lookoutequipment

package module
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Published: Sep 17, 2021 License: Apache-2.0 Imports: 31 Imported by: 0

Documentation

Overview

Package lookoutequipment provides the API client, operations, and parameter types for Amazon Lookout for Equipment.

Amazon Lookout for Equipment is a machine learning service that uses advanced analytics to identify anomalies in machines from sensor data for use in predictive maintenance.

Index

Constants

View Source
const ServiceAPIVersion = "2020-12-15"
View Source
const ServiceID = "LookoutEquipment"

Variables

This section is empty.

Functions

func NewDefaultEndpointResolver

func NewDefaultEndpointResolver() *internalendpoints.Resolver

NewDefaultEndpointResolver constructs a new service endpoint resolver

func WithAPIOptions

func WithAPIOptions(optFns ...func(*middleware.Stack) error) func(*Options)

WithAPIOptions returns a functional option for setting the Client's APIOptions option.

func WithEndpointResolver

func WithEndpointResolver(v EndpointResolver) func(*Options)

WithEndpointResolver returns a functional option for setting the Client's EndpointResolver option.

Types

type Client

type Client struct {
	// contains filtered or unexported fields
}

Client provides the API client to make operations call for Amazon Lookout for Equipment.

func New

func New(options Options, optFns ...func(*Options)) *Client

New returns an initialized Client based on the functional options. Provide additional functional options to further configure the behavior of the client, such as changing the client's endpoint or adding custom middleware behavior.

func NewFromConfig

func NewFromConfig(cfg aws.Config, optFns ...func(*Options)) *Client

NewFromConfig returns a new client from the provided config.

func (*Client) CreateDataset

func (c *Client) CreateDataset(ctx context.Context, params *CreateDatasetInput, optFns ...func(*Options)) (*CreateDatasetOutput, error)

Creates a container for a collection of data being ingested for analysis. The dataset contains the metadata describing where the data is and what the data actually looks like. In other words, it contains the location of the data source, the data schema, and other information. A dataset also contains any tags associated with the ingested data.

func (*Client) CreateInferenceScheduler

func (c *Client) CreateInferenceScheduler(ctx context.Context, params *CreateInferenceSchedulerInput, optFns ...func(*Options)) (*CreateInferenceSchedulerOutput, error)

Creates a scheduled inference. Scheduling an inference is setting up a continuous real-time inference plan to analyze new measurement data. When setting up the schedule, you provide an S3 bucket location for the input data, assign it a delimiter between separate entries in the data, set an offset delay if desired, and set the frequency of inferencing. You must also provide an S3 bucket location for the output data.

func (*Client) CreateModel

func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error)

Creates an ML model for data inference. A machine-learning (ML) model is a mathematical model that finds patterns in your data. In Amazon Lookout for Equipment, the model learns the patterns of normal behavior and detects abnormal behavior that could be potential equipment failure (or maintenance events). The models are made by analyzing normal data and abnormalities in machine behavior that have already occurred. Your model is trained using a portion of the data from your dataset and uses that data to learn patterns of normal behavior and abnormal patterns that lead to equipment failure. Another portion of the data is used to evaluate the model's accuracy.

func (*Client) DeleteDataset

func (c *Client) DeleteDataset(ctx context.Context, params *DeleteDatasetInput, optFns ...func(*Options)) (*DeleteDatasetOutput, error)

Deletes a dataset and associated artifacts. The operation will check to see if any inference scheduler or data ingestion job is currently using the dataset, and if there isn't, the dataset, its metadata, and any associated data stored in S3 will be deleted. This does not affect any models that used this dataset for training and evaluation, but does prevent it from being used in the future.

func (*Client) DeleteInferenceScheduler

func (c *Client) DeleteInferenceScheduler(ctx context.Context, params *DeleteInferenceSchedulerInput, optFns ...func(*Options)) (*DeleteInferenceSchedulerOutput, error)

Deletes an inference scheduler that has been set up. Already processed output results are not affected.

func (*Client) DeleteModel

func (c *Client) DeleteModel(ctx context.Context, params *DeleteModelInput, optFns ...func(*Options)) (*DeleteModelOutput, error)

Deletes an ML model currently available for Amazon Lookout for Equipment. This will prevent it from being used with an inference scheduler, even one that is already set up.

func (*Client) DescribeDataIngestionJob

func (c *Client) DescribeDataIngestionJob(ctx context.Context, params *DescribeDataIngestionJobInput, optFns ...func(*Options)) (*DescribeDataIngestionJobOutput, error)

Provides information on a specific data ingestion job such as creation time, dataset ARN, status, and so on.

func (*Client) DescribeDataset

func (c *Client) DescribeDataset(ctx context.Context, params *DescribeDatasetInput, optFns ...func(*Options)) (*DescribeDatasetOutput, error)

Provides a JSON description of the data that is in each time series dataset, including names, column names, and data types.

func (*Client) DescribeInferenceScheduler

func (c *Client) DescribeInferenceScheduler(ctx context.Context, params *DescribeInferenceSchedulerInput, optFns ...func(*Options)) (*DescribeInferenceSchedulerOutput, error)

Specifies information about the inference scheduler being used, including name, model, status, and associated metadata

func (*Client) DescribeModel

func (c *Client) DescribeModel(ctx context.Context, params *DescribeModelInput, optFns ...func(*Options)) (*DescribeModelOutput, error)

Provides a JSON containing the overall information about a specific ML model, including model name and ARN, dataset, training and evaluation information, status, and so on.

