AWS Native v0.112.0, Jul 24 24

AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.112.0 published on Wednesday, Jul 24, 2024 by Pulumi

pulumi/pulumi-aws-native

aws-native.iotanalytics.Dataset

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AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.112.0 published on Wednesday, Jul 24, 2024 by Pulumi

pulumi/pulumi-aws-native

Example Usage

Example

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

return await Deployment.RunAsync(() => 
{
    var dataset = new AwsNative.IoTAnalytics.Dataset("dataset", new()
    {
        DatasetName = "SimpleSQLDataset",
        Actions = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetActionArgs
            {
                ActionName = "SqlAction",
                QueryAction = new AwsNative.IoTAnalytics.Inputs.DatasetQueryActionArgs
                {
                    SqlQuery = "select * from Datastore",
                },
            },
        },
        Triggers = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetTriggerArgs
            {
                Schedule = new AwsNative.IoTAnalytics.Inputs.DatasetScheduleArgs
                {
                    ScheduleExpression = "cron(0 12 * * ? *)",
                },
            },
        },
    });

});

package main

import (
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/iotanalytics"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := iotanalytics.NewDataset(ctx, "dataset", &iotanalytics.DatasetArgs{
			DatasetName: pulumi.String("SimpleSQLDataset"),
			Actions: iotanalytics.DatasetActionArray{
				&iotanalytics.DatasetActionArgs{
					ActionName: pulumi.String("SqlAction"),
					QueryAction: &iotanalytics.DatasetQueryActionArgs{
						SqlQuery: pulumi.String("select * from Datastore"),
					},
				},
			},
			Triggers: iotanalytics.DatasetTriggerArray{
				&iotanalytics.DatasetTriggerArgs{
					Schedule: &iotanalytics.DatasetScheduleArgs{
						ScheduleExpression: pulumi.String("cron(0 12 * * ? *)"),
					},
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

Coming soon!

import pulumi
import pulumi_aws_native as aws_native

dataset = aws_native.iotanalytics.Dataset("dataset",
    dataset_name="SimpleSQLDataset",
    actions=[aws_native.iotanalytics.DatasetActionArgs(
        action_name="SqlAction",
        query_action=aws_native.iotanalytics.DatasetQueryActionArgs(
            sql_query="select * from Datastore",
        ),
    )],
    triggers=[aws_native.iotanalytics.DatasetTriggerArgs(
        schedule=aws_native.iotanalytics.DatasetScheduleArgs(
            schedule_expression="cron(0 12 * * ? *)",
        ),
    )])

import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const dataset = new aws_native.iotanalytics.Dataset("dataset", {
    datasetName: "SimpleSQLDataset",
    actions: [{
        actionName: "SqlAction",
        queryAction: {
            sqlQuery: "select * from Datastore",
        },
    }],
    triggers: [{
        schedule: {
            scheduleExpression: "cron(0 12 * * ? *)",
        },
    }],
});

Coming soon!

Example

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

return await Deployment.RunAsync(() => 
{
    var dataset = new AwsNative.IoTAnalytics.Dataset("dataset", new()
    {
        DatasetName = "SimpleSQLDataset",
        Actions = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetActionArgs
            {
                ActionName = "SqlAction",
                QueryAction = new AwsNative.IoTAnalytics.Inputs.DatasetQueryActionArgs
                {
                    SqlQuery = "select * from Datastore",
                },
            },
        },
        Triggers = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetTriggerArgs
            {
                Schedule = new AwsNative.IoTAnalytics.Inputs.DatasetScheduleArgs
                {
                    ScheduleExpression = "cron(0 12 * * ? *)",
                },
            },
        },
    });

});

package main

import (
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/iotanalytics"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := iotanalytics.NewDataset(ctx, "dataset", &iotanalytics.DatasetArgs{
			DatasetName: pulumi.String("SimpleSQLDataset"),
			Actions: iotanalytics.DatasetActionArray{
				&iotanalytics.DatasetActionArgs{
					ActionName: pulumi.String("SqlAction"),
					QueryAction: &iotanalytics.DatasetQueryActionArgs{
						SqlQuery: pulumi.String("select * from Datastore"),
					},
				},
			},
			Triggers: iotanalytics.DatasetTriggerArray{
				&iotanalytics.DatasetTriggerArgs{
					Schedule: &iotanalytics.DatasetScheduleArgs{
						ScheduleExpression: pulumi.String("cron(0 12 * * ? *)"),
					},
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

Coming soon!

import pulumi
import pulumi_aws_native as aws_native

dataset = aws_native.iotanalytics.Dataset("dataset",
    dataset_name="SimpleSQLDataset",
    actions=[aws_native.iotanalytics.DatasetActionArgs(
        action_name="SqlAction",
        query_action=aws_native.iotanalytics.DatasetQueryActionArgs(
            sql_query="select * from Datastore",
        ),
    )],
    triggers=[aws_native.iotanalytics.DatasetTriggerArgs(
        schedule=aws_native.iotanalytics.DatasetScheduleArgs(
            schedule_expression="cron(0 12 * * ? *)",
        ),
    )])

import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const dataset = new aws_native.iotanalytics.Dataset("dataset", {
    datasetName: "SimpleSQLDataset",
    actions: [{
        actionName: "SqlAction",
        queryAction: {
            sqlQuery: "select * from Datastore",
        },
    }],
    triggers: [{
        schedule: {
            scheduleExpression: "cron(0 12 * * ? *)",
        },
    }],
});

Coming soon!

