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Microsoft.MachineLearningServices workspaces/datasets 2020-05-01-preview

  • Article

Bicep resource definition

The workspaces/datasets resource type can be deployed with operations that target:

For a list of changed properties in each API version, see change log.

Resource format

To create a Microsoft.MachineLearningServices/workspaces/datasets resource, add the following Bicep to your template.

resource symbolicname 'Microsoft.MachineLearningServices/workspaces/datasets@2020-05-01-preview' = {
  datasetType: 'string'
  name: 'string'
  parameters: {
    header: 'string'
    includePath: bool
    partitionFormat: 'string'
    path: {
      dataPath: {
        datastoreName: 'string'
        relativePath: 'string'
      }
      httpUrl: 'string'
    }
    query: {
      datastoreName: 'string'
      query: 'string'
    }
    separator: 'string'
    sourceType: 'string'
  }
  registration: {
    description: 'string'
    name: 'string'
    tags: {
      {customized property}: 'string'
    }
  }
  skipValidation: bool
  timeSeries: {
    coarseGrainTimestamp: 'string'
    fineGrainTimestamp: 'string'
  }
}

Property values

DatasetCreateRequestParameters

Name Description Value
header Header type. 'all_files_have_same_headers'
'combine_all_files_headers'
'no_headers'
'only_first_file_has_headers'
includePath Boolean to keep path information as column in the dataset. Defaults to False. This is useful when reading multiple files, and want to know which file a particular record originated from, or to keep useful information in file path. bool
partitionFormat The partition information of each path will be extracted into columns based on the specified format. Format part '{column_name}' creates string column, and '{column_name:yyyy/MM/dd/HH/mm/ss}' creates datetime column, where 'yyyy', 'MM', 'dd', 'HH', 'mm' and 'ss' are used to extract year, month, day, hour, minute and second for the datetime type. The format should start from the position of first partition key until the end of file path. For example, given the path '../USA/2019/01/01/data.parquet' where the partition is by country/region and time, partition_format='/{CountryOrRegion}/{PartitionDate:yyyy/MM/dd}/data.csv' creates a string column 'CountryOrRegion' with the value 'USA' and a datetime column 'PartitionDate' with the value '2019-01-01 string
path DatasetCreateRequestParametersPath
query DatasetCreateRequestParametersQuery
separator The separator used to split columns for 'delimited_files' sourceType. string
sourceType Data source type. 'delimited_files'
'json_lines_files'
'parquet_files'

DatasetCreateRequestParametersPath

Name Description Value
dataPath DatasetCreateRequestParametersPathDataPath
httpUrl The Http URL. string

DatasetCreateRequestParametersPathDataPath

Name Description Value
datastoreName The datastore name. string
relativePath Path within the datastore. string

DatasetCreateRequestParametersQuery

Name Description Value
datastoreName The SQL/PostgreSQL/MySQL datastore name. string
query SQL Quey. string

DatasetCreateRequestRegistration

Name Description Value
description The description for the dataset. string
name The name of the dataset. string
tags Tags associated with the dataset. DatasetCreateRequestRegistrationTags

DatasetCreateRequestRegistrationTags

Name Description Value

DatasetCreateRequestTimeSeries

Name Description Value
coarseGrainTimestamp Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'. string
fineGrainTimestamp Column name to be used as FineGrainTimestamp string

Microsoft.MachineLearningServices/workspaces/datasets

Name Description Value
datasetType Specifies dataset type. 'file'
'tabular' (required)
name The resource name string (required)
parameters DatasetCreateRequestParameters (required)
parent In Bicep, you can specify the parent resource for a child resource. You only need to add this property when the child resource is declared outside of the parent resource.

For more information, see Child resource outside parent resource.		 Symbolic name for resource of type: workspaces
registration DatasetCreateRequestRegistration (required)
skipValidation Skip validation that ensures data can be loaded from the dataset before registration. bool
timeSeries DatasetCreateRequestTimeSeries

ARM template resource definition

The workspaces/datasets resource type can be deployed with operations that target:

For a list of changed properties in each API version, see change log.

Resource format

To create a Microsoft.MachineLearningServices/workspaces/datasets resource, add the following JSON to your template.