func (*Client) ListDataIngestionJobs

func (c *Client) ListDataIngestionJobs(ctx context.Context, params *ListDataIngestionJobsInput, optFns ...func(*Options)) (*ListDataIngestionJobsOutput, error)

Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.

func (*Client) ListDatasets

func (c *Client) ListDatasets(ctx context.Context, params *ListDatasetsInput, optFns ...func(*Options)) (*ListDatasetsOutput, error)

Lists all datasets currently available in your account, filtering on the dataset name.

func (*Client) ListInferenceExecutions

func (c *Client) ListInferenceExecutions(ctx context.Context, params *ListInferenceExecutionsInput, optFns ...func(*Options)) (*ListInferenceExecutionsOutput, error)

Lists all inference executions that have been performed by the specified inference scheduler.

func (*Client) ListInferenceSchedulers

func (c *Client) ListInferenceSchedulers(ctx context.Context, params *ListInferenceSchedulersInput, optFns ...func(*Options)) (*ListInferenceSchedulersOutput, error)

Retrieves a list of all inference schedulers currently available for your account.

func (*Client) ListModels

func (c *Client) ListModels(ctx context.Context, params *ListModelsInput, optFns ...func(*Options)) (*ListModelsOutput, error)

Generates a list of all models in the account, including model name and ARN, dataset, and status.

func (*Client) ListTagsForResource

func (c *Client) ListTagsForResource(ctx context.Context, params *ListTagsForResourceInput, optFns ...func(*Options)) (*ListTagsForResourceOutput, error)

Lists all the tags for a specified resource, including key and value.

func (*Client) StartDataIngestionJob

func (c *Client) StartDataIngestionJob(ctx context.Context, params *StartDataIngestionJobInput, optFns ...func(*Options)) (*StartDataIngestionJobOutput, error)

Starts a data ingestion job. Amazon Lookout for Equipment returns the job status.

func (*Client) StartInferenceScheduler

func (c *Client) StartInferenceScheduler(ctx context.Context, params *StartInferenceSchedulerInput, optFns ...func(*Options)) (*StartInferenceSchedulerOutput, error)

Starts an inference scheduler.

func (*Client) StopInferenceScheduler

func (c *Client) StopInferenceScheduler(ctx context.Context, params *StopInferenceSchedulerInput, optFns ...func(*Options)) (*StopInferenceSchedulerOutput, error)

Stops an inference scheduler.

func (*Client) TagResource

func (c *Client) TagResource(ctx context.Context, params *TagResourceInput, optFns ...func(*Options)) (*TagResourceOutput, error)

Associates a given tag to a resource in your account. A tag is a key-value pair which can be added to an Amazon Lookout for Equipment resource as metadata. Tags can be used for organizing your resources as well as helping you to search and filter by tag. Multiple tags can be added to a resource, either when you create it, or later. Up to 50 tags can be associated with each resource.

func (*Client) UntagResource

func (c *Client) UntagResource(ctx context.Context, params *UntagResourceInput, optFns ...func(*Options)) (*UntagResourceOutput, error)

Removes a specific tag from a given resource. The tag is specified by its key.

func (*Client) UpdateInferenceScheduler

func (c *Client) UpdateInferenceScheduler(ctx context.Context, params *UpdateInferenceSchedulerInput, optFns ...func(*Options)) (*UpdateInferenceSchedulerOutput, error)

Updates an inference scheduler.

type CreateDatasetInput

type CreateDatasetInput struct {

	// A unique identifier for the request. If you do not set the client request token,
	// Amazon Lookout for Equipment generates one.
	//
	// This member is required.
	ClientToken *string

	// The name of the dataset being created.
	//
	// This member is required.
	DatasetName *string

	// A JSON description of the data that is in each time series dataset, including
	// names, column names, and data types.
	//
	// This member is required.
	DatasetSchema *types.DatasetSchema

	// Provides the identifier of the KMS key used to encrypt dataset data by Amazon
	// Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Any tags associated with the ingested data described in the dataset.
	Tags []types.Tag
	// contains filtered or unexported fields
}

type CreateDatasetOutput

type CreateDatasetOutput struct {

	// The Amazon Resource Name (ARN) of the dataset being created.
	DatasetArn *string

	// The name of the dataset being created.
	DatasetName *string

	// Indicates the status of the CreateDataset operation.
	Status types.DatasetStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type CreateInferenceSchedulerInput

type CreateInferenceSchedulerInput struct {

	// A unique identifier for the request. If you do not set the client request token,
	// Amazon Lookout for Equipment generates one.
	//
	// This member is required.
	ClientToken *string

	// Specifies configuration information for the input data for the inference
	// scheduler, including delimiter, format, and dataset location.
	//
	// This member is required.
	DataInputConfiguration *types.InferenceInputConfiguration

	// Specifies configuration information for the output results for the inference
	// scheduler, including the S3 location for the output.
	//
	// This member is required.
	DataOutputConfiguration *types.InferenceOutputConfiguration

	// How often data is uploaded to the source S3 bucket for the input data. The value
	// chosen is the length of time between data uploads. For instance, if you select 5
	// minutes, Amazon Lookout for Equipment will upload the real-time data to the
	// source bucket once every 5 minutes. This frequency also determines how often
	// Amazon Lookout for Equipment starts a scheduled inference on your data. In this
	// example, it starts once every 5 minutes.
	//
	// This member is required.
	DataUploadFrequency types.DataUploadFrequency

