Azure Native v2 v2.90.0, Mar 27 25

These are the docs for Azure Native v2. We recommenend using the latest version, Azure Native v3.

Azure Native v2 v2.90.0 published on Thursday, Mar 27, 2025 by Pulumi

azure-native-v2.machinelearningservices.MachineLearningDataset

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These are the docs for Azure Native v2. We recommenend using the latest version, Azure Native v3.

Azure Native v2 v2.90.0 published on Thursday, Mar 27, 2025 by Pulumi

pulumi/pulumi-azure-native

Create Dataset

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;

return await Deployment.RunAsync(() => 
{
    var machineLearningDataset = new AzureNative.MachineLearningServices.MachineLearningDataset("machineLearningDataset", new()
    {
        DatasetName = "datasetName123",
        DatasetType = AzureNative.MachineLearningServices.DatasetType.File,
        Parameters = new AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestParametersArgs
        {
            Path = new AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestPathArgs
            {
                DataPath = new AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestDataPathArgs
                {
                    DatastoreName = "testblobfromarm",
                    RelativePath = "UI/03-26-2020_083359_UTC/latin1encoding.csv",
                },
            },
        },
        Registration = new AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestRegistrationArgs
        {
            Description = "test description",
            Name = "datasetName123",
        },
        ResourceGroupName = "acjain-mleastUS2",
        SkipValidation = false,
        WorkspaceName = "acjain-mleastUS2",
    });

});

package main

import (
	machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := machinelearningservices.NewMachineLearningDataset(ctx, "machineLearningDataset", &machinelearningservices.MachineLearningDatasetArgs{
			DatasetName: pulumi.String("datasetName123"),
			DatasetType: pulumi.String(machinelearningservices.DatasetTypeFile),
			Parameters: &machinelearningservices.DatasetCreateRequestParametersArgs{
				Path: &machinelearningservices.DatasetCreateRequestPathArgs{
					DataPath: &machinelearningservices.DatasetCreateRequestDataPathArgs{
						DatastoreName: pulumi.String("testblobfromarm"),
						RelativePath:  pulumi.String("UI/03-26-2020_083359_UTC/latin1encoding.csv"),
					},
				},
			},
			Registration: &machinelearningservices.DatasetCreateRequestRegistrationArgs{
				Description: pulumi.String("test description"),
				Name:        pulumi.String("datasetName123"),
			},
			ResourceGroupName: pulumi.String("acjain-mleastUS2"),
			SkipValidation:    pulumi.Bool(false),
			WorkspaceName:     pulumi.String("acjain-mleastUS2"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.MachineLearningDataset;
import com.pulumi.azurenative.machinelearningservices.MachineLearningDatasetArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.DatasetCreateRequestParametersArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.DatasetCreateRequestPathArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.DatasetCreateRequestDataPathArgs;
import com.pulumi.azurenative.machinelearningservices.inputs.DatasetCreateRequestRegistrationArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var machineLearningDataset = new MachineLearningDataset("machineLearningDataset", MachineLearningDatasetArgs.builder()
            .datasetName("datasetName123")
            .datasetType("file")
            .parameters(DatasetCreateRequestParametersArgs.builder()
                .path(DatasetCreateRequestPathArgs.builder()
                    .dataPath(DatasetCreateRequestDataPathArgs.builder()
                        .datastoreName("testblobfromarm")
                        .relativePath("UI/03-26-2020_083359_UTC/latin1encoding.csv")
                        .build())
                    .build())
                .build())
            .registration(DatasetCreateRequestRegistrationArgs.builder()
                .description("test description")
                .name("datasetName123")
                .build())
            .resourceGroupName("acjain-mleastUS2")
            .skipValidation(false)
            .workspaceName("acjain-mleastUS2")
            .build());

    }
}

import * as pulumi from "@pulumi/pulumi";
import * as azure_native from "@pulumi/azure-native";

const machineLearningDataset = new azure_native.machinelearningservices.MachineLearningDataset("machineLearningDataset", {
    datasetName: "datasetName123",
    datasetType: azure_native.machinelearningservices.DatasetType.File,
    parameters: {
        path: {
            dataPath: {
                datastoreName: "testblobfromarm",
                relativePath: "UI/03-26-2020_083359_UTC/latin1encoding.csv",
            },
        },
    },
    registration: {
        description: "test description",
        name: "datasetName123",
    },
    resourceGroupName: "acjain-mleastUS2",
    skipValidation: false,
    workspaceName: "acjain-mleastUS2",
});

import pulumi
import pulumi_azure_native as azure_native

machine_learning_dataset = azure_native.machinelearningservices.MachineLearningDataset("machineLearningDataset",
    dataset_name="datasetName123",
    dataset_type=azure_native.machinelearningservices.DatasetType.FILE,
    parameters={
        "path": {
            "data_path": {
                "datastore_name": "testblobfromarm",
                "relative_path": "UI/03-26-2020_083359_UTC/latin1encoding.csv",
            },
        },
    },
    registration={
        "description": "test description",
        "name": "datasetName123",
    },
    resource_group_name="acjain-mleastUS2",
    skip_validation=False,
    workspace_name="acjain-mleastUS2")

resources:
  machineLearningDataset:
    type: azure-native:machinelearningservices:MachineLearningDataset
    properties:
      datasetName: datasetName123
      datasetType: file
      parameters:
        path:
          dataPath:
            datastoreName: testblobfromarm
            relativePath: UI/03-26-2020_083359_UTC/latin1encoding.csv
      registration:
        description: test description
        name: datasetName123
      resourceGroupName: acjain-mleastUS2
      skipValidation: false
      workspaceName: acjain-mleastUS2

Create MachineLearningDataset Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

TypeScript
Python
Go
C#
Java
YAML

new MachineLearningDataset(name: string, args: MachineLearningDatasetArgs, opts?: CustomResourceOptions);

@overload
def MachineLearningDataset(resource_name: str,
                           args: MachineLearningDatasetArgs,
                           opts: Optional[ResourceOptions] = None)

