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
- func NewDefaultEndpointResolver() *internalendpoints.Resolver
- func WithAPIOptions(optFns ...func(*middleware.Stack) error) func(*Options)
- func WithEndpointResolver(v EndpointResolver) func(*Options)
- type Client
- func (c *Client) CreateDataset(ctx context.Context, params *CreateDatasetInput, optFns ...func(*Options)) (*CreateDatasetOutput, error)
- func (c *Client) CreateInferenceScheduler(ctx context.Context, params *CreateInferenceSchedulerInput, ...) (*CreateInferenceSchedulerOutput, error)
- func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error)
- func (c *Client) DeleteDataset(ctx context.Context, params *DeleteDatasetInput, optFns ...func(*Options)) (*DeleteDatasetOutput, error)
- func (c *Client) DeleteInferenceScheduler(ctx context.Context, params *DeleteInferenceSchedulerInput, ...) (*DeleteInferenceSchedulerOutput, error)
- func (c *Client) DeleteModel(ctx context.Context, params *DeleteModelInput, optFns ...func(*Options)) (*DeleteModelOutput, error)
- func (c *Client) DescribeDataIngestionJob(ctx context.Context, params *DescribeDataIngestionJobInput, ...) (*DescribeDataIngestionJobOutput, error)
- func (c *Client) DescribeDataset(ctx context.Context, params *DescribeDatasetInput, optFns ...func(*Options)) (*DescribeDatasetOutput, error)
- func (c *Client) DescribeInferenceScheduler(ctx context.Context, params *DescribeInferenceSchedulerInput, ...) (*DescribeInferenceSchedulerOutput, error)
- func (c *Client) DescribeModel(ctx context.Context, params *DescribeModelInput, optFns ...func(*Options)) (*DescribeModelOutput, error)
- func (c *Client) ListDataIngestionJobs(ctx context.Context, params *ListDataIngestionJobsInput, ...) (*ListDataIngestionJobsOutput, error)
- func (c *Client) ListDatasets(ctx context.Context, params *ListDatasetsInput, optFns ...func(*Options)) (*ListDatasetsOutput, error)
- func (c *Client) ListInferenceExecutions(ctx context.Context, params *ListInferenceExecutionsInput, ...) (*ListInferenceExecutionsOutput, error)
- func (c *Client) ListInferenceSchedulers(ctx context.Context, params *ListInferenceSchedulersInput, ...) (*ListInferenceSchedulersOutput, error)
- func (c *Client) ListModels(ctx context.Context, params *ListModelsInput, optFns ...func(*Options)) (*ListModelsOutput, error)
- func (c *Client) ListSensorStatistics(ctx context.Context, params *ListSensorStatisticsInput, ...) (*ListSensorStatisticsOutput, error)
- func (c *Client) ListTagsForResource(ctx context.Context, params *ListTagsForResourceInput, ...) (*ListTagsForResourceOutput, error)
- func (c *Client) StartDataIngestionJob(ctx context.Context, params *StartDataIngestionJobInput, ...) (*StartDataIngestionJobOutput, error)
- func (c *Client) StartInferenceScheduler(ctx context.Context, params *StartInferenceSchedulerInput, ...) (*StartInferenceSchedulerOutput, error)
- func (c *Client) StopInferenceScheduler(ctx context.Context, params *StopInferenceSchedulerInput, ...) (*StopInferenceSchedulerOutput, error)
- func (c *Client) TagResource(ctx context.Context, params *TagResourceInput, optFns ...func(*Options)) (*TagResourceOutput, error)
- func (c *Client) UntagResource(ctx context.Context, params *UntagResourceInput, optFns ...func(*Options)) (*UntagResourceOutput, error)