	// The name of the inference scheduler being created.
	//
	// This member is required.
	InferenceSchedulerName *string

	// The name of the previously trained ML model being used to create the inference
	// scheduler.
	//
	// This member is required.
	ModelName *string

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source being used for the inference.
	//
	// This member is required.
	RoleArn *string

	// A period of time (in minutes) by which inference on the data is delayed after
	// the data starts. For instance, if you select an offset delay time of five
	// minutes, inference will not begin on the data until the first data measurement
	// after the five minute mark. For example, if five minutes is selected, the
	// inference scheduler will wake up at the configured frequency with the additional
	// five minute delay time to check the customer S3 bucket. The customer can upload
	// data at the same frequency and they don't need to stop and restart the scheduler
	// when uploading new data.
	DataDelayOffsetInMinutes *int64

	// Provides the identifier of the KMS key used to encrypt inference scheduler data
	// by Amazon Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Any tags associated with the inference scheduler.
	Tags []types.Tag
	// contains filtered or unexported fields
}

type CreateInferenceSchedulerOutput

type CreateInferenceSchedulerOutput struct {

	// The Amazon Resource Name (ARN) of the inference scheduler being created.
	InferenceSchedulerArn *string

	// The name of inference scheduler being created.
	InferenceSchedulerName *string

	// Indicates the status of the CreateInferenceScheduler operation.
	Status types.InferenceSchedulerStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type CreateModelInput

type CreateModelInput struct {

	// A unique identifier for the request. If you do not set the client request token,
	// Amazon Lookout for Equipment generates one.
	//
	// This member is required.
	ClientToken *string

	// The name of the dataset for the ML model being created.
	//
	// This member is required.
	DatasetName *string

	// The name for the ML model to be created.
	//
	// This member is required.
	ModelName *string

	// The configuration is the TargetSamplingRate, which is the sampling rate of the
	// data after post processing by Amazon Lookout for Equipment. For example, if you
	// provide data that has been collected at a 1 second level and you want the system
	// to resample the data at a 1 minute rate before training, the TargetSamplingRate
	// is 1 minute. When providing a value for the TargetSamplingRate, you must attach
	// the prefix "PT" to the rate you want. The value for a 1 second rate is therefore
	// PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate
	// is PT1H
	DataPreProcessingConfiguration *types.DataPreProcessingConfiguration

	// The data schema for the ML model being created.
	DatasetSchema *types.DatasetSchema

	// Indicates the time reference in the dataset that should be used to end the
	// subset of evaluation data for the ML model.
	EvaluationDataEndTime *time.Time

	// Indicates the time reference in the dataset that should be used to begin the
	// subset of evaluation data for the ML model.
	EvaluationDataStartTime *time.Time

	// The input configuration for the labels being used for the ML model that's being
	// created.
	LabelsInputConfiguration *types.LabelsInputConfiguration

	// Indicates that the asset associated with this sensor has been shut off. As long
	// as this condition is met, Lookout for Equipment will not use data from this
	// asset for training, evaluation, or inference.
	OffCondition *string

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source being used to create the ML model.
	RoleArn *string

	// Provides the identifier of the KMS key used to encrypt model data by Amazon
	// Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Any tags associated with the ML model being created.
	Tags []types.Tag

	// Indicates the time reference in the dataset that should be used to end the
	// subset of training data for the ML model.
	TrainingDataEndTime *time.Time

	// Indicates the time reference in the dataset that should be used to begin the
	// subset of training data for the ML model.
	TrainingDataStartTime *time.Time
	// contains filtered or unexported fields
}

type CreateModelOutput

type CreateModelOutput struct {

	// The Amazon Resource Name (ARN) of the model being created.
	ModelArn *string

	// Indicates the status of the CreateModel operation.
	Status types.ModelStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DeleteDatasetInput

type DeleteDatasetInput struct {

	// The name of the dataset to be deleted.
	//
	// This member is required.
	DatasetName *string
	// contains filtered or unexported fields
}

type DeleteDatasetOutput

type DeleteDatasetOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DeleteInferenceSchedulerInput

type DeleteInferenceSchedulerInput struct {

	// The name of the inference scheduler to be deleted.
	//
	// This member is required.
	InferenceSchedulerName *string
	// contains filtered or unexported fields
}

type DeleteInferenceSchedulerOutput

type DeleteInferenceSchedulerOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DeleteModelInput

type DeleteModelInput struct {

	// The name of the ML model to be deleted.
	//
	// This member is required.
	ModelName *string
	// contains filtered or unexported fields
}

type DeleteModelOutput

type DeleteModelOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DescribeDataIngestionJobInput

type DescribeDataIngestionJobInput struct {

	// The job ID of the data ingestion job.
	//
	// This member is required.
	JobId *string
	// contains filtered or unexported fields
}

type DescribeDataIngestionJobOutput

type DescribeDataIngestionJobOutput struct {

	// The time at which the data ingestion job was created.
	CreatedAt *time.Time

	// The Amazon Resource Name (ARN) of the dataset being used in the data ingestion
	// job.
	DatasetArn *string

	// Specifies the reason for failure when a data ingestion job has failed.
	FailedReason *string

	// Specifies the S3 location configuration for the data input for the data
	// ingestion job.
	IngestionInputConfiguration *types.IngestionInputConfiguration

	// Indicates the job ID of the data ingestion job.
	JobId *string

	// The Amazon Resource Name (ARN) of an IAM role with permission to access the data
	// source being ingested.
	RoleArn *string

