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_properties
optional - map from string to string -
annotations
optional - list of string -
compression_codec
optional - string -
compression_level
optional - string -
data_factory_name
required - string -
description
optional - string -
folder
optional - string -
id
optional computed - string -
linked_service_name
required - string -
name
required - string -
parameters
optional - map from string to string -
resource_group_name
required - string -
azure_blob_storage_location
list block -
http_server_location
list block-
filename
required - string -
path
required - string -
relative_url
required - string
-
-
schema_column
list block-
description
optional - string -
name
required - string -
type
optional - string
-
-
timeouts
single 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
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