@overload
def MachineLearningDataset(resource_name: str,
                           opts: Optional[ResourceOptions] = None,
                           dataset_type: Optional[Union[str, DatasetType]] = None,
                           parameters: Optional[DatasetCreateRequestParametersArgs] = None,
                           registration: Optional[DatasetCreateRequestRegistrationArgs] = None,
                           resource_group_name: Optional[str] = None,
                           workspace_name: Optional[str] = None,
                           dataset_name: Optional[str] = None,
                           skip_validation: Optional[bool] = None,
                           time_series: Optional[DatasetCreateRequestTimeSeriesArgs] = None)

func NewMachineLearningDataset(ctx *Context, name string, args MachineLearningDatasetArgs, opts ...ResourceOption) (*MachineLearningDataset, error)

public MachineLearningDataset(string name, MachineLearningDatasetArgs args, CustomResourceOptions? opts = null)

public MachineLearningDataset(String name, MachineLearningDatasetArgs args)
public MachineLearningDataset(String name, MachineLearningDatasetArgs args, CustomResourceOptions options)

type: azure-native:machinelearningservices:MachineLearningDataset
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name string: The unique name of the resource.
args MachineLearningDatasetArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args MachineLearningDatasetArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args MachineLearningDatasetArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args MachineLearningDatasetArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args MachineLearningDatasetArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

TypeScript
Python
Go
C#
Java
YAML

var machineLearningDatasetResource = new AzureNative.Machinelearningservices.MachineLearningDataset("machineLearningDatasetResource", new()
{
    DatasetType = "string",
    Parameters = 
    {
        { "header", "string" },
        { "includePath", false },
        { "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", 
        {
            { "string", "string" },
        } },
    },
    ResourceGroupName = "string",
    WorkspaceName = "string",
    DatasetName = "string",
    SkipValidation = false,
    TimeSeries = 
    {
        { "coarseGrainTimestamp", "string" },
        { "fineGrainTimestamp", "string" },
    },
});

example, err := machinelearningservices.NewMachineLearningDataset(ctx, "machineLearningDatasetResource", &machinelearningservices.MachineLearningDatasetArgs{
	DatasetType: "string",
	Parameters: map[string]interface{}{
		"header":          "string",
		"includePath":     false,
		"partitionFormat": "string",
		"path": map[string]interface{}{
			"dataPath": map[string]interface{}{
				"datastoreName": "string",
				"relativePath":  "string",
			},
			"httpUrl": "string",
		},
		"query": map[string]interface{}{
			"datastoreName": "string",
			"query":         "string",
		},
		"separator":  "string",
		"sourceType": "string",
	},
	Registration: map[string]interface{}{
		"description": "string",
		"name":        "string",
		"tags": map[string]interface{}{
			"string": "string",
		},
	},
	ResourceGroupName: "string",
	WorkspaceName:     "string",
	DatasetName:       "string",
	SkipValidation:    false,
	TimeSeries: map[string]interface{}{
		"coarseGrainTimestamp": "string",
		"fineGrainTimestamp":   "string",
	},
})

var machineLearningDatasetResource = new MachineLearningDataset("machineLearningDatasetResource", MachineLearningDatasetArgs.builder()
    .datasetType("string")
    .parameters(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
    .registration(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
    .resourceGroupName("string")
    .workspaceName("string")
    .datasetName("string")
    .skipValidation(false)
    .timeSeries(%!v(PANIC=Format method: runtime error: invalid memory address or nil pointer dereference))
    .build());

machine_learning_dataset_resource = azure_native.machinelearningservices.MachineLearningDataset("machineLearningDatasetResource",
    dataset_type=string,
    parameters={
        header: string,
        includePath: False,
        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: {
            string: string,
        },
    },
    resource_group_name=string,
    workspace_name=string,
    dataset_name=string,
    skip_validation=False,
    time_series={
        coarseGrainTimestamp: string,
        fineGrainTimestamp: string,
    })

const machineLearningDatasetResource = new azure_native.machinelearningservices.MachineLearningDataset("machineLearningDatasetResource", {
    datasetType: "string",
    parameters: {
        header: "string",
        includePath: false,
        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: {
            string: "string",
        },
    },
    resourceGroupName: "string",
    workspaceName: "string",
    datasetName: "string",
    skipValidation: false,
    timeSeries: {
        coarseGrainTimestamp: "string",
        fineGrainTimestamp: "string",
    },
});

type: azure-native:machinelearningservices:MachineLearningDataset
properties:
    datasetName: string
    datasetType: string
    parameters:
        header: string
        includePath: false
        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:
            string: string
    resourceGroupName: string
    skipValidation: false
    timeSeries:
        coarseGrainTimestamp: string
        fineGrainTimestamp: string
    workspaceName: string

MachineLearningDataset Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The MachineLearningDataset resource accepts the following input properties:

DatasetType string | Pulumi.AzureNative.MachineLearningServices.DatasetType: Specifies dataset type.
Parameters Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestParameters
Registration Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestRegistration
ResourceGroupName string: Name of the resource group in which workspace is located.
WorkspaceName string: Name of Azure Machine Learning workspace.
DatasetName string: The Dataset name.
SkipValidation bool: Skip validation that ensures data can be loaded from the dataset before registration.
TimeSeries Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestTimeSeries

DatasetType string | DatasetType: Specifies dataset type.
Parameters DatasetCreateRequestParametersArgs
Registration DatasetCreateRequestRegistrationArgs
ResourceGroupName string: Name of the resource group in which workspace is located.
WorkspaceName string: Name of Azure Machine Learning workspace.
DatasetName string: The Dataset name.
SkipValidation bool: Skip validation that ensures data can be loaded from the dataset before registration.
TimeSeries DatasetCreateRequestTimeSeriesArgs

datasetType String | DatasetType: Specifies dataset type.
parameters DatasetCreateRequestParameters
registration DatasetCreateRequestRegistration
resourceGroupName String: Name of the resource group in which workspace is located.
workspaceName String: Name of Azure Machine Learning workspace.
datasetName String: The Dataset name.
skipValidation Boolean: Skip validation that ensures data can be loaded from the dataset before registration.
timeSeries DatasetCreateRequestTimeSeries