{
  "type": "Microsoft.MachineLearningServices/workspaces/datasets",
  "apiVersion": "2020-05-01-preview",
  "name": "string",
  "datasetType": "string",
  "parameters": {
    "header": "string",
    "includePath": "bool",
    "partitionFormat": "string",
    "path": {
      "dataPath": {
        "datastoreName": "string",
        "relativePath": "string"
      },
      "httpUrl": "string"
    },
    "query": {
      "datastoreName": "string",
      "query": "string"
    },
    "separator": "string",
    "sourceType": "string"
  },
  "registration": {
    "description": "string",
    "name": "string",
    "tags": {
      "{customized property}": "string"
    }
  },
  "skipValidation": "bool",
  "timeSeries": {
    "coarseGrainTimestamp": "string",
    "fineGrainTimestamp": "string"
  }
}

Property values

DatasetCreateRequestParameters

Name Description Value
header Header type. 'all_files_have_same_headers'
'combine_all_files_headers'
'no_headers'
'only_first_file_has_headers'
includePath Boolean to keep path information as column in the dataset. Defaults to False. This is useful when reading multiple files, and want to know which file a particular record originated from, or to keep useful information in file path. bool
partitionFormat The partition information of each path will be extracted into columns based on the specified format. Format part '{column_name}' creates string column, and '{column_name:yyyy/MM/dd/HH/mm/ss}' creates datetime column, where 'yyyy', 'MM', 'dd', 'HH', 'mm' and 'ss' are used to extract year, month, day, hour, minute and second for the datetime type. The format should start from the position of first partition key until the end of file path. For example, given the path '../USA/2019/01/01/data.parquet' where the partition is by country/region and time, partition_format='/{CountryOrRegion}/{PartitionDate:yyyy/MM/dd}/data.csv' creates a string column 'CountryOrRegion' with the value 'USA' and a datetime column 'PartitionDate' with the value '2019-01-01 string
path DatasetCreateRequestParametersPath
query DatasetCreateRequestParametersQuery
separator The separator used to split columns for 'delimited_files' sourceType. string
sourceType Data source type. 'delimited_files'
'json_lines_files'
'parquet_files'

DatasetCreateRequestParametersPath

Name Description Value
dataPath DatasetCreateRequestParametersPathDataPath
httpUrl The Http URL. string

DatasetCreateRequestParametersPathDataPath

Name Description Value
datastoreName The datastore name. string
relativePath Path within the datastore. string

DatasetCreateRequestParametersQuery

Name Description Value
datastoreName The SQL/PostgreSQL/MySQL datastore name. string
query SQL Quey. string

DatasetCreateRequestRegistration

Name Description Value
description The description for the dataset. string
name The name of the dataset. string
tags Tags associated with the dataset. DatasetCreateRequestRegistrationTags

DatasetCreateRequestRegistrationTags

Name Description Value

DatasetCreateRequestTimeSeries

Name Description Value
coarseGrainTimestamp Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'. string
fineGrainTimestamp Column name to be used as FineGrainTimestamp string

Microsoft.MachineLearningServices/workspaces/datasets

Name Description Value
apiVersion The api version '2020-05-01-preview'
datasetType Specifies dataset type. 'file'
'tabular' (required)
name The resource name string (required)
parameters DatasetCreateRequestParameters (required)
registration DatasetCreateRequestRegistration (required)
skipValidation Skip validation that ensures data can be loaded from the dataset before registration. bool
timeSeries DatasetCreateRequestTimeSeries
type The resource type 'Microsoft.MachineLearningServices/workspaces/datasets'

Quickstart templates

The following quickstart templates deploy this resource type.

Template Description
Create AML workspace with multiple Datasets & Datastores

Deploy to Azure		 This template creates Azure Machine Learning workspace with multiple datasets & datastores.
Create File Dataset from Relative Path in Datastore

Deploy to Azure		 This template creates a file dataset from relative path in datastore in Azure Machine Learning workspace.
Create File Dataset in AML workspace from Web URL

Deploy to Azure		 This template creates a file dataset from Web URL in Azure Machine Learning workspace.
Create Tabular Dataset from Relative Path in Datastore

Deploy to Azure		 This template creates a tabular dataset from relative path in datastore in Azure Machine Learning workspace.
Create Tabular Dataset from SQL/PostgreSQL/MySQL Datastore

Deploy to Azure		 This template creates a tabular dataset from SQL query in SQL/PostgreSQL/MySQL datastore in Azure Machine Learning workspace.
Create Tabular Dataset in AML workspace from Web URL

Deploy to Azure		 This template creates a tabular dataset from Web URL in Azure Machine Learning workspace.