Example

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

return await Deployment.RunAsync(() => 
{
    var dataset = new AwsNative.IoTAnalytics.Dataset("dataset", new()
    {
        DatasetName = "ComplexSQLDataset",
        Actions = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetActionArgs
            {
                ActionName = "SqlAction",
                QueryAction = new AwsNative.IoTAnalytics.Inputs.DatasetQueryActionArgs
                {
                    SqlQuery = "select * from Datastore",
                    Filters = new[]
                    {
                        new AwsNative.IoTAnalytics.Inputs.DatasetFilterArgs
                        {
                            DeltaTime = new AwsNative.IoTAnalytics.Inputs.DatasetDeltaTimeArgs
                            {
                                OffsetSeconds = 1,
                                TimeExpression = "timestamp",
                            },
                        },
                    },
                },
            },
        },
        Triggers = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetTriggerArgs
            {
                Schedule = new AwsNative.IoTAnalytics.Inputs.DatasetScheduleArgs
                {
                    ScheduleExpression = "cron(0 12 * * ? *)",
                },
            },
        },
        RetentionPeriod = new AwsNative.IoTAnalytics.Inputs.DatasetRetentionPeriodArgs
        {
            Unlimited = false,
            NumberOfDays = 10,
        },
        Tags = new[]
        {
            new AwsNative.Inputs.TagArgs
            {
                Key = "keyname1",
                Value = "value1",
            },
            new AwsNative.Inputs.TagArgs
            {
                Key = "keyname2",
                Value = "value2",
            },
        },
    });

});

package main

import (
	awsnative "github.com/pulumi/pulumi-aws-native/sdk/go/aws"
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/iotanalytics"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := iotanalytics.NewDataset(ctx, "dataset", &iotanalytics.DatasetArgs{
			DatasetName: pulumi.String("ComplexSQLDataset"),
			Actions: iotanalytics.DatasetActionArray{
				&iotanalytics.DatasetActionArgs{
					ActionName: pulumi.String("SqlAction"),
					QueryAction: &iotanalytics.DatasetQueryActionArgs{
						SqlQuery: pulumi.String("select * from Datastore"),
						Filters: iotanalytics.DatasetFilterArray{
							&iotanalytics.DatasetFilterArgs{
								DeltaTime: &iotanalytics.DatasetDeltaTimeArgs{
									OffsetSeconds:  pulumi.Int(1),
									TimeExpression: pulumi.String("timestamp"),
								},
							},
						},
					},
				},
			},
			Triggers: iotanalytics.DatasetTriggerArray{
				&iotanalytics.DatasetTriggerArgs{
					Schedule: &iotanalytics.DatasetScheduleArgs{
						ScheduleExpression: pulumi.String("cron(0 12 * * ? *)"),
					},
				},
			},
			RetentionPeriod: &iotanalytics.DatasetRetentionPeriodArgs{
				Unlimited:    pulumi.Bool(false),
				NumberOfDays: pulumi.Int(10),
			},
			Tags: aws.TagArray{
				&aws.TagArgs{
					Key:   pulumi.String("keyname1"),
					Value: pulumi.String("value1"),
				},
				&aws.TagArgs{
					Key:   pulumi.String("keyname2"),
					Value: pulumi.String("value2"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

Coming soon!

import pulumi
import pulumi_aws_native as aws_native

dataset = aws_native.iotanalytics.Dataset("dataset",
    dataset_name="ComplexSQLDataset",
    actions=[aws_native.iotanalytics.DatasetActionArgs(
        action_name="SqlAction",
        query_action=aws_native.iotanalytics.DatasetQueryActionArgs(
            sql_query="select * from Datastore",
            filters=[aws_native.iotanalytics.DatasetFilterArgs(
                delta_time=aws_native.iotanalytics.DatasetDeltaTimeArgs(
                    offset_seconds=1,
                    time_expression="timestamp",
                ),
            )],
        ),
    )],
    triggers=[aws_native.iotanalytics.DatasetTriggerArgs(
        schedule=aws_native.iotanalytics.DatasetScheduleArgs(
            schedule_expression="cron(0 12 * * ? *)",
        ),
    )],
    retention_period=aws_native.iotanalytics.DatasetRetentionPeriodArgs(
        unlimited=False,
        number_of_days=10,
    ),
    tags=[
        aws_native.TagArgs(
            key="keyname1",
            value="value1",
        ),
        aws_native.TagArgs(
            key="keyname2",
            value="value2",
        ),
    ])

import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const dataset = new aws_native.iotanalytics.Dataset("dataset", {
    datasetName: "ComplexSQLDataset",
    actions: [{
        actionName: "SqlAction",
        queryAction: {
            sqlQuery: "select * from Datastore",
            filters: [{
                deltaTime: {
                    offsetSeconds: 1,
                    timeExpression: "timestamp",
                },
            }],
        },
    }],
    triggers: [{
        schedule: {
            scheduleExpression: "cron(0 12 * * ? *)",
        },
    }],
    retentionPeriod: {
        unlimited: false,
        numberOfDays: 10,
    },
    tags: [
        {
            key: "keyname1",
            value: "value1",
        },
        {
            key: "keyname2",
            value: "value2",
        },
    ],
});

Coming soon!

