Azure Data Factory Dataset Parquet
This page shows how to write Terraform and Azure Resource Manager for Data Factory Dataset Parquet and write them securely.
azurerm_data_factory_dataset_parquet (Terraform)
The Dataset Parquet in Data Factory can be configured in Terraform with the resource name azurerm_data_factory_dataset_parquet. 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
-
additional_propertiesoptional - map from string to string -
annotationsoptional - list of string -
compression_codecoptional - string -
compression_leveloptional - string -
data_factory_namerequired - string -
descriptionoptional - string -
folderoptional - string -
idoptional computed - string -
linked_service_namerequired - string -
namerequired - string -
parametersoptional - map from string to string -
resource_group_namerequired - string -
azure_blob_storage_locationlist block -
http_server_locationlist block-
filenamerequired - string -
pathrequired - string -
relative_urlrequired - string
-
-
schema_columnlist block-
descriptionoptional - string -
namerequired - string -
typeoptional - string
-
-
timeoutssingle block
Explanation in Terraform Registry
Manages an Azure Parquet Dataset inside an Azure Data Factory.
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
apiVersionrequired - stringnamerequired - stringThe dataset name.
propertiesrequiredadditionalPropertiesoptional - objectUnmatched properties from the message are deserialized this collection
annotationsoptional - arrayList of tags that can be used for describing the Dataset.
descriptionoptional - stringDataset description.
folderoptionalnameoptional - stringThe name of the folder that this Dataset is in.
linkedServiceNamerequiredparametersoptional - objectAn object mapping parameter names to argument values.
referenceNamerequired - stringReference LinkedService name.
typerequired - stringLinked service reference type.
parametersoptional - undefinedDefinition of all parameters for an entity.
schemaoptional - objectColumns that define the physical type schema of the dataset. Type: array (or Expression with resultType array), itemType: DatasetSchemaDataElement.
structureoptional - objectColumns that define the structure of the dataset. Type: array (or Expression with resultType array), itemType: DatasetDataElement.
typerequired - string