datasetType string | DatasetType: Specifies dataset type.
parameters DatasetCreateRequestParameters
registration DatasetCreateRequestRegistration
resourceGroupName string: Name of the resource group in which workspace is located.
workspaceName string: Name of Azure Machine Learning workspace.
datasetName string: The Dataset name.
skipValidation boolean: Skip validation that ensures data can be loaded from the dataset before registration.
timeSeries DatasetCreateRequestTimeSeries

dataset_type str | DatasetType: Specifies dataset type.
parameters DatasetCreateRequestParametersArgs
registration DatasetCreateRequestRegistrationArgs
resource_group_name str: Name of the resource group in which workspace is located.
workspace_name str: Name of Azure Machine Learning workspace.
dataset_name str: The Dataset name.
skip_validation bool: Skip validation that ensures data can be loaded from the dataset before registration.
time_series DatasetCreateRequestTimeSeriesArgs

datasetType String | "tabular" | "file": Specifies dataset type.
parameters Property Map
registration Property Map
resourceGroupName String: Name of the resource group in which workspace is located.
workspaceName String: Name of Azure Machine Learning workspace.
datasetName String: The Dataset name.
skipValidation Boolean: Skip validation that ensures data can be loaded from the dataset before registration.
timeSeries Property Map

Outputs

All input properties are implicitly available as output properties. Additionally, the MachineLearningDataset resource produces the following output properties:

Id string: The provider-assigned unique ID for this managed resource.
Name string: Specifies the name of the resource.
Properties Pulumi.AzureNative.MachineLearningServices.Outputs.DatasetResponse: Dataset properties
Type string: Specifies the type of the resource.
Identity Pulumi.AzureNative.MachineLearningServices.Outputs.IdentityResponse: The identity of the resource.
Location string: Specifies the location of the resource.
Sku Pulumi.AzureNative.MachineLearningServices.Outputs.SkuResponse: The sku of the workspace.
Tags Dictionary<string, string>: Contains resource tags defined as key/value pairs.

Id string: The provider-assigned unique ID for this managed resource.
Name string: Specifies the name of the resource.
Properties DatasetResponse: Dataset properties
Type string: Specifies the type of the resource.
Identity IdentityResponse: The identity of the resource.
Location string: Specifies the location of the resource.
Sku SkuResponse: The sku of the workspace.
Tags map[string]string: Contains resource tags defined as key/value pairs.

id String: The provider-assigned unique ID for this managed resource.
name String: Specifies the name of the resource.
properties DatasetResponse: Dataset properties
type String: Specifies the type of the resource.
identity IdentityResponse: The identity of the resource.
location String: Specifies the location of the resource.
sku SkuResponse: The sku of the workspace.
tags Map<String,String>: Contains resource tags defined as key/value pairs.

id string: The provider-assigned unique ID for this managed resource.
name string: Specifies the name of the resource.
properties DatasetResponse: Dataset properties
type string: Specifies the type of the resource.
identity IdentityResponse: The identity of the resource.
location string: Specifies the location of the resource.
sku SkuResponse: The sku of the workspace.
tags {[key: string]: string}: Contains resource tags defined as key/value pairs.

id str: The provider-assigned unique ID for this managed resource.
name str: Specifies the name of the resource.
properties DatasetResponse: Dataset properties
type str: Specifies the type of the resource.
identity IdentityResponse: The identity of the resource.
location str: Specifies the location of the resource.
sku SkuResponse: The sku of the workspace.
tags Mapping[str, str]: Contains resource tags defined as key/value pairs.

id String: The provider-assigned unique ID for this managed resource.
name String: Specifies the name of the resource.
properties Property Map: Dataset properties
type String: Specifies the type of the resource.
identity Property Map: The identity of the resource.
location String: Specifies the location of the resource.
sku Property Map: The sku of the workspace.
tags Map<String>: Contains resource tags defined as key/value pairs.

Supporting Types

DatasetCreateRequestDataPath
, DatasetCreateRequestDataPathArgs

DatastoreName string: The datastore name.
RelativePath string: Path within the datastore.

DatastoreName string: The datastore name.
RelativePath string: Path within the datastore.

datastoreName String: The datastore name.
relativePath String: Path within the datastore.

datastoreName string: The datastore name.
relativePath string: Path within the datastore.

datastore_name str: The datastore name.
relative_path str: Path within the datastore.

datastoreName String: The datastore name.
relativePath String: Path within the datastore.

DatasetCreateRequestParameters
, DatasetCreateRequestParametersArgs

Header string | Pulumi.AzureNative.MachineLearningServices.Header: Header type.
IncludePath bool: 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.
PartitionFormat string: 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
Path Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestPath
Query Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestQuery
Separator string: The separator used to split columns for 'delimited_files' sourceType.
SourceType string | Pulumi.AzureNative.MachineLearningServices.SourceType: Data source type.

Header string | Header: Header type.
IncludePath bool: 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.
PartitionFormat string: 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
Path DatasetCreateRequestPath
Query DatasetCreateRequestQuery
Separator string: The separator used to split columns for 'delimited_files' sourceType.
SourceType string | SourceType: Data source type.

header String | Header: Header type.
includePath Boolean: 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.
partitionFormat String: 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
path DatasetCreateRequestPath
query DatasetCreateRequestQuery
separator String: The separator used to split columns for 'delimited_files' sourceType.
sourceType String | SourceType: Data source type.

header string | Header: Header type.
includePath boolean: 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.
partitionFormat string: 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
path DatasetCreateRequestPath
query DatasetCreateRequestQuery
separator string: The separator used to split columns for 'delimited_files' sourceType.
sourceType string | SourceType: Data source type.

header str | Header: Header type.
include_path bool: 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.
partition_format str: 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
path DatasetCreateRequestPath
query DatasetCreateRequestQuery
separator str: The separator used to split columns for 'delimited_files' sourceType.
source_type str | SourceType: Data source type.

header String | "all_files_have_same_headers" | "only_first_file_has_headers" | "no_headers" | "combine_all_files_headers": Header type.
includePath Boolean: 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.
partitionFormat String: 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
path Property Map
query Property Map
separator String: The separator used to split columns for 'delimited_files' sourceType.
sourceType String | "delimited_files" | "json_lines_files" | "parquet_files": Data source type.

DatasetCreateRequestPath
, DatasetCreateRequestPathArgs

DataPath Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetCreateRequestDataPath
HttpUrl string: The Http URL.