Example

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

return await Deployment.RunAsync(() => 
{
    var dataset = new AwsNative.IoTAnalytics.Dataset("dataset", new()
    {
        DatasetName = "ComplexSQLDataset",
        Actions = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetActionArgs
            {
                ActionName = "SqlAction",
                QueryAction = new AwsNative.IoTAnalytics.Inputs.DatasetQueryActionArgs
                {
                    SqlQuery = "select * from Datastore",
                    Filters = new[]
                    {
                        new AwsNative.IoTAnalytics.Inputs.DatasetFilterArgs
                        {
                            DeltaTime = new AwsNative.IoTAnalytics.Inputs.DatasetDeltaTimeArgs
                            {
                                OffsetSeconds = 1,
                                TimeExpression = "timestamp",
                            },
                        },
                    },
                },
            },
        },
        Triggers = new[]
        {
            new AwsNative.IoTAnalytics.Inputs.DatasetTriggerArgs
            {
                Schedule = new AwsNative.IoTAnalytics.Inputs.DatasetScheduleArgs
                {
                    ScheduleExpression = "cron(0 12 * * ? *)",
                },
            },
        },
        RetentionPeriod = new AwsNative.IoTAnalytics.Inputs.DatasetRetentionPeriodArgs
        {
            Unlimited = false,
            NumberOfDays = 10,
        },
        Tags = new[]
        {
            new AwsNative.Inputs.TagArgs
            {
                Key = "keyname1",
                Value = "value1",
            },
            new AwsNative.Inputs.TagArgs
            {
                Key = "keyname2",
                Value = "value2",
            },
        },
    });

});

package main

import (
	awsnative "github.com/pulumi/pulumi-aws-native/sdk/go/aws"
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/iotanalytics"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := iotanalytics.NewDataset(ctx, "dataset", &iotanalytics.DatasetArgs{
			DatasetName: pulumi.String("ComplexSQLDataset"),
			Actions: iotanalytics.DatasetActionArray{
				&iotanalytics.DatasetActionArgs{
					ActionName: pulumi.String("SqlAction"),
					QueryAction: &iotanalytics.DatasetQueryActionArgs{
						SqlQuery: pulumi.String("select * from Datastore"),
						Filters: iotanalytics.DatasetFilterArray{
							&iotanalytics.DatasetFilterArgs{
								DeltaTime: &iotanalytics.DatasetDeltaTimeArgs{
									OffsetSeconds:  pulumi.Int(1),
									TimeExpression: pulumi.String("timestamp"),
								},
							},
						},
					},
				},
			},
			Triggers: iotanalytics.DatasetTriggerArray{
				&iotanalytics.DatasetTriggerArgs{
					Schedule: &iotanalytics.DatasetScheduleArgs{
						ScheduleExpression: pulumi.String("cron(0 12 * * ? *)"),
					},
				},
			},
			RetentionPeriod: &iotanalytics.DatasetRetentionPeriodArgs{
				Unlimited:    pulumi.Bool(false),
				NumberOfDays: pulumi.Int(10),
			},
			Tags: aws.TagArray{
				&aws.TagArgs{
					Key:   pulumi.String("keyname1"),
					Value: pulumi.String("value1"),
				},
				&aws.TagArgs{
					Key:   pulumi.String("keyname2"),
					Value: pulumi.String("value2"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

Coming soon!

import pulumi
import pulumi_aws_native as aws_native

dataset = aws_native.iotanalytics.Dataset("dataset",
    dataset_name="ComplexSQLDataset",
    actions=[aws_native.iotanalytics.DatasetActionArgs(
        action_name="SqlAction",
        query_action=aws_native.iotanalytics.DatasetQueryActionArgs(
            sql_query="select * from Datastore",
            filters=[aws_native.iotanalytics.DatasetFilterArgs(
                delta_time=aws_native.iotanalytics.DatasetDeltaTimeArgs(
                    offset_seconds=1,
                    time_expression="timestamp",
                ),
            )],
        ),
    )],
    triggers=[aws_native.iotanalytics.DatasetTriggerArgs(
        schedule=aws_native.iotanalytics.DatasetScheduleArgs(
            schedule_expression="cron(0 12 * * ? *)",
        ),
    )],
    retention_period=aws_native.iotanalytics.DatasetRetentionPeriodArgs(
        unlimited=False,
        number_of_days=10,
    ),
    tags=[
        aws_native.TagArgs(
            key="keyname1",
            value="value1",
        ),
        aws_native.TagArgs(
            key="keyname2",
            value="value2",
        ),
    ])

import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const dataset = new aws_native.iotanalytics.Dataset("dataset", {
    datasetName: "ComplexSQLDataset",
    actions: [{
        actionName: "SqlAction",
        queryAction: {
            sqlQuery: "select * from Datastore",
            filters: [{
                deltaTime: {
                    offsetSeconds: 1,
                    timeExpression: "timestamp",
                },
            }],
        },
    }],
    triggers: [{
        schedule: {
            scheduleExpression: "cron(0 12 * * ? *)",
        },
    }],
    retentionPeriod: {
        unlimited: false,
        numberOfDays: 10,
    },
    tags: [
        {
            key: "keyname1",
            value: "value1",
        },
        {
            key: "keyname2",
            value: "value2",
        },
    ],
});

Coming soon!

Create Dataset Resource

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

Constructor syntax

new Dataset(name: string, args: DatasetArgs, opts?: CustomResourceOptions);

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

@overload
def Dataset(resource_name: str,
            opts: Optional[ResourceOptions] = None,
            actions: Optional[Sequence[DatasetActionArgs]] = None,
            content_delivery_rules: Optional[Sequence[DatasetContentDeliveryRuleArgs]] = None,
            dataset_name: Optional[str] = None,
            late_data_rules: Optional[Sequence[DatasetLateDataRuleArgs]] = None,
            retention_period: Optional[DatasetRetentionPeriodArgs] = None,
            tags: Optional[Sequence[_root_inputs.TagArgs]] = None,
            triggers: Optional[Sequence[DatasetTriggerArgs]] = None,
            versioning_configuration: Optional[DatasetVersioningConfigurationArgs] = None)

func NewDataset(ctx *Context, name string, args DatasetArgs, opts ...ResourceOption) (*Dataset, error)

public Dataset(string name, DatasetArgs args, CustomResourceOptions? opts = null)

public Dataset(String name, DatasetArgs args)
public Dataset(String name, DatasetArgs args, CustomResourceOptions options)

type: aws-native:iotanalytics:Dataset
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 DatasetArgs: 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 DatasetArgs: 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 DatasetArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

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

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

Dataset Resource Properties

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

Inputs

The Dataset resource accepts the following input properties:

Actions List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetAction>

The DatasetAction objects that automatically create the dataset contents.