Terraform (AzAPI provider) resource definition

The workspaces/datasets resource type can be deployed with operations that target:

  • Resource groups

For a list of changed properties in each API version, see change log.

Resource format

To create a Microsoft.MachineLearningServices/workspaces/datasets resource, add the following Terraform to your template.

resource "azapi_resource" "symbolicname" {
  type = "Microsoft.MachineLearningServices/workspaces/datasets@2020-05-01-preview"
  name = "string"
  datasetType = "string"
  parameters = {
    header = "string"
    includePath = bool
    partitionFormat = "string"
    path = {
      dataPath = {
        datastoreName = "string"
        relativePath = "string"
      }
      httpUrl = "string"
    }
    query = {
      datastoreName = "string"
      query = "string"
    }
    separator = "string"
    sourceType = "string"
  }
  registration = {
    description = "string"
    name = "string"
    tags = {
      {customized property} = "string"
    }
  }
  skipValidation = bool
  timeSeries = {
    coarseGrainTimestamp = "string"
    fineGrainTimestamp = "string"
  }
}

Property values

DatasetCreateRequestParameters

Name Description Value
header Header type. 'all_files_have_same_headers'
'combine_all_files_headers'
'no_headers'
'only_first_file_has_headers'
includePath Boolean to keep path information as column in the dataset. Defaults to False. This is useful when reading multiple files, and want to know which file a particular record originated from, or to keep useful information in file path. bool
partitionFormat The partition information of each path will be extracted into columns based on the specified format. Format part '{column_name}' creates string column, and '{column_name:yyyy/MM/dd/HH/mm/ss}' creates datetime column, where 'yyyy', 'MM', 'dd', 'HH', 'mm' and 'ss' are used to extract year, month, day, hour, minute and second for the datetime type. The format should start from the position of first partition key until the end of file path. For example, given the path '../USA/2019/01/01/data.parquet' where the partition is by country/region and time, partition_format='/{CountryOrRegion}/{PartitionDate:yyyy/MM/dd}/data.csv' creates a string column 'CountryOrRegion' with the value 'USA' and a datetime column 'PartitionDate' with the value '2019-01-01 string
path DatasetCreateRequestParametersPath
query DatasetCreateRequestParametersQuery
separator The separator used to split columns for 'delimited_files' sourceType. string
sourceType Data source type. 'delimited_files'
'json_lines_files'
'parquet_files'

DatasetCreateRequestParametersPath

Name Description Value
dataPath DatasetCreateRequestParametersPathDataPath
httpUrl The Http URL. string

DatasetCreateRequestParametersPathDataPath

Name Description Value
datastoreName The datastore name. string
relativePath Path within the datastore. string

DatasetCreateRequestParametersQuery

Name Description Value
datastoreName The SQL/PostgreSQL/MySQL datastore name. string
query SQL Quey. string

DatasetCreateRequestRegistration

Name Description Value
description The description for the dataset. string
name The name of the dataset. string
tags Tags associated with the dataset. DatasetCreateRequestRegistrationTags

DatasetCreateRequestRegistrationTags

Name Description Value

DatasetCreateRequestTimeSeries

Name Description Value
coarseGrainTimestamp Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'. string
fineGrainTimestamp Column name to be used as FineGrainTimestamp string

Microsoft.MachineLearningServices/workspaces/datasets

Name Description Value
datasetType Specifies dataset type. 'file'
'tabular' (required)
name The resource name string (required)
parameters DatasetCreateRequestParameters (required)
parent_id The ID of the resource that is the parent for this resource. ID for resource of type: workspaces
registration DatasetCreateRequestRegistration (required)
skipValidation Skip validation that ensures data can be loaded from the dataset before registration. bool
timeSeries DatasetCreateRequestTimeSeries
type The resource type "Microsoft.MachineLearningServices/workspaces/datasets@2020-05-01-preview"