DataPath DatasetCreateRequestDataPath
HttpUrl string: The Http URL.

dataPath DatasetCreateRequestDataPath
httpUrl String: The Http URL.

dataPath DatasetCreateRequestDataPath
httpUrl string: The Http URL.

data_path DatasetCreateRequestDataPath
http_url str: The Http URL.

dataPath Property Map
httpUrl String: The Http URL.

DatasetCreateRequestQuery
, DatasetCreateRequestQueryArgs

DatastoreName string: The SQL/PostgreSQL/MySQL datastore name.
Query string: SQL Quey.

DatastoreName string: The SQL/PostgreSQL/MySQL datastore name.
Query string: SQL Quey.

datastoreName String: The SQL/PostgreSQL/MySQL datastore name.
query String: SQL Quey.

datastoreName string: The SQL/PostgreSQL/MySQL datastore name.
query string: SQL Quey.

datastore_name str: The SQL/PostgreSQL/MySQL datastore name.
query str: SQL Quey.

datastoreName String: The SQL/PostgreSQL/MySQL datastore name.
query String: SQL Quey.

DatasetCreateRequestRegistration
, DatasetCreateRequestRegistrationArgs

Description string: The description for the dataset.
Name string: The name of the dataset.
Tags Dictionary<string, string>: Tags associated with the dataset.

Description string: The description for the dataset.
Name string: The name of the dataset.
Tags map[string]string: Tags associated with the dataset.

description String: The description for the dataset.
name String: The name of the dataset.
tags Map<String,String>: Tags associated with the dataset.

description string: The description for the dataset.
name string: The name of the dataset.
tags {[key: string]: string}: Tags associated with the dataset.

description str: The description for the dataset.
name str: The name of the dataset.
tags Mapping[str, str]: Tags associated with the dataset.

description String: The description for the dataset.
name String: The name of the dataset.
tags Map<String>: Tags associated with the dataset.

DatasetCreateRequestTimeSeries
, DatasetCreateRequestTimeSeriesArgs

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

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

coarseGrainTimestamp String: Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'.
fineGrainTimestamp String: Column name to be used as FineGrainTimestamp

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

coarse_grain_timestamp str: Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'.
fine_grain_timestamp str: Column name to be used as FineGrainTimestamp

coarseGrainTimestamp String: Column name to be used as CoarseGrainTimestamp. Can only be used if 'fineGrainTimestamp' is specified and cannot be same as 'fineGrainTimestamp'.
fineGrainTimestamp String: Column name to be used as FineGrainTimestamp

DatasetResponse
, DatasetResponseArgs

CreatedTime string: The dataset creation time (UTC).
DatasetId string: Unique Dataset identifier.
DatasetType string: Dataset Type.
DefaultCompute string: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
Description string: Description about this dataset version.
Etag string: eTag description
IsVisible bool: Flag to hide Dataset in UI
ModifiedTime string: The dataset last modified time (UTC).
Name string: Unique dataset name
Tags Dictionary<string, string>: Tags for this dataset version.
DatasetState Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetStateResponse: Dataset state
Latest Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetResponseLatest: Last created Dataset definition.

CreatedTime string: The dataset creation time (UTC).
DatasetId string: Unique Dataset identifier.
DatasetType string: Dataset Type.
DefaultCompute string: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
Description string: Description about this dataset version.
Etag string: eTag description
IsVisible bool: Flag to hide Dataset in UI
ModifiedTime string: The dataset last modified time (UTC).
Name string: Unique dataset name
Tags map[string]string: Tags for this dataset version.
DatasetState DatasetStateResponse: Dataset state
Latest DatasetResponseLatest: Last created Dataset definition.

createdTime String: The dataset creation time (UTC).
datasetId String: Unique Dataset identifier.
datasetType String: Dataset Type.
defaultCompute String: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
description String: Description about this dataset version.
etag String: eTag description
isVisible Boolean: Flag to hide Dataset in UI
modifiedTime String: The dataset last modified time (UTC).
name String: Unique dataset name
tags Map<String,String>: Tags for this dataset version.
datasetState DatasetStateResponse: Dataset state
latest DatasetResponseLatest: Last created Dataset definition.

createdTime string: The dataset creation time (UTC).
datasetId string: Unique Dataset identifier.
datasetType string: Dataset Type.
defaultCompute string: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
description string: Description about this dataset version.
etag string: eTag description
isVisible boolean: Flag to hide Dataset in UI
modifiedTime string: The dataset last modified time (UTC).
name string: Unique dataset name
tags {[key: string]: string}: Tags for this dataset version.
datasetState DatasetStateResponse: Dataset state
latest DatasetResponseLatest: Last created Dataset definition.

created_time str: The dataset creation time (UTC).
dataset_id str: Unique Dataset identifier.
dataset_type str: Dataset Type.
default_compute str: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
description str: Description about this dataset version.
etag str: eTag description
is_visible bool: Flag to hide Dataset in UI
modified_time str: The dataset last modified time (UTC).
name str: Unique dataset name
tags Mapping[str, str]: Tags for this dataset version.
dataset_state DatasetStateResponse: Dataset state
latest DatasetResponseLatest: Last created Dataset definition.

createdTime String: The dataset creation time (UTC).
datasetId String: Unique Dataset identifier.
datasetType String: Dataset Type.
defaultCompute String: Name of the default compute to be used for any Dataset actions (such as Profile, Write).
description String: Description about this dataset version.
etag String: eTag description
isVisible Boolean: Flag to hide Dataset in UI
modifiedTime String: The dataset last modified time (UTC).
name String: Unique dataset name
tags Map<String>: Tags for this dataset version.
datasetState Property Map: Dataset state
latest Property Map: Last created Dataset definition.

DatasetResponseDataPath
, DatasetResponseDataPathArgs

AzureFilePath string: Azure path for Azure Blob or File
DatastoreName string: Data store Name
HttpUrl string: HTTP URL.
PartitionFormat string: Specify the partition format of path. Defaults to None.
PartitionFormatIgnoreError bool: Whether or not to ignore unmatched path.
Paths List<string>: List of files expanded from a file GLOB specified
RelativePath string: Relative path in the data store
AdditionalProperties Dictionary<string, object>: Additional Properties.
SqlDataPath Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetResponseSqlDataPath: Sql Query/Table/Stored Procedure details.