	// Indicates the status of the DataIngestionJob operation.
	Status types.IngestionJobStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DescribeDatasetInput

type DescribeDatasetInput struct {

	// The name of the dataset to be described.
	//
	// This member is required.
	DatasetName *string
	// contains filtered or unexported fields
}

type DescribeDatasetOutput

type DescribeDatasetOutput struct {

	// Specifies the time the dataset was created in Amazon Lookout for Equipment.
	CreatedAt *time.Time

	// The Amazon Resource Name (ARN) of the dataset being described.
	DatasetArn *string

	// The name of the dataset being described.
	DatasetName *string

	// Specifies the S3 location configuration for the data input for the data
	// ingestion job.
	IngestionInputConfiguration *types.IngestionInputConfiguration

	// Specifies the time the dataset was last updated, if it was.
	LastUpdatedAt *time.Time

	// A JSON description of the data that is in each time series dataset, including
	// names, column names, and data types.
	//
	// This value conforms to the media type: application/json
	Schema *string

	// Provides the identifier of the KMS key used to encrypt dataset data by Amazon
	// Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Indicates the status of the dataset.
	Status types.DatasetStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DescribeInferenceSchedulerInput

type DescribeInferenceSchedulerInput struct {

	// The name of the inference scheduler being described.
	//
	// This member is required.
	InferenceSchedulerName *string
	// contains filtered or unexported fields
}

type DescribeInferenceSchedulerOutput

type DescribeInferenceSchedulerOutput struct {

	// Specifies the time at which the inference scheduler was created.
	CreatedAt *time.Time

	// A period of time (in minutes) by which inference on the data is delayed after
	// the data starts. For instance, if you select an offset delay time of five
	// minutes, inference will not begin on the data until the first data measurement
	// after the five minute mark. For example, if five minutes is selected, the
	// inference scheduler will wake up at the configured frequency with the additional
	// five minute delay time to check the customer S3 bucket. The customer can upload
	// data at the same frequency and they don't need to stop and restart the scheduler
	// when uploading new data.
	DataDelayOffsetInMinutes *int64

	// Specifies configuration information for the input data for the inference
	// scheduler, including delimiter, format, and dataset location.
	DataInputConfiguration *types.InferenceInputConfiguration

	// Specifies information for the output results for the inference scheduler,
	// including the output S3 location.
	DataOutputConfiguration *types.InferenceOutputConfiguration

	// Specifies how often data is uploaded to the source S3 bucket for the input data.
	// This value is the length of time between data uploads. For instance, if you
	// select 5 minutes, Amazon Lookout for Equipment will upload the real-time data to
	// the source bucket once every 5 minutes. This frequency also determines how often
	// Amazon Lookout for Equipment starts a scheduled inference on your data. In this
	// example, it starts once every 5 minutes.
	DataUploadFrequency types.DataUploadFrequency

	// The Amazon Resource Name (ARN) of the inference scheduler being described.
	InferenceSchedulerArn *string

	// The name of the inference scheduler being described.
	InferenceSchedulerName *string

	// The Amazon Resource Name (ARN) of the ML model of the inference scheduler being
	// described.
	ModelArn *string

	// The name of the ML model of the inference scheduler being described.
	ModelName *string

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source for the inference scheduler being described.
	RoleArn *string

	// Provides the identifier of the KMS key used to encrypt inference scheduler data
	// by Amazon Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Indicates the status of the inference scheduler.
	Status types.InferenceSchedulerStatus

	// Specifies the time at which the inference scheduler was last updated, if it was.
	UpdatedAt *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type DescribeModelInput

type DescribeModelInput struct {

	// The name of the ML model to be described.
	//
	// This member is required.
	ModelName *string
	// contains filtered or unexported fields
}

type DescribeModelOutput

type DescribeModelOutput struct {

	// Indicates the time and date at which the ML model was created.
	CreatedAt *time.Time

	// The configuration is the TargetSamplingRate, which is the sampling rate of the
	// data after post processing by Amazon Lookout for Equipment. For example, if you
	// provide data that has been collected at a 1 second level and you want the system
	// to resample the data at a 1 minute rate before training, the TargetSamplingRate
	// is 1 minute. When providing a value for the TargetSamplingRate, you must attach
	// the prefix "PT" to the rate you want. The value for a 1 second rate is therefore
	// PT1S, the value for a 15 minute rate is PT15M, and the value for a 1 hour rate
	// is PT1H
	DataPreProcessingConfiguration *types.DataPreProcessingConfiguration

	// The Amazon Resouce Name (ARN) of the dataset used to create the ML model being
	// described.
	DatasetArn *string

	// The name of the dataset being used by the ML being described.
	DatasetName *string

	// Indicates the time reference in the dataset that was used to end the subset of
	// evaluation data for the ML model.
	EvaluationDataEndTime *time.Time

	// Indicates the time reference in the dataset that was used to begin the subset of
	// evaluation data for the ML model.
	EvaluationDataStartTime *time.Time

	// If the training of the ML model failed, this indicates the reason for that
	// failure.
	FailedReason *string

	// Specifies configuration information about the labels input, including its S3
	// location.
	LabelsInputConfiguration *types.LabelsInputConfiguration

	// Indicates the last time the ML model was updated. The type of update is not
	// specified.
	LastUpdatedTime *time.Time

	// The Amazon Resource Name (ARN) of the ML model being described.
	ModelArn *string