ContentDeliveryRules List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetContentDeliveryRule>

When dataset contents are created they are delivered to destinations specified here.

DatasetName string

The name of the dataset.

LateDataRules List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetLateDataRule>

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

RetentionPeriod Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetRetentionPeriod

Optional. How long, in days, message data is kept for the dataset.

Tags List<Pulumi.AwsNative.Inputs.Tag>

Metadata which can be used to manage the data set.

For more information, see Tag .

Triggers List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetTrigger>

The DatasetTrigger objects that specify when the dataset is automatically updated.

VersioningConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetVersioningConfiguration

Optional. How many versions of dataset contents are kept. If not specified or set to null, only the latest version plus the latest succeeded version (if they are different) are kept for the time period specified by the retentionPeriod parameter. For more information, see Keeping Multiple Versions of AWS IoT Analytics datasets in the AWS IoT Analytics User Guide .

Actions []DatasetActionArgs

The DatasetAction objects that automatically create the dataset contents.

ContentDeliveryRules []DatasetContentDeliveryRuleArgs

When dataset contents are created they are delivered to destinations specified here.

DatasetName string

The name of the dataset.

LateDataRules []DatasetLateDataRuleArgs

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

RetentionPeriod DatasetRetentionPeriodArgs

Optional. How long, in days, message data is kept for the dataset.

Tags TagArgs

Metadata which can be used to manage the data set.

For more information, see Tag .

Triggers []DatasetTriggerArgs

The DatasetTrigger objects that specify when the dataset is automatically updated.

VersioningConfiguration DatasetVersioningConfigurationArgs

actions List<DatasetAction>

The DatasetAction objects that automatically create the dataset contents.

contentDeliveryRules List<DatasetContentDeliveryRule>

When dataset contents are created they are delivered to destinations specified here.

datasetName String

The name of the dataset.

lateDataRules List<DatasetLateDataRule>

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

retentionPeriod DatasetRetentionPeriod

Optional. How long, in days, message data is kept for the dataset.

tags List<Tag>

Metadata which can be used to manage the data set.

For more information, see Tag .

triggers List<DatasetTrigger>

The DatasetTrigger objects that specify when the dataset is automatically updated.

versioningConfiguration DatasetVersioningConfiguration

actions DatasetAction[]

The DatasetAction objects that automatically create the dataset contents.

contentDeliveryRules DatasetContentDeliveryRule[]

When dataset contents are created they are delivered to destinations specified here.

datasetName string

The name of the dataset.

lateDataRules DatasetLateDataRule[]

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

retentionPeriod DatasetRetentionPeriod

Optional. How long, in days, message data is kept for the dataset.

tags Tag[]

Metadata which can be used to manage the data set.

For more information, see Tag .

triggers DatasetTrigger[]

The DatasetTrigger objects that specify when the dataset is automatically updated.

versioningConfiguration DatasetVersioningConfiguration

actions Sequence[DatasetActionArgs]

The DatasetAction objects that automatically create the dataset contents.

content_delivery_rules Sequence[DatasetContentDeliveryRuleArgs]

When dataset contents are created they are delivered to destinations specified here.

dataset_name str

The name of the dataset.

late_data_rules Sequence[DatasetLateDataRuleArgs]

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

retention_period DatasetRetentionPeriodArgs

Optional. How long, in days, message data is kept for the dataset.

tags Sequence[TagArgs]

Metadata which can be used to manage the data set.

For more information, see Tag .

triggers Sequence[DatasetTriggerArgs]

The DatasetTrigger objects that specify when the dataset is automatically updated.

versioning_configuration DatasetVersioningConfigurationArgs

actions List<Property Map>

The DatasetAction objects that automatically create the dataset contents.

contentDeliveryRules List<Property Map>

When dataset contents are created they are delivered to destinations specified here.

datasetName String

The name of the dataset.

lateDataRules List<Property Map>

A list of data rules that send notifications to CloudWatch, when data arrives late. To specify lateDataRules , the dataset must use a DeltaTimer filter.

retentionPeriod Property Map

Optional. How long, in days, message data is kept for the dataset.

tags List<Property Map>

Metadata which can be used to manage the data set.

For more information, see Tag .

triggers List<Property Map>

The DatasetTrigger objects that specify when the dataset is automatically updated.

versioningConfiguration Property Map

Outputs

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

AwsId string
Id string: The provider-assigned unique ID for this managed resource.

AwsId string
Id string: The provider-assigned unique ID for this managed resource.

awsId String
id String: The provider-assigned unique ID for this managed resource.

awsId string
id string: The provider-assigned unique ID for this managed resource.

aws_id str
id str: The provider-assigned unique ID for this managed resource.

awsId String
id String: The provider-assigned unique ID for this managed resource.

Supporting Types

DatasetAction, DatasetActionArgs

ActionName string: The name of the data set action by which data set contents are automatically created.
ContainerAction Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetContainerAction: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
QueryAction Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetQueryAction: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

ActionName string: The name of the data set action by which data set contents are automatically created.
ContainerAction DatasetContainerAction: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
QueryAction DatasetQueryAction: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

actionName String: The name of the data set action by which data set contents are automatically created.
containerAction DatasetContainerAction: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
queryAction DatasetQueryAction: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

actionName string: The name of the data set action by which data set contents are automatically created.
containerAction DatasetContainerAction: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
queryAction DatasetQueryAction: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

action_name str: The name of the data set action by which data set contents are automatically created.
container_action DatasetContainerAction: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
query_action DatasetQueryAction: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

actionName String: The name of the data set action by which data set contents are automatically created.
containerAction Property Map: Information which allows the system to run a containerized application in order to create the data set contents. The application must be in a Docker container along with any needed support libraries.
queryAction Property Map: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.