- func (c *Client) UpdateInferenceScheduler(ctx context.Context, params *UpdateInferenceSchedulerInput, ...) (*UpdateInferenceSchedulerOutput, error)
- type CreateDatasetInput
- type CreateDatasetOutput
- type CreateInferenceSchedulerInput
- type CreateInferenceSchedulerOutput
- type CreateModelInput
- type CreateModelOutput
- type DeleteDatasetInput
- type DeleteDatasetOutput
- type DeleteInferenceSchedulerInput
- type DeleteInferenceSchedulerOutput
- type DeleteModelInput
- type DeleteModelOutput
- type DescribeDataIngestionJobInput
- type DescribeDataIngestionJobOutput
- type DescribeDatasetInput
- type DescribeDatasetOutput
- type DescribeInferenceSchedulerInput
- type DescribeInferenceSchedulerOutput
- type DescribeModelInput
- type DescribeModelOutput
- type EndpointResolver
- type EndpointResolverFunc
- type EndpointResolverOptions
- type HTTPClient
- type HTTPSignerV4
- type IdempotencyTokenProvider
- type ListDataIngestionJobsAPIClient
- type ListDataIngestionJobsInput
- type ListDataIngestionJobsOutput
- type ListDataIngestionJobsPaginator
- type ListDataIngestionJobsPaginatorOptions
- type ListDatasetsAPIClient
- type ListDatasetsInput
- type ListDatasetsOutput
- type ListDatasetsPaginator
- type ListDatasetsPaginatorOptions
- type ListInferenceExecutionsAPIClient
- type ListInferenceExecutionsInput
- type ListInferenceExecutionsOutput
- type ListInferenceExecutionsPaginator
- type ListInferenceExecutionsPaginatorOptions
- type ListInferenceSchedulersAPIClient
- type ListInferenceSchedulersInput
- type ListInferenceSchedulersOutput
- type ListInferenceSchedulersPaginator
- type ListInferenceSchedulersPaginatorOptions
- type ListModelsAPIClient
- type ListModelsInput
- type ListModelsOutput
- type ListModelsPaginator
- type ListModelsPaginatorOptions
- type ListSensorStatisticsAPIClient
- type ListSensorStatisticsInput
- type ListSensorStatisticsOutput
- type ListSensorStatisticsPaginator
- type ListSensorStatisticsPaginatorOptions
- type ListTagsForResourceInput
- type ListTagsForResourceOutput
- type Options
- type ResolveEndpoint
- type StartDataIngestionJobInput
- type StartDataIngestionJobOutput
- type StartInferenceSchedulerInput
- type StartInferenceSchedulerOutput
- type StopInferenceSchedulerInput
- type StopInferenceSchedulerOutput
- type TagResourceInput
- type TagResourceOutput
- type UntagResourceInput
- type UntagResourceOutput
- type UpdateInferenceSchedulerInput
- type UpdateInferenceSchedulerOutput
Constants ¶
const ServiceAPIVersion = "2020-12-15"
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 ¶
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 ¶
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, and status.
func (*Client) DescribeDataset ¶
func (c *Client) DescribeDataset(ctx context.Context, params *DescribeDatasetInput, optFns ...func(*Options)) (*DescribeDatasetOutput, error)
Provides a JSON description of the data 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) ListSensorStatistics ¶ added in v1.13.0
func (c *Client) ListSensorStatistics(ctx context.Context, params *ListSensorStatisticsInput, optFns ...func(*Options)) (*ListSensorStatisticsOutput, error)
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset. Can also be used to retreive Sensor Statistics for a previous ingestion job.
