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Azure Data Factory Dataset Snowflake

This page shows how to write Terraform and Azure Resource Manager for Data Factory Dataset Snowflake and write them securely.

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azurerm_data_factory_dataset_snowflake (Terraform)

The Dataset Snowflake in Data Factory can be configured in Terraform with the resource name azurerm_data_factory_dataset_snowflake. The following sections describe how to use the resource and its parameters.

Example Usage from GitHub

An example could not be found in GitHub.

Review your Terraform file for Azure best practices

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Parameters

The following arguments are supported:

  • name - (Required) Specifies the name of the Data Factory Dataset Snowflake. Changing this forces a new resource to be created. Must be globally unique. See the Microsoft documentation for all restrictions.

  • resource_group_name - (Required) The name of the resource group in which to create the Data Factory Dataset Snowflake. Changing this forces a new resource

  • data_factory_name - (Required) The Data Factory name in which to associate the Dataset with. Changing this forces a new resource.

  • linked_service_name - (Required) The Data Factory Linked Service name in which to associate the Dataset with.

  • schema_name - (Optional) The schema name of the Data Factory Dataset Snowflake.

  • table_name - (Optional) The table name of the Data Factory Dataset Snowflake.

  • folder - (Optional) The folder that this Dataset is in. If not specified, the Dataset will appear at the root level.

  • schema_column - (Optional) A schema_column block as defined below.

  • description - (Optional) The description for the Data Factory Dataset Snowflake.

  • annotations - (Optional) List of tags that can be used for describing the Data Factory Dataset Snowflake.

  • parameters - (Optional) A map of parameters to associate with the Data Factory Dataset Snowflake.

  • additional_properties - (Optional) A map of additional properties to associate with the Data Factory Dataset Snowflake.

NOTE: This block has been deprecated in favour of the schema_column.

A structure_column block supports the following (Conflicts with schema_column):

  • name - (Required) The name of the column.

  • type - (Optional) Type of the column. Valid values are Byte, Byte[], Boolean, Date, DateTime,DateTimeOffset, Decimal, Double, Guid, Int16, Int32, Int64, Single, String, TimeSpan. Please note these values are case sensitive.

  • description - (Optional) The description of the column.

A schema_column block supports the following (Conflicts with structure_column):

  • name - (Required) The name of the column.

  • type - (Optional) Type of the column. Valid values are NUMBER, DECIMAL, NUMERIC, INT, INTEGER, BIGINT, SMALLINT, FLOAT``FLOAT4, FLOAT8, DOUBLE, DOUBLE PRECISION, REAL, VARCHAR, CHAR, CHARACTER, STRING, TEXT, BINARY, VARBINARY, BOOLEAN, DATE, DATETIME, TIME, TIMESTAMP, TIMESTAMP_LTZ, TIMESTAMP_NTZ, TIMESTAMP_TZ, VARIANT, OBJECT, ARRAY, GEOGRAPHY. Please note these values are case sensitive.

  • precision - (Optional) The total number of digits allowed.

  • scale - (Optional) The number of digits allowed to the right of the decimal point.

The following attributes are exported:

  • id - The ID of the Data Factory Snowflake Dataset.

>> from Terraform Registry

Explanation in Terraform Registry

Manages a Snowflake Dataset inside an Azure Data Factory.

>> from Terraform Registry

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.

risk-label

azurerm_data_factory

Ensure to disable public access

It is better to disable public access for Data Factory, which is enabled as default.

Review your Azure Data Factory settings

In addition to the above, there are other security points you should be aware of making sure that your .tf files are protected in Shisho Cloud.

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 - string
  • name required - string

    The dataset name.

  • properties required
      • additionalProperties optional - object

        Unmatched properties from the message are deserialized this collection

      • annotations optional - array

        List of tags that can be used for describing the Dataset.

      • description optional - string

        Dataset description.

      • folder optional
          • name optional - string

            The name of the folder that this Dataset is in.

      • linkedServiceName required
          • parameters optional - object

            An object mapping parameter names to argument values.

          • referenceName required - string

            Reference LinkedService name.

          • type required - string

            Linked service reference type.

      • parameters optional - undefined

        Definition of all parameters for an entity.

      • schema optional - object

        Columns that define the physical type schema of the dataset. Type: array (or Expression with resultType array), itemType: DatasetSchemaDataElement.

      • structure optional - object

        Columns that define the structure of the dataset. Type: array (or Expression with resultType array), itemType: DatasetDataElement.

  • type required - string

>> from Azure Resource Manager Documentation

The Other Related Azure Data Factory Resources

Frequently asked questions

What is Azure Data Factory Dataset Snowflake?

Azure Data Factory Dataset Snowflake is a resource for Data Factory of Microsoft Azure. Settings can be wrote in Terraform.

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