Azure Data Factory Custom Dataset
This page shows how to write Terraform and Azure Resource Manager for Data Factory Custom Dataset and write them securely.
azurerm_data_factory_custom_dataset (Terraform)
The Custom Dataset in Data Factory can be configured in Terraform with the resource name azurerm_data_factory_custom_dataset
. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
Parameters
name
- (Required) Specifies the name of the Data Factory Dataset. Changing this forces a new resource to be created. Must be globally unique. See the Microsoft documentation for all restrictions.data_factory_id
- (Required) The Data Factory ID in which to associate the Dataset with. Changing this forces a new resource.linked_service
- (Required) Alinked_service
block as defined below.type
- (Required) The type of dataset that will be associated with Data Factory.type_properties_json
- (Required) A JSON object that contains the properties of the Data Factory Dataset.additional_properties
- (Optional) A map of additional properties to associate with the Data Factory Dataset.annotations
- (Optional) List of tags that can be used for describing the Data Factory Dataset.description
- (Optional) The description for the Data Factory Dataset.folder
- (Optional) The folder that this Dataset is in. If not specified, the Dataset will appear at the root level.parameters
- (Optional) A map of parameters to associate with the Data Factory Dataset.schema_json
- (Optional) A JSON object that contains the schema of the Data Factory Dataset.
A linked_service
block supports the following:
name
- (Required) The name of the Data Factory Linked Service.parameters
- (Optional) A map of parameters to associate with the Data Factory Linked Service.
The following attributes are exported:
id
- The ID of the Data Factory Dataset.
Explanation in Terraform Registry
Manages a Dataset inside an Azure Data Factory. This is a generic resource that supports all different Dataset Types.
Tips: Best Practices for The Other Azure Data Factory Resources
In addition to the azurerm_data_factory, Azure Data Factory has the other resources that should be configured for security reasons. Please check some examples of those resources and precautions.
azurerm_data_factory
Ensure to disable public access
It is better to disable public access for Data Factory, which is enabled as default.
Microsoft.DataFactory/factories/datasets (Azure Resource Manager)
The factories/datasets in Microsoft.DataFactory can be configured in Azure Resource Manager with the resource name Microsoft.DataFactory/factories/datasets
. The following sections describe how to use the resource and its parameters.
Example Usage from GitHub
An example could not be found in GitHub.
Parameters
apiVersion
required - stringname
required - stringThe dataset name.
properties
requiredadditionalProperties
optional - objectUnmatched properties from the message are deserialized this collection
annotations
optional - arrayList of tags that can be used for describing the Dataset.
description
optional - stringDataset description.
folder
optionalname
optional - stringThe name of the folder that this Dataset is in.
linkedServiceName
requiredparameters
optional - objectAn object mapping parameter names to argument values.
referenceName
required - stringReference LinkedService name.
type
required - stringLinked service reference type.
parameters
optional - undefinedDefinition of all parameters for an entity.
schema
optional - objectColumns that define the physical type schema of the dataset. Type: array (or Expression with resultType array), itemType: DatasetSchemaDataElement.
structure
optional - objectColumns that define the structure of the dataset. Type: array (or Expression with resultType array), itemType: DatasetDataElement.
type
required - string