DatasetContainerAction, DatasetContainerActionArgs

ExecutionRoleArn string: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
Image string: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
ResourceConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetResourceConfiguration: Configuration of the resource which executes the "containerAction".
Variables List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetVariable>: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

ExecutionRoleArn string: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
Image string: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
ResourceConfiguration DatasetResourceConfiguration: Configuration of the resource which executes the "containerAction".
Variables []DatasetVariable: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

executionRoleArn String: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
image String: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
resourceConfiguration DatasetResourceConfiguration: Configuration of the resource which executes the "containerAction".
variables List<DatasetVariable>: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

executionRoleArn string: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
image string: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
resourceConfiguration DatasetResourceConfiguration: Configuration of the resource which executes the "containerAction".
variables DatasetVariable[]: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

execution_role_arn str: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
image str: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
resource_configuration DatasetResourceConfiguration: Configuration of the resource which executes the "containerAction".
variables Sequence[DatasetVariable]: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

executionRoleArn String: The ARN of the role which gives permission to the system to access needed resources in order to run the "containerAction". This includes, at minimum, permission to retrieve the data set contents which are the input to the containerized application.
image String: The ARN of the Docker container stored in your account. The Docker container contains an application and needed support libraries and is used to generate data set contents.
resourceConfiguration Property Map: Configuration of the resource which executes the "containerAction".
variables List<Property Map>: The values of variables used within the context of the execution of the containerized application (basically, parameters passed to the application). Each variable must have a name and a value given by one of "stringValue", "datasetContentVersionValue", or "outputFileUriValue".

DatasetContentDeliveryRule, DatasetContentDeliveryRuleArgs

Destination Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetContentDeliveryRuleDestination: The destination to which dataset contents are delivered.
EntryName string: The name of the dataset content delivery rules entry.

Destination DatasetContentDeliveryRuleDestination: The destination to which dataset contents are delivered.
EntryName string: The name of the dataset content delivery rules entry.

destination DatasetContentDeliveryRuleDestination: The destination to which dataset contents are delivered.
entryName String: The name of the dataset content delivery rules entry.

destination DatasetContentDeliveryRuleDestination: The destination to which dataset contents are delivered.
entryName string: The name of the dataset content delivery rules entry.

destination DatasetContentDeliveryRuleDestination: The destination to which dataset contents are delivered.
entry_name str: The name of the dataset content delivery rules entry.

destination Property Map: The destination to which dataset contents are delivered.
entryName String: The name of the dataset content delivery rules entry.

DatasetContentDeliveryRuleDestination, DatasetContentDeliveryRuleDestinationArgs

IotEventsDestinationConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetIotEventsDestinationConfiguration: Configuration information for delivery of dataset contents to AWS IoT Events .
S3DestinationConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetS3DestinationConfiguration: Configuration information for delivery of dataset contents to Amazon S3.

IotEventsDestinationConfiguration DatasetIotEventsDestinationConfiguration: Configuration information for delivery of dataset contents to AWS IoT Events .
S3DestinationConfiguration DatasetS3DestinationConfiguration: Configuration information for delivery of dataset contents to Amazon S3.

iotEventsDestinationConfiguration DatasetIotEventsDestinationConfiguration: Configuration information for delivery of dataset contents to AWS IoT Events .
s3DestinationConfiguration DatasetS3DestinationConfiguration: Configuration information for delivery of dataset contents to Amazon S3.

iotEventsDestinationConfiguration DatasetIotEventsDestinationConfiguration: Configuration information for delivery of dataset contents to AWS IoT Events .
s3DestinationConfiguration DatasetS3DestinationConfiguration: Configuration information for delivery of dataset contents to Amazon S3.

iot_events_destination_configuration DatasetIotEventsDestinationConfiguration: Configuration information for delivery of dataset contents to AWS IoT Events .
s3_destination_configuration DatasetS3DestinationConfiguration: Configuration information for delivery of dataset contents to Amazon S3.

iotEventsDestinationConfiguration Property Map: Configuration information for delivery of dataset contents to AWS IoT Events .
s3DestinationConfiguration Property Map: Configuration information for delivery of dataset contents to Amazon S3.

DatasetContentVersionValue, DatasetContentVersionValueArgs

DatasetName string: The name of the dataset whose latest contents are used as input to the notebook or application.

DatasetName string: The name of the dataset whose latest contents are used as input to the notebook or application.

datasetName String: The name of the dataset whose latest contents are used as input to the notebook or application.

datasetName string: The name of the dataset whose latest contents are used as input to the notebook or application.

dataset_name str: The name of the dataset whose latest contents are used as input to the notebook or application.

datasetName String: The name of the dataset whose latest contents are used as input to the notebook or application.

DatasetDeltaTime, DatasetDeltaTimeArgs

OffsetSeconds int: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
TimeExpression string: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

OffsetSeconds int: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
TimeExpression string: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

offsetSeconds Integer: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
timeExpression String: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

offsetSeconds number: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
timeExpression string: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

offset_seconds int: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
time_expression str: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

offsetSeconds Number: The number of seconds of estimated in-flight lag time of message data. When you create dataset contents using message data from a specified timeframe, some message data might still be in flight when processing begins, and so do not arrive in time to be processed. Use this field to make allowances for the in flight time of your message data, so that data not processed from a previous timeframe is included with the next timeframe. Otherwise, missed message data would be excluded from processing during the next timeframe too, because its timestamp places it within the previous timeframe.
timeExpression String: An expression by which the time of the message data might be determined. This can be the name of a timestamp field or a SQL expression that is used to derive the time the message data was generated.