AzureFilePath string: Azure path for Azure Blob or File
DatastoreName string: Data store Name
HttpUrl string: HTTP URL.
PartitionFormat string: Specify the partition format of path. Defaults to None.
PartitionFormatIgnoreError bool: Whether or not to ignore unmatched path.
Paths []string: List of files expanded from a file GLOB specified
RelativePath string: Relative path in the data store
AdditionalProperties map[string]interface{}: Additional Properties.
SqlDataPath DatasetResponseSqlDataPath: Sql Query/Table/Stored Procedure details.

azureFilePath String: Azure path for Azure Blob or File
datastoreName String: Data store Name
httpUrl String: HTTP URL.
partitionFormat String: Specify the partition format of path. Defaults to None.
partitionFormatIgnoreError Boolean: Whether or not to ignore unmatched path.
paths List<String>: List of files expanded from a file GLOB specified
relativePath String: Relative path in the data store
additionalProperties Map<String,Object>: Additional Properties.
sqlDataPath DatasetResponseSqlDataPath: Sql Query/Table/Stored Procedure details.

azureFilePath string: Azure path for Azure Blob or File
datastoreName string: Data store Name
httpUrl string: HTTP URL.
partitionFormat string: Specify the partition format of path. Defaults to None.
partitionFormatIgnoreError boolean: Whether or not to ignore unmatched path.
paths string[]: List of files expanded from a file GLOB specified
relativePath string: Relative path in the data store
additionalProperties {[key: string]: any}: Additional Properties.
sqlDataPath DatasetResponseSqlDataPath: Sql Query/Table/Stored Procedure details.

azure_file_path str: Azure path for Azure Blob or File
datastore_name str: Data store Name
http_url str: HTTP URL.
partition_format str: Specify the partition format of path. Defaults to None.
partition_format_ignore_error bool: Whether or not to ignore unmatched path.
paths Sequence[str]: List of files expanded from a file GLOB specified
relative_path str: Relative path in the data store
additional_properties Mapping[str, Any]: Additional Properties.
sql_data_path DatasetResponseSqlDataPath: Sql Query/Table/Stored Procedure details.

azureFilePath String: Azure path for Azure Blob or File
datastoreName String: Data store Name
httpUrl String: HTTP URL.
partitionFormat String: Specify the partition format of path. Defaults to None.
partitionFormatIgnoreError Boolean: Whether or not to ignore unmatched path.
paths List<String>: List of files expanded from a file GLOB specified
relativePath String: Relative path in the data store
additionalProperties Map<Any>: Additional Properties.
sqlDataPath Property Map: Sql Query/Table/Stored Procedure details.

DatasetResponseLatest
, DatasetResponseLatestArgs

CreatedTime string: The dataset creation time (UTC).
Dataflow string: Dataflow Json
DatasetId string: Unique Dataset identifier.
Description string: Description about the dataset.
Etag string: eTag description
FileType string: Dataset FileType, specified by user.
ModifiedTime string: The dataset last modified time (UTC).
Notes string: Summary of Definition changes.
PartitionFormatInPath bool: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
SavedDatasetId string: Indicates the saved dataset this definition is mapping to, populated on Get.
Tags Dictionary<string, string>: Tags associated with the dataset.
TelemetryInfo Dictionary<string, string>: Telemetry information about the dataset including information like which service the dataset was created from.
UseDescriptionTagsFromDefinition bool: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
VersionId string: An identifier uniquely identifies a definition change.
CreatedBy Pulumi.AzureNative.MachineLearningServices.Inputs.UserInfoResponse: User who created.
DataPath Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetResponseDataPath: Datastore and reference to location of data such as relativePath, Sql Query and etc.
DatasetDefinitionState Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetStateResponse: Dataset state
Properties Dictionary<string, object>: Properties stores information like name of time series column for time series dataset.

CreatedTime string: The dataset creation time (UTC).
Dataflow string: Dataflow Json
DatasetId string: Unique Dataset identifier.
Description string: Description about the dataset.
Etag string: eTag description
FileType string: Dataset FileType, specified by user.
ModifiedTime string: The dataset last modified time (UTC).
Notes string: Summary of Definition changes.
PartitionFormatInPath bool: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
SavedDatasetId string: Indicates the saved dataset this definition is mapping to, populated on Get.
Tags map[string]string: Tags associated with the dataset.
TelemetryInfo map[string]string: Telemetry information about the dataset including information like which service the dataset was created from.
UseDescriptionTagsFromDefinition bool: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
VersionId string: An identifier uniquely identifies a definition change.
CreatedBy UserInfoResponse: User who created.
DataPath DatasetResponseDataPath: Datastore and reference to location of data such as relativePath, Sql Query and etc.
DatasetDefinitionState DatasetStateResponse: Dataset state
Properties map[string]interface{}: Properties stores information like name of time series column for time series dataset.

createdTime String: The dataset creation time (UTC).
dataflow String: Dataflow Json
datasetId String: Unique Dataset identifier.
description String: Description about the dataset.
etag String: eTag description
fileType String: Dataset FileType, specified by user.
modifiedTime String: The dataset last modified time (UTC).
notes String: Summary of Definition changes.
partitionFormatInPath Boolean: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
savedDatasetId String: Indicates the saved dataset this definition is mapping to, populated on Get.
tags Map<String,String>: Tags associated with the dataset.
telemetryInfo Map<String,String>: Telemetry information about the dataset including information like which service the dataset was created from.
useDescriptionTagsFromDefinition Boolean: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
versionId String: An identifier uniquely identifies a definition change.
createdBy UserInfoResponse: User who created.
dataPath DatasetResponseDataPath: Datastore and reference to location of data such as relativePath, Sql Query and etc.
datasetDefinitionState DatasetStateResponse: Dataset state
properties Map<String,Object>: Properties stores information like name of time series column for time series dataset.