	// The Model Metrics show an aggregated summary of the model's performance within
	// the evaluation time range. This is the JSON content of the metrics created when
	// evaluating the model.
	//
	// This value conforms to the media type: application/json
	ModelMetrics *string

	// The name of the ML model being described.
	ModelName *string

	// Indicates that the asset associated with this sensor has been shut off. As long
	// as this condition is met, Lookout for Equipment will not use data from this
	// asset for training, evaluation, or inference.
	OffCondition *string

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source for the ML model being described.
	RoleArn *string

	// A JSON description of the data that is in each time series dataset, including
	// names, column names, and data types.
	//
	// This value conforms to the media type: application/json
	Schema *string

	// Provides the identifier of the KMS key used to encrypt model data by Amazon
	// Lookout for Equipment.
	ServerSideKmsKeyId *string

	// Specifies the current status of the model being described. Status describes the
	// status of the most recent action of the model.
	Status types.ModelStatus

	// Indicates the time reference in the dataset that was used to end the subset of
	// training data for the ML model.
	TrainingDataEndTime *time.Time

	// Indicates the time reference in the dataset that was used to begin the subset of
	// training data for the ML model.
	TrainingDataStartTime *time.Time

	// Indicates the time at which the training of the ML model was completed.
	TrainingExecutionEndTime *time.Time

	// Indicates the time at which the training of the ML model began.
	TrainingExecutionStartTime *time.Time

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type EndpointResolver

type EndpointResolver interface {
	ResolveEndpoint(region string, options EndpointResolverOptions) (aws.Endpoint, error)
}

EndpointResolver interface for resolving service endpoints.

func EndpointResolverFromURL

func EndpointResolverFromURL(url string, optFns ...func(*aws.Endpoint)) EndpointResolver

EndpointResolverFromURL returns an EndpointResolver configured using the provided endpoint url. By default, the resolved endpoint resolver uses the client region as signing region, and the endpoint source is set to EndpointSourceCustom.You can provide functional options to configure endpoint values for the resolved endpoint.

type EndpointResolverFunc

type EndpointResolverFunc func(region string, options EndpointResolverOptions) (aws.Endpoint, error)

EndpointResolverFunc is a helper utility that wraps a function so it satisfies the EndpointResolver interface. This is useful when you want to add additional endpoint resolving logic, or stub out specific endpoints with custom values.

func (EndpointResolverFunc) ResolveEndpoint

func (fn EndpointResolverFunc) ResolveEndpoint(region string, options EndpointResolverOptions) (endpoint aws.Endpoint, err error)

type EndpointResolverOptions

type EndpointResolverOptions = internalendpoints.Options

EndpointResolverOptions is the service endpoint resolver options

type HTTPClient

type HTTPClient interface {
	Do(*http.Request) (*http.Response, error)
}

type HTTPSignerV4

type HTTPSignerV4 interface {
	SignHTTP(ctx context.Context, credentials aws.Credentials, r *http.Request, payloadHash string, service string, region string, signingTime time.Time, optFns ...func(*v4.SignerOptions)) error
}

type IdempotencyTokenProvider

type IdempotencyTokenProvider interface {
	GetIdempotencyToken() (string, error)
}

IdempotencyTokenProvider interface for providing idempotency token

type ListDataIngestionJobsAPIClient

type ListDataIngestionJobsAPIClient interface {
	ListDataIngestionJobs(context.Context, *ListDataIngestionJobsInput, ...func(*Options)) (*ListDataIngestionJobsOutput, error)
}

ListDataIngestionJobsAPIClient is a client that implements the ListDataIngestionJobs operation.

type ListDataIngestionJobsInput

type ListDataIngestionJobsInput struct {

	// The name of the dataset being used for the data ingestion job.
	DatasetName *string

	// Specifies the maximum number of data ingestion jobs to list.
	MaxResults *int32

	// An opaque pagination token indicating where to continue the listing of data
	// ingestion jobs.
	NextToken *string

	// Indicates the status of the data ingestion job.
	Status types.IngestionJobStatus
	// contains filtered or unexported fields
}

type ListDataIngestionJobsOutput

type ListDataIngestionJobsOutput struct {

	// Specifies information about the specific data ingestion job, including dataset
	// name and status.
	DataIngestionJobSummaries []types.DataIngestionJobSummary

	// An opaque pagination token indicating where to continue the listing of data
	// ingestion jobs.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type ListDataIngestionJobsPaginator

type ListDataIngestionJobsPaginator struct {
	// contains filtered or unexported fields
}

ListDataIngestionJobsPaginator is a paginator for ListDataIngestionJobs

func NewListDataIngestionJobsPaginator

NewListDataIngestionJobsPaginator returns a new ListDataIngestionJobsPaginator

func (*ListDataIngestionJobsPaginator) HasMorePages

func (p *ListDataIngestionJobsPaginator) HasMorePages() bool

HasMorePages returns a boolean indicating whether more pages are available

func (*ListDataIngestionJobsPaginator) NextPage

NextPage retrieves the next ListDataIngestionJobs page.

type ListDataIngestionJobsPaginatorOptions

type ListDataIngestionJobsPaginatorOptions struct {
	// Specifies the maximum number of data ingestion jobs to list.
	Limit int32

	// Set to true if pagination should stop if the service returns a pagination token
	// that matches the most recent token provided to the service.
	StopOnDuplicateToken bool
}