DatasetDeltaTimeSessionWindowConfiguration, DatasetDeltaTimeSessionWindowConfigurationArgs

TimeoutInMinutes int

A time interval. You can use timeoutInMinutes so that AWS IoT Analytics can batch up late data notifications that have been generated since the last execution. AWS IoT Analytics sends one batch of notifications to Amazon CloudWatch Events at one time.

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

TimeoutInMinutes int

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

timeoutInMinutes Integer

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

timeoutInMinutes number

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

timeout_in_minutes int

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

timeoutInMinutes Number

For more information about how to write a timestamp expression, see Date and Time Functions and Operators , in the Presto 0.172 Documentation .

DatasetFilter, DatasetFilterArgs

DeltaTime Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetDeltaTime: Used to limit data to that which has arrived since the last execution of the action.

DeltaTime DatasetDeltaTime: Used to limit data to that which has arrived since the last execution of the action.

deltaTime DatasetDeltaTime: Used to limit data to that which has arrived since the last execution of the action.

deltaTime DatasetDeltaTime: Used to limit data to that which has arrived since the last execution of the action.

delta_time DatasetDeltaTime: Used to limit data to that which has arrived since the last execution of the action.

deltaTime Property Map: Used to limit data to that which has arrived since the last execution of the action.

DatasetGlueConfiguration, DatasetGlueConfigurationArgs

DatabaseName string: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
TableName string: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

DatabaseName string: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
TableName string: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

databaseName String: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
tableName String: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

databaseName string: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
tableName string: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

database_name str: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
table_name str: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

databaseName String: The name of the database in your AWS Glue Data Catalog in which the table is located. An AWS Glue Data Catalog database contains metadata tables.
tableName String: The name of the table in your AWS Glue Data Catalog that is used to perform the ETL operations. An AWS Glue Data Catalog table contains partitioned data and descriptions of data sources and targets.

DatasetIotEventsDestinationConfiguration, DatasetIotEventsDestinationConfigurationArgs

InputName string: The name of the AWS IoT Events input to which dataset contents are delivered.
RoleArn string: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

InputName string: The name of the AWS IoT Events input to which dataset contents are delivered.
RoleArn string: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

inputName String: The name of the AWS IoT Events input to which dataset contents are delivered.
roleArn String: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

inputName string: The name of the AWS IoT Events input to which dataset contents are delivered.
roleArn string: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

input_name str: The name of the AWS IoT Events input to which dataset contents are delivered.
role_arn str: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

inputName String: The name of the AWS IoT Events input to which dataset contents are delivered.
roleArn String: The ARN of the role that grants AWS IoT Analytics permission to deliver dataset contents to an AWS IoT Events input.

DatasetLateDataRule, DatasetLateDataRuleArgs

RuleConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetLateDataRuleConfiguration: The information needed to configure the late data rule.
RuleName string: The name of the late data rule.

RuleConfiguration DatasetLateDataRuleConfiguration: The information needed to configure the late data rule.
RuleName string: The name of the late data rule.

ruleConfiguration DatasetLateDataRuleConfiguration: The information needed to configure the late data rule.
ruleName String: The name of the late data rule.

ruleConfiguration DatasetLateDataRuleConfiguration: The information needed to configure the late data rule.
ruleName string: The name of the late data rule.

rule_configuration DatasetLateDataRuleConfiguration: The information needed to configure the late data rule.
rule_name str: The name of the late data rule.

ruleConfiguration Property Map: The information needed to configure the late data rule.
ruleName String: The name of the late data rule.

DatasetLateDataRuleConfiguration, DatasetLateDataRuleConfigurationArgs

DeltaTimeSessionWindowConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetDeltaTimeSessionWindowConfiguration: The information needed to configure a delta time session window.

DeltaTimeSessionWindowConfiguration DatasetDeltaTimeSessionWindowConfiguration: The information needed to configure a delta time session window.

deltaTimeSessionWindowConfiguration DatasetDeltaTimeSessionWindowConfiguration: The information needed to configure a delta time session window.

deltaTimeSessionWindowConfiguration DatasetDeltaTimeSessionWindowConfiguration: The information needed to configure a delta time session window.

delta_time_session_window_configuration DatasetDeltaTimeSessionWindowConfiguration: The information needed to configure a delta time session window.

deltaTimeSessionWindowConfiguration Property Map: The information needed to configure a delta time session window.

DatasetOutputFileUriValue, DatasetOutputFileUriValueArgs

FileName string: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

FileName string: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

fileName String: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

fileName string: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

file_name str: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

fileName String: The URI of the location where dataset contents are stored, usually the URI of a file in an S3 bucket.

DatasetQueryAction, DatasetQueryActionArgs

SqlQuery string: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
Filters List<Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetFilter>: Pre-filters applied to message data.

SqlQuery string: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
Filters []DatasetFilter: Pre-filters applied to message data.

sqlQuery String: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
filters List<DatasetFilter>: Pre-filters applied to message data.

sqlQuery string: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
filters DatasetFilter[]: Pre-filters applied to message data.

sql_query str: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
filters Sequence[DatasetFilter]: Pre-filters applied to message data.

sqlQuery String: An "SqlQueryDatasetAction" object that uses an SQL query to automatically create data set contents.
filters List<Property Map>: Pre-filters applied to message data.

DatasetResourceConfiguration, DatasetResourceConfigurationArgs

ComputeType Pulumi.AwsNative.IoTAnalytics.DatasetResourceConfigurationComputeType: The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
VolumeSizeInGb int: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

ComputeType DatasetResourceConfigurationComputeType: The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
VolumeSizeInGb int: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

computeType DatasetResourceConfigurationComputeType: The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
volumeSizeInGb Integer: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

computeType DatasetResourceConfigurationComputeType: The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
volumeSizeInGb number: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

compute_type DatasetResourceConfigurationComputeType: The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
volume_size_in_gb int: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

computeType "ACU_1" | "ACU_2": The type of the compute resource used to execute the containerAction . Possible values are: ACU_1 (vCPU=4, memory=16 GiB) or ACU_2 (vCPU=8, memory=32 GiB).
volumeSizeInGb Number: The size, in GB, of the persistent storage available to the resource instance used to execute the containerAction (min: 1, max: 50).