createdTime string: The dataset creation time (UTC).
dataflow string: Dataflow Json
datasetId string: Unique Dataset identifier.
description string: Description about the dataset.
etag string: eTag description
fileType string: Dataset FileType, specified by user.
modifiedTime string: The dataset last modified time (UTC).
notes string: Summary of Definition changes.
partitionFormatInPath boolean: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
savedDatasetId string: Indicates the saved dataset this definition is mapping to, populated on Get.
tags {[key: string]: string}: Tags associated with the dataset.
telemetryInfo {[key: string]: string}: Telemetry information about the dataset including information like which service the dataset was created from.
useDescriptionTagsFromDefinition boolean: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
versionId string: An identifier uniquely identifies a definition change.
createdBy UserInfoResponse: User who created.
dataPath DatasetResponseDataPath: Datastore and reference to location of data such as relativePath, Sql Query and etc.
datasetDefinitionState DatasetStateResponse: Dataset state
properties {[key: string]: any}: Properties stores information like name of time series column for time series dataset.

created_time str: The dataset creation time (UTC).
dataflow str: Dataflow Json
dataset_id str: Unique Dataset identifier.
description str: Description about the dataset.
etag str: eTag description
file_type str: Dataset FileType, specified by user.
modified_time str: The dataset last modified time (UTC).
notes str: Summary of Definition changes.
partition_format_in_path bool: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
saved_dataset_id str: Indicates the saved dataset this definition is mapping to, populated on Get.
tags Mapping[str, str]: Tags associated with the dataset.
telemetry_info Mapping[str, str]: Telemetry information about the dataset including information like which service the dataset was created from.
use_description_tags_from_definition bool: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
version_id str: An identifier uniquely identifies a definition change.
created_by UserInfoResponse: User who created.
data_path DatasetResponseDataPath: Datastore and reference to location of data such as relativePath, Sql Query and etc.
dataset_definition_state DatasetStateResponse: Dataset state
properties Mapping[str, Any]: Properties stores information like name of time series column for time series dataset.

createdTime String: The dataset creation time (UTC).
dataflow String: Dataflow Json
datasetId String: Unique Dataset identifier.
description String: Description about the dataset.
etag String: eTag description
fileType String: Dataset FileType, specified by user.
modifiedTime String: The dataset last modified time (UTC).
notes String: Summary of Definition changes.
partitionFormatInPath Boolean: Indicates how the source data is partitioned. This is defined to filter on a range of partitioned data before performing actions or materialization.
savedDatasetId String: Indicates the saved dataset this definition is mapping to, populated on Get.
tags Map<String>: Tags associated with the dataset.
telemetryInfo Map<String>: Telemetry information about the dataset including information like which service the dataset was created from.
useDescriptionTagsFromDefinition Boolean: Whether to use description and tags from the definition level as opposed to dataset level (old behavior).
versionId String: An identifier uniquely identifies a definition change.
createdBy Property Map: User who created.
dataPath Property Map: Datastore and reference to location of data such as relativePath, Sql Query and etc.
datasetDefinitionState Property Map: Dataset state
properties Map<Any>: Properties stores information like name of time series column for time series dataset.

DatasetResponseSqlDataPath
, DatasetResponseSqlDataPathArgs

QueryTimeout double: SQL query timeout. Unit in seconds.
SqlQuery string: SQL query
SqlStoredProcedureName string: SQL storedProcedure name
SqlTableName string: SQL table name

QueryTimeout float64: SQL query timeout. Unit in seconds.
SqlQuery string: SQL query
SqlStoredProcedureName string: SQL storedProcedure name
SqlTableName string: SQL table name

queryTimeout Double: SQL query timeout. Unit in seconds.
sqlQuery String: SQL query
sqlStoredProcedureName String: SQL storedProcedure name
sqlTableName String: SQL table name

queryTimeout number: SQL query timeout. Unit in seconds.
sqlQuery string: SQL query
sqlStoredProcedureName string: SQL storedProcedure name
sqlTableName string: SQL table name

query_timeout float: SQL query timeout. Unit in seconds.
sql_query str: SQL query
sql_stored_procedure_name str: SQL storedProcedure name
sql_table_name str: SQL table name

queryTimeout Number: SQL query timeout. Unit in seconds.
sqlQuery String: SQL query
sqlStoredProcedureName String: SQL storedProcedure name
sqlTableName String: SQL table name

DatasetStateResponse
, DatasetStateResponseArgs

Etag string: eTag description
DeprecatedBy Pulumi.AzureNative.MachineLearningServices.Inputs.DatasetStateResponseDeprecatedBy: Reference to better Dataset or a Definition
State string: Dataset state

Etag string: eTag description
DeprecatedBy DatasetStateResponseDeprecatedBy: Reference to better Dataset or a Definition
State string: Dataset state

etag String: eTag description
deprecatedBy DatasetStateResponseDeprecatedBy: Reference to better Dataset or a Definition
state String: Dataset state

etag string: eTag description
deprecatedBy DatasetStateResponseDeprecatedBy: Reference to better Dataset or a Definition
state string: Dataset state

etag str: eTag description
deprecated_by DatasetStateResponseDeprecatedBy: Reference to better Dataset or a Definition
state str: Dataset state

etag String: eTag description
deprecatedBy Property Map: Reference to better Dataset or a Definition
state String: Dataset state

DatasetStateResponseDeprecatedBy
, DatasetStateResponseDeprecatedByArgs

DatasetId string: Unique Dataset identifier.
DefinitionVersion string: Definition Version

DatasetId string: Unique Dataset identifier.
DefinitionVersion string: Definition Version

datasetId String: Unique Dataset identifier.
definitionVersion String: Definition Version

datasetId string: Unique Dataset identifier.
definitionVersion string: Definition Version

dataset_id str: Unique Dataset identifier.
definition_version str: Definition Version

datasetId String: Unique Dataset identifier.
definitionVersion String: Definition Version

DatasetType
, DatasetTypeArgs

Tabular: tabular
File: file

DatasetTypeTabular: tabular
DatasetTypeFile: file

Tabular: tabular
File: file

Tabular: tabular
File: file

TABULAR: tabular
FILE: file

"tabular": tabular
"file": file

All_files_have_same_headers: all_files_have_same_headers
Only_first_file_has_headers: only_first_file_has_headers
No_headers: no_headers
Combine_all_files_headers: combine_all_files_headers

