataplex entity that represents the data source (e.g. BigQuery table) for DataScan, of the form: `projects/{project_number}/locations/{locationId}/lakes/{lakeId}/zones/{zoneId}/entities/{entityId}`.
-`resource`: The service-qualified full resource name of the cloud resource for a DataScan job to scan against. The field could be: BigQuery table of type "TABLE" for DataProfileScan/DataQualityScan format, e.g: `//bigquery.googleapis.com/projects/PROJECT_ID/datasets/DATASET_ID/tables/TABLE_ID`.
The authoritative and additive approaches can be used together, provided different roles are managed by each. Some care must also be taken with the `iam_by_principals` variable to ensure that variable keys are static values, so that Terraform is able to compute the dependency graph.
An example is provided below for using some of these variables. Refer to the [project module](../project/README.md#iam) for complete examples of the IAM interface.
| name | description | type | required | default |
|---|---|:---:|:---:|:---:|
| [data](variables.tf#L17) | The data source for DataScan. The source can be either a Dataplex `entity` or a BigQuery `resource`. | <codetitle="object({ entity = optional(string) resource = optional(string) })">object({…})</code> | ✓ | |
| [execution_schedule](variables.tf#L91) | Schedule DataScan to run periodically based on a cron schedule expression. If not specified, the DataScan is created with `on_demand` schedule, which means it will not run until the user calls `dataScans.run` API. | <code>string</code> | | <code>null</code> |
| [factories_config](variables.tf#L97) | Paths to data files and folders that enable factory functionality. | <codetitle="object({ data_quality_spec = optional(string) })">object({…})</code> | | <code>{}</code> |
| [iam](variables-iam.tf#L24) | Dataplex DataScan IAM bindings in {ROLE => [MEMBERS]} format. | <code>map(list(string))</code> | | <code>{}</code> |
| [iam_bindings](variables-iam.tf#L31) | Authoritative IAM bindings in {KEY => {role = ROLE, members = [], condition = {}}}. Keys are arbitrary. | <codetitle="map(object({ members = list(string) role = string condition = optional(object({ expression = string title = string description = optional(string) })) }))">map(object({…}))</code> | | <code>{}</code> |
| [iam_bindings_additive](variables-iam.tf#L46) | Individual additive IAM bindings. Keys are arbitrary. | <codetitle="map(object({ member = string role = string condition = optional(object({ expression = string title = string description = optional(string) })) }))">map(object({…}))</code> | | <code>{}</code> |
| [iam_by_principals](variables-iam.tf#L17) | Authoritative IAM binding in {PRINCIPAL => [ROLES]} format. Principals need to be statically defined to avoid cycle errors. Merged internally with the `iam` variable. | <code>map(list(string))</code> | | <code>{}</code> |
| [incremental_field](variables.tf#L106) | The unnested field (of type Date or Timestamp) that contains values which monotonically increase over time. If not specified, a data scan will run for all data in the table. | <code>string</code> | | <code>null</code> |
| [id](outputs.tf#L22) | A fully qualified Dataplex DataScan identifier for the resource with format projects/{{project}}/locations/{{location}}/dataScans/{{data_scan_id}}. | |
| [name](outputs.tf#L27) | The relative resource name of the scan, of the form: projects/{project}/locations/{locationId}/dataScans/{datascan_id}, where project refers to a project_id or project_number and locationId refers to a GCP region. | |
| [type](outputs.tf#L32) | The type of DataScan. | |