DatasetResourceConfigurationComputeType, DatasetResourceConfigurationComputeTypeArgs

Acu1: ACU_1
Acu2: ACU_2

DatasetResourceConfigurationComputeTypeAcu1: ACU_1
DatasetResourceConfigurationComputeTypeAcu2: ACU_2

Acu1: ACU_1
Acu2: ACU_2

Acu1: ACU_1
Acu2: ACU_2

ACU1: ACU_1
ACU2: ACU_2

"ACU_1": ACU_1
"ACU_2": ACU_2

DatasetRetentionPeriod, DatasetRetentionPeriodArgs

NumberOfDays int: The number of days that message data is kept. The unlimited parameter must be false.
Unlimited bool: If true, message data is kept indefinitely.

NumberOfDays int: The number of days that message data is kept. The unlimited parameter must be false.
Unlimited bool: If true, message data is kept indefinitely.

numberOfDays Integer: The number of days that message data is kept. The unlimited parameter must be false.
unlimited Boolean: If true, message data is kept indefinitely.

numberOfDays number: The number of days that message data is kept. The unlimited parameter must be false.
unlimited boolean: If true, message data is kept indefinitely.

number_of_days int: The number of days that message data is kept. The unlimited parameter must be false.
unlimited bool: If true, message data is kept indefinitely.

numberOfDays Number: The number of days that message data is kept. The unlimited parameter must be false.
unlimited Boolean: If true, message data is kept indefinitely.

DatasetS3DestinationConfiguration, DatasetS3DestinationConfigurationArgs

Bucket string

The name of the S3 bucket to which dataset contents are delivered.

Key string

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

RoleArn string

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

GlueConfiguration Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetGlueConfiguration

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

Bucket string

The name of the S3 bucket to which dataset contents are delivered.

Key string

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

RoleArn string

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

GlueConfiguration DatasetGlueConfiguration

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

bucket String

The name of the S3 bucket to which dataset contents are delivered.

key String

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

roleArn String

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

glueConfiguration DatasetGlueConfiguration

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

bucket string

The name of the S3 bucket to which dataset contents are delivered.

key string

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

roleArn string

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

glueConfiguration DatasetGlueConfiguration

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

bucket str

The name of the S3 bucket to which dataset contents are delivered.

key str

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

role_arn str

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

glue_configuration DatasetGlueConfiguration

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

bucket String

The name of the S3 bucket to which dataset contents are delivered.

key String

The key of the dataset contents object in an S3 bucket. Each object has a key that is a unique identifier. Each object has exactly one key.

You can create a unique key with the following options:

Use !{iotanalytics:scheduleTime} to insert the time of a scheduled SQL query run.
Use !{iotanalytics:versionId} to insert a unique hash that identifies a dataset content.
Use !{iotanalytics:creationTime} to insert the creation time of a dataset content.

The following example creates a unique key for a CSV file: dataset/mydataset/!{iotanalytics:scheduleTime}/!{iotanalytics:versionId}.csv

If you don't use !{iotanalytics:versionId} to specify the key, you might get duplicate keys. For example, you might have two dataset contents with the same scheduleTime but different versionId s. This means that one dataset content overwrites the other.

roleArn String

The ARN of the role that grants AWS IoT Analytics permission to interact with your Amazon S3 and AWS Glue resources.

glueConfiguration Property Map

Configuration information for coordination with AWS Glue , a fully managed extract, transform and load (ETL) service.

DatasetSchedule, DatasetScheduleArgs

ScheduleExpression string: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

ScheduleExpression string: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

scheduleExpression String: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

scheduleExpression string: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

schedule_expression str: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

scheduleExpression String: The expression that defines when to trigger an update. For more information, see Schedule Expressions for Rules in the Amazon CloudWatch documentation.

DatasetTrigger, DatasetTriggerArgs

Schedule Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetSchedule: The "Schedule" when the trigger is initiated.
TriggeringDataset Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetTriggeringDataset: Information about the data set whose content generation triggers the new data set content generation.

Schedule DatasetSchedule: The "Schedule" when the trigger is initiated.
TriggeringDataset DatasetTriggeringDataset: Information about the data set whose content generation triggers the new data set content generation.

schedule DatasetSchedule: The "Schedule" when the trigger is initiated.
triggeringDataset DatasetTriggeringDataset: Information about the data set whose content generation triggers the new data set content generation.

schedule DatasetSchedule: The "Schedule" when the trigger is initiated.
triggeringDataset DatasetTriggeringDataset: Information about the data set whose content generation triggers the new data set content generation.

schedule DatasetSchedule: The "Schedule" when the trigger is initiated.
triggering_dataset DatasetTriggeringDataset: Information about the data set whose content generation triggers the new data set content generation.

schedule Property Map: The "Schedule" when the trigger is initiated.
triggeringDataset Property Map: Information about the data set whose content generation triggers the new data set content generation.

DatasetTriggeringDataset, DatasetTriggeringDatasetArgs

DatasetName string: The name of the data set whose content generation triggers the new data set content generation.

DatasetName string: The name of the data set whose content generation triggers the new data set content generation.

datasetName String: The name of the data set whose content generation triggers the new data set content generation.

datasetName string: The name of the data set whose content generation triggers the new data set content generation.

dataset_name str: The name of the data set whose content generation triggers the new data set content generation.

datasetName String: The name of the data set whose content generation triggers the new data set content generation.