Header_All_files_have_same_headers: all_files_have_same_headers
Header_Only_first_file_has_headers: only_first_file_has_headers
Header_No_headers: no_headers
Header_Combine_all_files_headers: combine_all_files_headers

All_files_have_same_headers: all_files_have_same_headers
Only_first_file_has_headers: only_first_file_has_headers
No_headers: no_headers
Combine_all_files_headers: combine_all_files_headers

All_files_have_same_headers: all_files_have_same_headers
Only_first_file_has_headers: only_first_file_has_headers
No_headers: no_headers
Combine_all_files_headers: combine_all_files_headers

ALL_FILES_HAVE_SAME_HEADERS: all_files_have_same_headers
ONLY_FIRST_FILE_HAS_HEADERS: only_first_file_has_headers
NO_HEADERS: no_headers
COMBINE_ALL_FILES_HEADERS: combine_all_files_headers

"all_files_have_same_headers": all_files_have_same_headers
"only_first_file_has_headers": only_first_file_has_headers
"no_headers": no_headers
"combine_all_files_headers": combine_all_files_headers

IdentityResponse
, IdentityResponseArgs

PrincipalId string: The principal ID of resource identity.
TenantId string: The tenant ID of resource.
Type string: The identity type.
UserAssignedIdentities Dictionary<string, Pulumi.AzureNative.MachineLearningServices.Inputs.UserAssignedIdentityResponse>: The user assigned identities associated with the resource.

PrincipalId string: The principal ID of resource identity.
TenantId string: The tenant ID of resource.
Type string: The identity type.
UserAssignedIdentities map[string]UserAssignedIdentityResponse: The user assigned identities associated with the resource.

principalId String: The principal ID of resource identity.
tenantId String: The tenant ID of resource.
type String: The identity type.
userAssignedIdentities Map<String,UserAssignedIdentityResponse>: The user assigned identities associated with the resource.

principalId string: The principal ID of resource identity.
tenantId string: The tenant ID of resource.
type string: The identity type.
userAssignedIdentities {[key: string]: UserAssignedIdentityResponse}: The user assigned identities associated with the resource.

principal_id str: The principal ID of resource identity.
tenant_id str: The tenant ID of resource.
type str: The identity type.
user_assigned_identities Mapping[str, UserAssignedIdentityResponse]: The user assigned identities associated with the resource.

principalId String: The principal ID of resource identity.
tenantId String: The tenant ID of resource.
type String: The identity type.
userAssignedIdentities Map<Property Map>: The user assigned identities associated with the resource.

SkuResponse
, SkuResponseArgs

Name string: The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string: If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier string: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

Name string: The name of the SKU. Ex - P3. It is typically a letter+number code
Capacity int: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
Family string: If the service has different generations of hardware, for the same SKU, then that can be captured here.
Size string: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
Tier string: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

name String: The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Integer: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String: If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier String: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

name string: The name of the SKU. Ex - P3. It is typically a letter+number code
capacity number: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family string: If the service has different generations of hardware, for the same SKU, then that can be captured here.
size string: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier string: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

name str: The name of the SKU. Ex - P3. It is typically a letter+number code
capacity int: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family str: If the service has different generations of hardware, for the same SKU, then that can be captured here.
size str: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier str: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

name String: The name of the SKU. Ex - P3. It is typically a letter+number code
capacity Number: If the SKU supports scale out/in then the capacity integer should be included. If scale out/in is not possible for the resource this may be omitted.
family String: If the service has different generations of hardware, for the same SKU, then that can be captured here.
size String: The SKU size. When the name field is the combination of tier and some other value, this would be the standalone code.
tier String: This field is required to be implemented by the Resource Provider if the service has more than one tier, but is not required on a PUT.

SourceType
, SourceTypeArgs

Delimited_files: delimited_files
Json_lines_files: json_lines_files
Parquet_files: parquet_files

SourceType_Delimited_files: delimited_files
SourceType_Json_lines_files: json_lines_files
SourceType_Parquet_files: parquet_files

Delimited_files: delimited_files
Json_lines_files: json_lines_files
Parquet_files: parquet_files

Delimited_files: delimited_files
Json_lines_files: json_lines_files
Parquet_files: parquet_files

DELIMITED_FILES: delimited_files
JSON_LINES_FILES: json_lines_files
PARQUET_FILES: parquet_files

"delimited_files": delimited_files
"json_lines_files": json_lines_files
"parquet_files": parquet_files

UserAssignedIdentityResponse
, UserAssignedIdentityResponseArgs

ClientId string: The client ID of the assigned identity.
PrincipalId string: The principal ID of the assigned identity.
TenantId string: The tenant ID of the user assigned identity.

ClientId string: The client ID of the assigned identity.
PrincipalId string: The principal ID of the assigned identity.
TenantId string: The tenant ID of the user assigned identity.

clientId String: The client ID of the assigned identity.
principalId String: The principal ID of the assigned identity.
tenantId String: The tenant ID of the user assigned identity.

clientId string: The client ID of the assigned identity.
principalId string: The principal ID of the assigned identity.
tenantId string: The tenant ID of the user assigned identity.

client_id str: The client ID of the assigned identity.
principal_id str: The principal ID of the assigned identity.
tenant_id str: The tenant ID of the user assigned identity.

clientId String: The client ID of the assigned identity.
principalId String: The principal ID of the assigned identity.
tenantId String: The tenant ID of the user assigned identity.

UserInfoResponse
, UserInfoResponseArgs

UserAltSecId string: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
UserIdp string: A user identity provider. Eg live.com
UserIss string: The issuer which issued the token for this user.
UserName string: A user's full name or a service principal's app ID.
UserObjectId string: A user or service principal's object ID..
UserPuId string: A user or service principal's PuID.
UserTenantId string: A user or service principal's tenant ID.