ListDataIngestionJobsPaginatorOptions is the paginator options for ListDataIngestionJobs

type ListDatasetsAPIClient

type ListDatasetsAPIClient interface {
	ListDatasets(context.Context, *ListDatasetsInput, ...func(*Options)) (*ListDatasetsOutput, error)
}

ListDatasetsAPIClient is a client that implements the ListDatasets operation.

type ListDatasetsInput

type ListDatasetsInput struct {

	// The beginning of the name of the datasets to be listed.
	DatasetNameBeginsWith *string

	// Specifies the maximum number of datasets to list.
	MaxResults *int32

	// An opaque pagination token indicating where to continue the listing of datasets.
	NextToken *string
	// contains filtered or unexported fields
}

type ListDatasetsOutput

type ListDatasetsOutput struct {

	// Provides information about the specified dataset, including creation time,
	// dataset ARN, and status.
	DatasetSummaries []types.DatasetSummary

	// An opaque pagination token indicating where to continue the listing of datasets.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type ListDatasetsPaginator

type ListDatasetsPaginator struct {
	// contains filtered or unexported fields
}

ListDatasetsPaginator is a paginator for ListDatasets

func NewListDatasetsPaginator

func NewListDatasetsPaginator(client ListDatasetsAPIClient, params *ListDatasetsInput, optFns ...func(*ListDatasetsPaginatorOptions)) *ListDatasetsPaginator

NewListDatasetsPaginator returns a new ListDatasetsPaginator

func (*ListDatasetsPaginator) HasMorePages

func (p *ListDatasetsPaginator) HasMorePages() bool

HasMorePages returns a boolean indicating whether more pages are available

func (*ListDatasetsPaginator) NextPage

func (p *ListDatasetsPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListDatasetsOutput, error)

NextPage retrieves the next ListDatasets page.

type ListDatasetsPaginatorOptions

type ListDatasetsPaginatorOptions struct {
	// Specifies the maximum number of datasets to list.
	Limit int32

	// Set to true if pagination should stop if the service returns a pagination token
	// that matches the most recent token provided to the service.
	StopOnDuplicateToken bool
}

ListDatasetsPaginatorOptions is the paginator options for ListDatasets

type ListInferenceExecutionsAPIClient

type ListInferenceExecutionsAPIClient interface {
	ListInferenceExecutions(context.Context, *ListInferenceExecutionsInput, ...func(*Options)) (*ListInferenceExecutionsOutput, error)
}

ListInferenceExecutionsAPIClient is a client that implements the ListInferenceExecutions operation.

type ListInferenceExecutionsInput

type ListInferenceExecutionsInput struct {

	// The name of the inference scheduler for the inference execution listed.
	//
	// This member is required.
	InferenceSchedulerName *string

	// The time reference in the inferenced dataset before which Amazon Lookout for
	// Equipment stopped the inference execution.
	DataEndTimeBefore *time.Time

	// The time reference in the inferenced dataset after which Amazon Lookout for
	// Equipment started the inference execution.
	DataStartTimeAfter *time.Time

	// Specifies the maximum number of inference executions to list.
	MaxResults *int32

	// An opaque pagination token indicating where to continue the listing of inference
	// executions.
	NextToken *string

	// The status of the inference execution.
	Status types.InferenceExecutionStatus
	// contains filtered or unexported fields
}

type ListInferenceExecutionsOutput

type ListInferenceExecutionsOutput struct {

	// Provides an array of information about the individual inference executions
	// returned from the ListInferenceExecutions operation, including model used,
	// inference scheduler, data configuration, and so on.
	InferenceExecutionSummaries []types.InferenceExecutionSummary

	// An opaque pagination token indicating where to continue the listing of inference
	// executions.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type ListInferenceExecutionsPaginator

type ListInferenceExecutionsPaginator struct {
	// contains filtered or unexported fields
}

ListInferenceExecutionsPaginator is a paginator for ListInferenceExecutions

func NewListInferenceExecutionsPaginator

NewListInferenceExecutionsPaginator returns a new ListInferenceExecutionsPaginator

func (*ListInferenceExecutionsPaginator) HasMorePages

func (p *ListInferenceExecutionsPaginator) HasMorePages() bool

HasMorePages returns a boolean indicating whether more pages are available

func (*ListInferenceExecutionsPaginator) NextPage

NextPage retrieves the next ListInferenceExecutions page.

type ListInferenceExecutionsPaginatorOptions

type ListInferenceExecutionsPaginatorOptions struct {
	// Specifies the maximum number of inference executions to list.
	Limit int32

	// Set to true if pagination should stop if the service returns a pagination token
	// that matches the most recent token provided to the service.
	StopOnDuplicateToken bool
}

ListInferenceExecutionsPaginatorOptions is the paginator options for ListInferenceExecutions

type ListInferenceSchedulersAPIClient

type ListInferenceSchedulersAPIClient interface {
	ListInferenceSchedulers(context.Context, *ListInferenceSchedulersInput, ...func(*Options)) (*ListInferenceSchedulersOutput, error)
}

ListInferenceSchedulersAPIClient is a client that implements the ListInferenceSchedulers operation.

type ListInferenceSchedulersInput

type ListInferenceSchedulersInput struct {

	// The beginning of the name of the inference schedulers to be listed.
	InferenceSchedulerNameBeginsWith *string

	// Specifies the maximum number of inference schedulers to list.
	MaxResults *int32

	// The name of the ML model used by the inference scheduler to be listed.
	ModelName *string