DatasetVariable, DatasetVariableArgs

VariableName string: The name of the variable.
DatasetContentVersionValue Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetContentVersionValue: The value of the variable as a structure that specifies a dataset content version.
DoubleValue double: The value of the variable as a double (numeric).
OutputFileUriValue Pulumi.AwsNative.IoTAnalytics.Inputs.DatasetOutputFileUriValue: The value of the variable as a structure that specifies an output file URI.
StringValue string: The value of the variable as a string.

VariableName string: The name of the variable.
DatasetContentVersionValue DatasetContentVersionValue: The value of the variable as a structure that specifies a dataset content version.
DoubleValue float64: The value of the variable as a double (numeric).
OutputFileUriValue DatasetOutputFileUriValue: The value of the variable as a structure that specifies an output file URI.
StringValue string: The value of the variable as a string.

variableName String: The name of the variable.
datasetContentVersionValue DatasetContentVersionValue: The value of the variable as a structure that specifies a dataset content version.
doubleValue Double: The value of the variable as a double (numeric).
outputFileUriValue DatasetOutputFileUriValue: The value of the variable as a structure that specifies an output file URI.
stringValue String: The value of the variable as a string.

variableName string: The name of the variable.
datasetContentVersionValue DatasetContentVersionValue: The value of the variable as a structure that specifies a dataset content version.
doubleValue number: The value of the variable as a double (numeric).
outputFileUriValue DatasetOutputFileUriValue: The value of the variable as a structure that specifies an output file URI.
stringValue string: The value of the variable as a string.

variable_name str: The name of the variable.
dataset_content_version_value DatasetContentVersionValue: The value of the variable as a structure that specifies a dataset content version.
double_value float: The value of the variable as a double (numeric).
output_file_uri_value DatasetOutputFileUriValue: The value of the variable as a structure that specifies an output file URI.
string_value str: The value of the variable as a string.

variableName String: The name of the variable.
datasetContentVersionValue Property Map: The value of the variable as a structure that specifies a dataset content version.
doubleValue Number: The value of the variable as a double (numeric).
outputFileUriValue Property Map: The value of the variable as a structure that specifies an output file URI.
stringValue String: The value of the variable as a string.

DatasetVersioningConfiguration, DatasetVersioningConfigurationArgs

MaxVersions int: How many versions of dataset contents are kept. The unlimited parameter must be false .
Unlimited bool: If true, unlimited versions of dataset contents are kept.

MaxVersions int: How many versions of dataset contents are kept. The unlimited parameter must be false .
Unlimited bool: If true, unlimited versions of dataset contents are kept.

maxVersions Integer: How many versions of dataset contents are kept. The unlimited parameter must be false .
unlimited Boolean: If true, unlimited versions of dataset contents are kept.

maxVersions number: How many versions of dataset contents are kept. The unlimited parameter must be false .
unlimited boolean: If true, unlimited versions of dataset contents are kept.

max_versions int: How many versions of dataset contents are kept. The unlimited parameter must be false .
unlimited bool: If true, unlimited versions of dataset contents are kept.

maxVersions Number: How many versions of dataset contents are kept. The unlimited parameter must be false .
unlimited Boolean: If true, unlimited versions of dataset contents are kept.

Tag, TagArgs

Key string: The key name of the tag
Value string: The value of the tag

Key string: The key name of the tag
Value string: The value of the tag

key String: The key name of the tag
value String: The value of the tag

key string: The key name of the tag
value string: The value of the tag

key str: The key name of the tag
value str: The value of the tag

key String: The key name of the tag
value String: The value of the tag

Package Details

Repository: AWS Native pulumi/pulumi-aws-native
License: Apache-2.0

AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.112.0 published on Wednesday, Jul 24, 2024 by Pulumi

pulumi/pulumi-aws-native

aws-native.iotanalytics.Dataset

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Example Usage

Example

Example

Example

Example

Create Dataset Resource

Constructor syntax

Parameters

Dataset Resource Properties

Inputs

Outputs

Supporting Types

DatasetAction, DatasetActionArgs

DatasetContainerAction, DatasetContainerActionArgs

DatasetContentDeliveryRule, DatasetContentDeliveryRuleArgs

DatasetContentDeliveryRuleDestination, DatasetContentDeliveryRuleDestinationArgs

DatasetContentVersionValue, DatasetContentVersionValueArgs

DatasetDeltaTime, DatasetDeltaTimeArgs

DatasetDeltaTimeSessionWindowConfiguration, DatasetDeltaTimeSessionWindowConfigurationArgs

DatasetFilter, DatasetFilterArgs

DatasetGlueConfiguration, DatasetGlueConfigurationArgs

DatasetIotEventsDestinationConfiguration, DatasetIotEventsDestinationConfigurationArgs

DatasetLateDataRule, DatasetLateDataRuleArgs

DatasetLateDataRuleConfiguration, DatasetLateDataRuleConfigurationArgs

DatasetOutputFileUriValue, DatasetOutputFileUriValueArgs

DatasetQueryAction, DatasetQueryActionArgs

DatasetResourceConfiguration, DatasetResourceConfigurationArgs

DatasetResourceConfigurationComputeType, DatasetResourceConfigurationComputeTypeArgs

DatasetRetentionPeriod, DatasetRetentionPeriodArgs

DatasetS3DestinationConfiguration, DatasetS3DestinationConfigurationArgs

DatasetSchedule, DatasetScheduleArgs

DatasetTrigger, DatasetTriggerArgs

DatasetTriggeringDataset, DatasetTriggeringDatasetArgs

DatasetVariable, DatasetVariableArgs

DatasetVersioningConfiguration, DatasetVersioningConfigurationArgs

Tag, TagArgs

Package Details

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