UserAltSecId string: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
UserIdp string: A user identity provider. Eg live.com
UserIss string: The issuer which issued the token for this user.
UserName string: A user's full name or a service principal's app ID.
UserObjectId string: A user or service principal's object ID..
UserPuId string: A user or service principal's PuID.
UserTenantId string: A user or service principal's tenant ID.

userAltSecId String: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
userIdp String: A user identity provider. Eg live.com
userIss String: The issuer which issued the token for this user.
userName String: A user's full name or a service principal's app ID.
userObjectId String: A user or service principal's object ID..
userPuId String: A user or service principal's PuID.
userTenantId String: A user or service principal's tenant ID.

userAltSecId string: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
userIdp string: A user identity provider. Eg live.com
userIss string: The issuer which issued the token for this user.
userName string: A user's full name or a service principal's app ID.
userObjectId string: A user or service principal's object ID..
userPuId string: A user or service principal's PuID.
userTenantId string: A user or service principal's tenant ID.

user_alt_sec_id str: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
user_idp str: A user identity provider. Eg live.com
user_iss str: The issuer which issued the token for this user.
user_name str: A user's full name or a service principal's app ID.
user_object_id str: A user or service principal's object ID..
user_pu_id str: A user or service principal's PuID.
user_tenant_id str: A user or service principal's tenant ID.

userAltSecId String: A user alternate sec id. This represents the user in a different identity provider system Eg.1:live.com:puid
userIdp String: A user identity provider. Eg live.com
userIss String: The issuer which issued the token for this user.
userName String: A user's full name or a service principal's app ID.
userObjectId String: A user or service principal's object ID..
userPuId String: A user or service principal's PuID.
userTenantId String: A user or service principal's tenant ID.

Import

An existing resource can be imported using its type token, name, and identifier, e.g.

$ pulumi import azure-native:machinelearningservices:MachineLearningDataset datasetName123 /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/datasets/{datasetName}

To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository: azure-native-v2 pulumi/pulumi-azure-native
License: Apache-2.0

These are the docs for Azure Native v2. We recommenend using the latest version, Azure Native v3.

Azure Native v2 v2.90.0 published on Thursday, Mar 27, 2025 by Pulumi

pulumi/pulumi-azure-native

azure-native-v2.machinelearningservices.MachineLearningDataset

On this page

On this page

Example Usage

Create Dataset

Create MachineLearningDataset Resource

Constructor syntax

Parameters

Constructor example

MachineLearningDataset Resource Properties

Inputs

Outputs

Supporting Types

DatasetCreateRequestDataPath
, DatasetCreateRequestDataPathArgs

DatasetCreateRequestParameters
, DatasetCreateRequestParametersArgs

DatasetCreateRequestPath
, DatasetCreateRequestPathArgs

DatasetCreateRequestQuery
, DatasetCreateRequestQueryArgs

DatasetCreateRequestRegistration
, DatasetCreateRequestRegistrationArgs

DatasetCreateRequestTimeSeries
, DatasetCreateRequestTimeSeriesArgs

DatasetResponse
, DatasetResponseArgs

DatasetResponseDataPath
, DatasetResponseDataPathArgs

DatasetResponseLatest
, DatasetResponseLatestArgs

DatasetResponseSqlDataPath
, DatasetResponseSqlDataPathArgs

DatasetStateResponse
, DatasetStateResponseArgs

DatasetStateResponseDeprecatedBy
, DatasetStateResponseDeprecatedByArgs

DatasetType
, DatasetTypeArgs

Header
, HeaderArgs

IdentityResponse
, IdentityResponseArgs

SkuResponse
, SkuResponseArgs

SourceType
, SourceTypeArgs

UserAssignedIdentityResponse
, UserAssignedIdentityResponseArgs

UserInfoResponse
, UserInfoResponseArgs

Import

Package Details

On this page

On this page

azure-native-v2.machinelearningservices.MachineLearningDataset

On this page

On this page

Example Usage

Create Dataset

Create MachineLearningDataset Resource

Constructor syntax

Parameters

Constructor example

MachineLearningDataset Resource Properties

Inputs

Outputs

Supporting Types

DatasetCreateRequestDataPath, DatasetCreateRequestDataPathArgs

DatasetCreateRequestParameters, DatasetCreateRequestParametersArgs

DatasetCreateRequestPath, DatasetCreateRequestPathArgs

DatasetCreateRequestQuery, DatasetCreateRequestQueryArgs

DatasetCreateRequestRegistration, DatasetCreateRequestRegistrationArgs

DatasetCreateRequestTimeSeries, DatasetCreateRequestTimeSeriesArgs

DatasetResponse, DatasetResponseArgs

DatasetResponseDataPath, DatasetResponseDataPathArgs

DatasetResponseLatest, DatasetResponseLatestArgs

DatasetResponseSqlDataPath, DatasetResponseSqlDataPathArgs

DatasetStateResponse, DatasetStateResponseArgs

DatasetStateResponseDeprecatedBy, DatasetStateResponseDeprecatedByArgs

DatasetType, DatasetTypeArgs

Header, HeaderArgs

IdentityResponse, IdentityResponseArgs

SkuResponse, SkuResponseArgs

SourceType, SourceTypeArgs

UserAssignedIdentityResponse, UserAssignedIdentityResponseArgs

UserInfoResponse, UserInfoResponseArgs

Import

Package Details

On this page

On this page

DatasetCreateRequestDataPath
, DatasetCreateRequestDataPathArgs

DatasetCreateRequestParameters
, DatasetCreateRequestParametersArgs

DatasetCreateRequestPath
, DatasetCreateRequestPathArgs

DatasetCreateRequestQuery
, DatasetCreateRequestQueryArgs

DatasetCreateRequestRegistration
, DatasetCreateRequestRegistrationArgs

DatasetCreateRequestTimeSeries
, DatasetCreateRequestTimeSeriesArgs

DatasetResponse
, DatasetResponseArgs

DatasetResponseDataPath
, DatasetResponseDataPathArgs

DatasetResponseLatest
, DatasetResponseLatestArgs

DatasetResponseSqlDataPath
, DatasetResponseSqlDataPathArgs

DatasetStateResponse
, DatasetStateResponseArgs

DatasetStateResponseDeprecatedBy
, DatasetStateResponseDeprecatedByArgs

DatasetType
, DatasetTypeArgs

Header
, HeaderArgs

IdentityResponse
, IdentityResponseArgs

SkuResponse
, SkuResponseArgs

SourceType
, SourceTypeArgs

UserAssignedIdentityResponse
, UserAssignedIdentityResponseArgs

UserInfoResponse
, UserInfoResponseArgs