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. 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 // Indicates the latest timestamp corresponding to data that was successfully // ingested during this specific ingestion job. DataEndTime *time.Time // Gives statistics about a completed ingestion job. These statistics primarily // relate to quantifying incorrect data such as MissingCompleteSensorData, // MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, and // DuplicateTimeStamps. DataQualitySummary *types.DataQualitySummary // Indicates the earliest timestamp corresponding to data that was successfully // ingested during this specific ingestion job. DataStartTime *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 // Indicates the size of the ingested dataset. IngestedDataSize *int64 // Gives statistics about how many files have been ingested, and which files have // not been ingested, for a particular ingestion job. IngestedFilesSummary *types.IngestedFilesSummary // 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 // Provides details about status of the ingestion job that is currently in // progress. StatusDetail *string // 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 // Indicates the latest timestamp corresponding to data that was successfully // ingested during the most recent ingestion of this particular dataset. DataEndTime *time.Time // Gives statistics associated with the given dataset for the latest successful // associated ingestion job id. These statistics primarily relate to quantifying // incorrect data such as MissingCompleteSensorData, MissingSensorData, // UnsupportedDateFormats, InsufficientSensorData, and DuplicateTimeStamps. DataQualitySummary *types.DataQualitySummary // Indicates the earliest timestamp corresponding to data that was successfully // ingested during the most recent ingestion of this particular dataset. DataStartTime *time.Time // The Amazon Resource Name (ARN) of the dataset being described. DatasetArn *string // The name of the dataset being described. DatasetName *string // IngestedFilesSummary associated with the given dataset for the latest successful // associated ingestion job id. IngestedFilesSummary *types.IngestedFilesSummary // 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 // The Amazon Resource Name (ARN) of the IAM role that you are using for this the // data ingestion job. 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 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 HTTPSignerV4 ¶
type IdempotencyTokenProvider ¶
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 ¶
func NewListDataIngestionJobsPaginator(client ListDataIngestionJobsAPIClient, params *ListDataIngestionJobsInput, optFns ...func(*ListDataIngestionJobsPaginatorOptions)) *ListDataIngestionJobsPaginator
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 ¶
func (p *ListDataIngestionJobsPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListDataIngestionJobsOutput, error)
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 ¶
func NewListInferenceExecutionsPaginator(client ListInferenceExecutionsAPIClient, params *ListInferenceExecutionsInput, optFns ...func(*ListInferenceExecutionsPaginatorOptions)) *ListInferenceExecutionsPaginator
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 ¶
func (p *ListInferenceExecutionsPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListInferenceExecutionsOutput, error)
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 ¶
func NewListInferenceSchedulersPaginator(client ListInferenceSchedulersAPIClient, params *ListInferenceSchedulersInput, optFns ...func(*ListInferenceSchedulersPaginatorOptions)) *ListInferenceSchedulersPaginator
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 ¶
func (p *ListInferenceSchedulersPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListInferenceSchedulersOutput, error)
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 ListSensorStatisticsAPIClient ¶ added in v1.13.0
type ListSensorStatisticsAPIClient interface {
ListSensorStatistics(context.Context, *ListSensorStatisticsInput, ...func(*Options)) (*ListSensorStatisticsOutput, error)
}
ListSensorStatisticsAPIClient is a client that implements the ListSensorStatistics operation.
type ListSensorStatisticsInput ¶ added in v1.13.0
type ListSensorStatisticsInput struct { // The name of the dataset associated with the list of Sensor Statistics. // // This member is required. DatasetName *string // The ingestion job id associated with the list of Sensor Statistics. To get // sensor statistics for a particular ingestion job id, both dataset name and // ingestion job id must be submitted as inputs. IngestionJobId *string // Specifies the maximum number of sensors for which to retrieve statistics. MaxResults *int32 // An opaque pagination token indicating where to continue the listing of sensor // statistics. NextToken *string // contains filtered or unexported fields }
type ListSensorStatisticsOutput ¶ added in v1.13.0
type ListSensorStatisticsOutput struct { // An opaque pagination token indicating where to continue the listing of sensor // statistics. NextToken *string // Provides ingestion-based statistics regarding the specified sensor with respect // to various validation types, such as whether data exists, the number and // percentage of missing values, and the number and percentage of duplicate // timestamps. SensorStatisticsSummaries []types.SensorStatisticsSummary // Metadata pertaining to the operation's result. ResultMetadata middleware.Metadata // contains filtered or unexported fields }
type ListSensorStatisticsPaginator ¶ added in v1.13.0
type ListSensorStatisticsPaginator struct {
// contains filtered or unexported fields
}
ListSensorStatisticsPaginator is a paginator for ListSensorStatistics
func NewListSensorStatisticsPaginator ¶ added in v1.13.0
func NewListSensorStatisticsPaginator(client ListSensorStatisticsAPIClient, params *ListSensorStatisticsInput, optFns ...func(*ListSensorStatisticsPaginatorOptions)) *ListSensorStatisticsPaginator
NewListSensorStatisticsPaginator returns a new ListSensorStatisticsPaginator
func (*ListSensorStatisticsPaginator) HasMorePages ¶ added in v1.13.0
func (p *ListSensorStatisticsPaginator) HasMorePages() bool
HasMorePages returns a boolean indicating whether more pages are available
func (*ListSensorStatisticsPaginator) NextPage ¶ added in v1.13.0
func (p *ListSensorStatisticsPaginator) NextPage(ctx context.Context, optFns ...func(*Options)) (*ListSensorStatisticsOutput, error)
NextPage retrieves the next ListSensorStatistics page.