	// An opaque pagination token indicating where to continue the listing of inference
	// schedulers.
	NextToken *string
	// contains filtered or unexported fields
}

type ListInferenceSchedulersOutput

type ListInferenceSchedulersOutput struct {

	// Provides information about the specified inference scheduler, including data
	// upload frequency, model name and ARN, and status.
	InferenceSchedulerSummaries []types.InferenceSchedulerSummary

	// An opaque pagination token indicating where to continue the listing of inference
	// schedulers.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type ListInferenceSchedulersPaginator

type ListInferenceSchedulersPaginator struct {
	// contains filtered or unexported fields
}

ListInferenceSchedulersPaginator is a paginator for ListInferenceSchedulers

func NewListInferenceSchedulersPaginator

NewListInferenceSchedulersPaginator returns a new ListInferenceSchedulersPaginator

func (*ListInferenceSchedulersPaginator) HasMorePages

func (p *ListInferenceSchedulersPaginator) HasMorePages() bool

HasMorePages returns a boolean indicating whether more pages are available

func (*ListInferenceSchedulersPaginator) NextPage

NextPage retrieves the next ListInferenceSchedulers page.

type ListInferenceSchedulersPaginatorOptions

type ListInferenceSchedulersPaginatorOptions struct {
	// Specifies the maximum number of inference schedulers to list.
	Limit int32

	// Set to true if pagination should stop if the service returns a pagination token
	// that matches the most recent token provided to the service.
	StopOnDuplicateToken bool
}

ListInferenceSchedulersPaginatorOptions is the paginator options for ListInferenceSchedulers

type ListModelsAPIClient

type ListModelsAPIClient interface {
	ListModels(context.Context, *ListModelsInput, ...func(*Options)) (*ListModelsOutput, error)
}

ListModelsAPIClient is a client that implements the ListModels operation.

type ListModelsInput

type ListModelsInput struct {

	// The beginning of the name of the dataset of the ML models to be listed.
	DatasetNameBeginsWith *string

	// Specifies the maximum number of ML models to list.
	MaxResults *int32

	// The beginning of the name of the ML models being listed.
	ModelNameBeginsWith *string

	// An opaque pagination token indicating where to continue the listing of ML
	// models.
	NextToken *string

	// The status of the ML model.
	Status types.ModelStatus
	// contains filtered or unexported fields
}

type ListModelsOutput

type ListModelsOutput struct {

	// Provides information on the specified model, including created time, model and
	// dataset ARNs, and status.
	ModelSummaries []types.ModelSummary

	// An opaque pagination token indicating where to continue the listing of ML
	// models.
	NextToken *string

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type ListModelsPaginator

type ListModelsPaginator struct {
	// contains filtered or unexported fields
}

ListModelsPaginator is a paginator for ListModels

func NewListModelsPaginator

func NewListModelsPaginator(client ListModelsAPIClient, params *ListModelsInput, optFns ...func(*ListModelsPaginatorOptions)) *ListModelsPaginator

NewListModelsPaginator returns a new ListModelsPaginator

func (*ListModelsPaginator) HasMorePages

func (p *ListModelsPaginator) HasMorePages() bool

HasMorePages returns a boolean indicating whether more pages are available

func (*ListModelsPaginator) NextPage

func (p *ListModelsPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListModelsOutput, error)

NextPage retrieves the next ListModels page.

type ListModelsPaginatorOptions

type ListModelsPaginatorOptions struct {
	// Specifies the maximum number of ML models to list.
	Limit int32

	// Set to true if pagination should stop if the service returns a pagination token
	// that matches the most recent token provided to the service.
	StopOnDuplicateToken bool
}

ListModelsPaginatorOptions is the paginator options for ListModels

type ListTagsForResourceInput

type ListTagsForResourceInput struct {

	// The Amazon Resource Name (ARN) of the resource (such as the dataset or model)
	// that is the focus of the ListTagsForResource operation.
	//
	// This member is required.
	ResourceArn *string
	// contains filtered or unexported fields
}

type ListTagsForResourceOutput

type ListTagsForResourceOutput struct {

	// Any tags associated with the resource.
	Tags []types.Tag

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type Options

type Options struct {
	// Set of options to modify how an operation is invoked. These apply to all
	// operations invoked for this client. Use functional options on operation call to
	// modify this list for per operation behavior.
	APIOptions []func(*middleware.Stack) error

	// Configures the events that will be sent to the configured logger.
	ClientLogMode aws.ClientLogMode

	// The credentials object to use when signing requests.
	Credentials aws.CredentialsProvider

	// The endpoint options to be used when attempting to resolve an endpoint.
	EndpointOptions EndpointResolverOptions

	// The service endpoint resolver.
	EndpointResolver EndpointResolver

	// Signature Version 4 (SigV4) Signer
	HTTPSignerV4 HTTPSignerV4

	// Provides idempotency tokens values that will be automatically populated into
	// idempotent API operations.
	IdempotencyTokenProvider IdempotencyTokenProvider

	// The logger writer interface to write logging messages to.
	Logger logging.Logger

	// The region to send requests to. (Required)
	Region string

	// Retryer guides how HTTP requests should be retried in case of recoverable
	// failures. When nil the API client will use a default retryer.
	Retryer aws.Retryer

	// The HTTP client to invoke API calls with. Defaults to client's default HTTP
	// implementation if nil.
	HTTPClient HTTPClient
}

func (Options) Copy

func (o Options) Copy() Options

Copy creates a clone where the APIOptions list is deep copied.

type ResolveEndpoint

type ResolveEndpoint struct {
	Resolver EndpointResolver
	Options  EndpointResolverOptions
}

func (*ResolveEndpoint) HandleSerialize

func (*ResolveEndpoint) ID

func (*ResolveEndpoint) ID() string

type StartDataIngestionJobInput

type StartDataIngestionJobInput struct {

	// A unique identifier for the request. If you do not set the client request token,
	// Amazon Lookout for Equipment generates one.
	//
	// This member is required.
	ClientToken *string

	// The name of the dataset being used by the data ingestion job.
	//
	// This member is required.
	DatasetName *string

	// Specifies information for the input data for the data ingestion job, including
	// dataset S3 location.
	//
	// This member is required.
	IngestionInputConfiguration *types.IngestionInputConfiguration

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source for the data ingestion job.
	//
	// This member is required.
	RoleArn *string
	// contains filtered or unexported fields
}

type StartDataIngestionJobOutput

type StartDataIngestionJobOutput struct {

	// Indicates the job ID of the data ingestion job.
	JobId *string

	// Indicates the status of the StartDataIngestionJob operation.
	Status types.IngestionJobStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type StartInferenceSchedulerInput

type StartInferenceSchedulerInput struct {

	// The name of the inference scheduler to be started.
	//
	// This member is required.
	InferenceSchedulerName *string
	// contains filtered or unexported fields
}

type StartInferenceSchedulerOutput

type StartInferenceSchedulerOutput struct {

	// The Amazon Resource Name (ARN) of the inference scheduler being started.
	InferenceSchedulerArn *string

	// The name of the inference scheduler being started.
	InferenceSchedulerName *string

	// The Amazon Resource Name (ARN) of the ML model being used by the inference
	// scheduler.
	ModelArn *string

	// The name of the ML model being used by the inference scheduler.
	ModelName *string

	// Indicates the status of the inference scheduler.
	Status types.InferenceSchedulerStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type StopInferenceSchedulerInput

type StopInferenceSchedulerInput struct {

	// The name of the inference scheduler to be stopped.
	//
	// This member is required.
	InferenceSchedulerName *string
	// contains filtered or unexported fields
}

type StopInferenceSchedulerOutput

type StopInferenceSchedulerOutput struct {

	// The Amazon Resource Name (ARN) of the inference schedule being stopped.
	InferenceSchedulerArn *string

	// The name of the inference scheduler being stopped.
	InferenceSchedulerName *string

	// The Amazon Resource Name (ARN) of the ML model used by the inference scheduler
	// being stopped.
	ModelArn *string

	// The name of the ML model used by the inference scheduler being stopped.
	ModelName *string

	// Indicates the status of the inference scheduler.
	Status types.InferenceSchedulerStatus

	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type TagResourceInput

type TagResourceInput struct {

	// The Amazon Resource Name (ARN) of the specific resource to which the tag should
	// be associated.
	//
	// This member is required.
	ResourceArn *string

	// The tag or tags to be associated with a specific resource. Both the tag key and
	// value are specified.
	//
	// This member is required.
	Tags []types.Tag
	// contains filtered or unexported fields
}

type TagResourceOutput

type TagResourceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type UntagResourceInput

type UntagResourceInput struct {

	// The Amazon Resource Name (ARN) of the resource to which the tag is currently
	// associated.
	//
	// This member is required.
	ResourceArn *string

	// Specifies the key of the tag to be removed from a specified resource.
	//
	// This member is required.
	TagKeys []string
	// contains filtered or unexported fields
}

type UntagResourceOutput

type UntagResourceOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

type UpdateInferenceSchedulerInput

type UpdateInferenceSchedulerInput struct {

	// The name of the inference scheduler to be updated.
	//
	// This member is required.
	InferenceSchedulerName *string

	// A period of time (in minutes) by which inference on the data is delayed after
	// the data starts. For instance, if you select an offset delay time of five
	// minutes, inference will not begin on the data until the first data measurement
	// after the five minute mark. For example, if five minutes is selected, the
	// inference scheduler will wake up at the configured frequency with the additional
	// five minute delay time to check the customer S3 bucket. The customer can upload
	// data at the same frequency and they don't need to stop and restart the scheduler
	// when uploading new data.
	DataDelayOffsetInMinutes *int64

	// Specifies information for the input data for the inference scheduler, including
	// delimiter, format, and dataset location.
	DataInputConfiguration *types.InferenceInputConfiguration

	// Specifies information for the output results from the inference scheduler,
	// including the output S3 location.
	DataOutputConfiguration *types.InferenceOutputConfiguration

	// How often data is uploaded to the source S3 bucket for the input data. The value
	// chosen is the length of time between data uploads. For instance, if you select 5
	// minutes, Amazon Lookout for Equipment will upload the real-time data to the
	// source bucket once every 5 minutes. This frequency also determines how often
	// Amazon Lookout for Equipment starts a scheduled inference on your data. In this
	// example, it starts once every 5 minutes.
	DataUploadFrequency types.DataUploadFrequency

	// The Amazon Resource Name (ARN) of a role with permission to access the data
	// source for the inference scheduler.
	RoleArn *string
	// contains filtered or unexported fields
}

type UpdateInferenceSchedulerOutput

type UpdateInferenceSchedulerOutput struct {
	// Metadata pertaining to the operation's result.
	ResultMetadata middleware.Metadata
	// contains filtered or unexported fields
}

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