type ListSensorStatisticsPaginatorOptions ¶ added in v1.13.0
type ListSensorStatisticsPaginatorOptions struct { // Specifies the maximum number of sensors for which to retrieve statistics. 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 }
ListSensorStatisticsPaginatorOptions is the paginator options for ListSensorStatistics
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 configuration DefaultsMode that the SDK should use when constructing the // clients initial default settings. DefaultsMode aws.DefaultsMode // 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 // RetryMaxAttempts specifies the maximum number attempts an API client will call // an operation that fails with a retryable error. A value of 0 is ignored, and // will not be used to configure the API client created default retryer, or modify // per operation call's retry max attempts. When creating a new API Clients this // member will only be used if the Retryer Options member is nil. This value will // be ignored if Retryer is not nil. If specified in an operation call's functional // options with a value that is different than the constructed client's Options, // the Client's Retryer will be wrapped to use the operation's specific // RetryMaxAttempts value. RetryMaxAttempts int // RetryMode specifies the retry mode the API client will be created with, if // Retryer option is not also specified. When creating a new API Clients this // member will only be used if the Retryer Options member is nil. This value will // be ignored if Retryer is not nil. Currently does not support per operation call // overrides, may in the future. RetryMode aws.RetryMode // Retryer guides how HTTP requests should be retried in case of recoverable // failures. When nil the API client will use a default retryer. The kind of // default retry created by the API client can be changed with the RetryMode // option. Retryer aws.Retryer // The RuntimeEnvironment configuration, only populated if the DefaultsMode is set // to DefaultsModeAuto and is initialized using config.LoadDefaultConfig. You // should not populate this structure programmatically, or rely on the values here // within your applications. RuntimeEnvironment aws.RuntimeEnvironment // The HTTP client to invoke API calls with. Defaults to client's default HTTP // implementation if nil. HTTPClient HTTPClient // contains filtered or unexported fields }
type ResolveEndpoint ¶
type ResolveEndpoint struct { Resolver EndpointResolver Options EndpointResolverOptions }
func (*ResolveEndpoint) HandleSerialize ¶
func (m *ResolveEndpoint) HandleSerialize(ctx context.Context, in middleware.SerializeInput, next middleware.SerializeHandler) ( out middleware.SerializeOutput, metadata middleware.Metadata, err error, )
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 }
Source Files ¶
- api_client.go
- api_op_CreateDataset.go
- api_op_CreateInferenceScheduler.go
- api_op_CreateModel.go
- api_op_DeleteDataset.go
- api_op_DeleteInferenceScheduler.go
- api_op_DeleteModel.go
- api_op_DescribeDataIngestionJob.go
- api_op_DescribeDataset.go
- api_op_DescribeInferenceScheduler.go
- api_op_DescribeModel.go
- api_op_ListDataIngestionJobs.go
- api_op_ListDatasets.go
- api_op_ListInferenceExecutions.go
- api_op_ListInferenceSchedulers.go
- api_op_ListModels.go
- api_op_ListSensorStatistics.go
- api_op_ListTagsForResource.go
- api_op_StartDataIngestionJob.go
- api_op_StartInferenceScheduler.go
- api_op_StopInferenceScheduler.go
- api_op_TagResource.go
- api_op_UntagResource.go
- api_op_UpdateInferenceScheduler.go
- deserializers.go
- doc.go
- endpoints.go
- go_module_metadata.go
- serializers.go
- validators.go