SDK for PHP 3.x

Client: Aws\LookoutEquipment\LookoutEquipmentClient
Service ID: lookoutequipment
Version: 2020-12-15

This page describes the parameters and results for the operations of the Amazon Lookout for Equipment (2020-12-15), and shows how to use the Aws\LookoutEquipment\LookoutEquipmentClient object to call the described operations. This documentation is specific to the 2020-12-15 API version of the service.

Operation Summary

Each of the following operations can be created from a client using $client->getCommand('CommandName'), where "CommandName" is the name of one of the following operations. Note: a command is a value that encapsulates an operation and the parameters used to create an HTTP request.

You can also create and send a command immediately using the magic methods available on a client object: $client->commandName(/* parameters */). You can send the command asynchronously (returning a promise) by appending the word "Async" to the operation name: $client->commandNameAsync(/* parameters */).

CreateDataset ( array $params = [] )
Creates a container for a collection of data being ingested for analysis.
CreateInferenceScheduler ( array $params = [] )
Creates a scheduled inference.
CreateLabel ( array $params = [] )
Creates a label for an event.
CreateLabelGroup ( array $params = [] )
Creates a group of labels.
CreateModel ( array $params = [] )
Creates a machine learning model for data inference.
CreateRetrainingScheduler ( array $params = [] )
Creates a retraining scheduler on the specified model.
DeleteDataset ( array $params = [] )
Deletes a dataset and associated artifacts.
DeleteInferenceScheduler ( array $params = [] )
Deletes an inference scheduler that has been set up.
DeleteLabel ( array $params = [] )
Deletes a label.
DeleteLabelGroup ( array $params = [] )
Deletes a group of labels.
DeleteModel ( array $params = [] )
Deletes a machine learning model currently available for Amazon Lookout for Equipment.
DeleteResourcePolicy ( array $params = [] )
Deletes the resource policy attached to the resource.
DeleteRetrainingScheduler ( array $params = [] )
Deletes a retraining scheduler from a model.
DescribeDataIngestionJob ( array $params = [] )
Provides information on a specific data ingestion job such as creation time, dataset ARN, and status.
DescribeDataset ( array $params = [] )
Provides a JSON description of the data in each time series dataset, including names, column names, and data types.
DescribeInferenceScheduler ( array $params = [] )
Specifies information about the inference scheduler being used, including name, model, status, and associated metadata
DescribeLabel ( array $params = [] )
Returns the name of the label.
DescribeLabelGroup ( array $params = [] )
Returns information about the label group.
DescribeModel ( array $params = [] )
Provides a JSON containing the overall information about a specific machine learning model, including model name and ARN, dataset, training and evaluation information, status, and so on.
DescribeModelVersion ( array $params = [] )
Retrieves information about a specific machine learning model version.
DescribeResourcePolicy ( array $params = [] )
Provides the details of a resource policy attached to a resource.
DescribeRetrainingScheduler ( array $params = [] )
Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.
ImportDataset ( array $params = [] )
Imports a dataset.
ImportModelVersion ( array $params = [] )
Imports a model that has been trained successfully.
ListDataIngestionJobs ( array $params = [] )
Provides a list of all data ingestion jobs, including dataset name and ARN, S3 location of the input data, status, and so on.
ListDatasets ( array $params = [] )
Lists all datasets currently available in your account, filtering on the dataset name.
ListInferenceEvents ( array $params = [] )
Lists all inference events that have been found for the specified inference scheduler.
ListInferenceExecutions ( array $params = [] )
Lists all inference executions that have been performed by the specified inference scheduler.
ListInferenceSchedulers ( array $params = [] )
Retrieves a list of all inference schedulers currently available for your account.
ListLabelGroups ( array $params = [] )
Returns a list of the label groups.
ListLabels ( array $params = [] )
Provides a list of labels.
ListModelVersions ( array $params = [] )
Generates a list of all model versions for a given model, including the model version, model version ARN, and status.
ListModels ( array $params = [] )
Generates a list of all models in the account, including model name and ARN, dataset, and status.
ListRetrainingSchedulers ( array $params = [] )
Lists all retraining schedulers in your account, filtering by model name prefix and status.
ListSensorStatistics ( array $params = [] )
Lists statistics about the data collected for each of the sensors that have been successfully ingested in the particular dataset.
ListTagsForResource ( array $params = [] )
Lists all the tags for a specified resource, including key and value.
PutResourcePolicy ( array $params = [] )
Creates a resource control policy for a given resource.
StartDataIngestionJob ( array $params = [] )
Starts a data ingestion job.
StartInferenceScheduler ( array $params = [] )
Starts an inference scheduler.
StartRetrainingScheduler ( array $params = [] )
Starts a retraining scheduler.
StopInferenceScheduler ( array $params = [] )
Stops an inference scheduler.
StopRetrainingScheduler ( array $params = [] )
Stops a retraining scheduler.
TagResource ( array $params = [] )
Associates a given tag to a resource in your account.
UntagResource ( array $params = [] )
Removes a specific tag from a given resource.
UpdateActiveModelVersion ( array $params = [] )
Sets the active model version for a given machine learning model.
UpdateInferenceScheduler ( array $params = [] )
Updates an inference scheduler.
UpdateLabelGroup ( array $params = [] )
Updates the label group.
UpdateModel ( array $params = [] )
Updates a model in the account.
UpdateRetrainingScheduler ( array $params = [] )
Updates a retraining scheduler.

Paginators

Paginators handle automatically iterating over paginated API results. Paginators are associated with specific API operations, and they accept the parameters that the corresponding API operation accepts. You can get a paginator from a client class using getPaginator($paginatorName, $operationParameters). This client supports the following paginators:

ListDataIngestionJobs
ListDatasets
ListInferenceEvents
ListInferenceExecutions
ListInferenceSchedulers
ListLabelGroups
ListLabels
ListModelVersions
ListModels
ListRetrainingSchedulers
ListSensorStatistics

Operations

CreateDataset

$result = $client->createDataset([/* ... */]);
$promise = $client->createDatasetAsync([/* ... */]);

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. For example, 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.

Parameter Syntax

$result = $client->createDataset([
    'ClientToken' => '<string>', // REQUIRED
    'DatasetName' => '<string>', // REQUIRED
    'DatasetSchema' => [
        'InlineDataSchema' => '<string>',
    ],
    'ServerSideKmsKeyId' => '<string>',
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DatasetName
Required: Yes
Type: string

The name of the dataset being created.

DatasetSchema
Type: DatasetSchema structure

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

ServerSideKmsKeyId
Type: string

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

Tags
Type: Array of Tag structures

Any tags associated with the ingested data described in the dataset.

Result Syntax

[
    'DatasetArn' => '<string>',
    'DatasetName' => '<string>',
    'Status' => 'CREATED|INGESTION_IN_PROGRESS|ACTIVE|IMPORT_IN_PROGRESS',
]

Result Details

Members
DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset being created.

DatasetName
Type: string

The name of the dataset being created.

Status
Type: string

Indicates the status of the CreateDataset operation.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

CreateInferenceScheduler

$result = $client->createInferenceScheduler([/* ... */]);
$promise = $client->createInferenceSchedulerAsync([/* ... */]);

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.

Parameter Syntax

$result = $client->createInferenceScheduler([
    'ClientToken' => '<string>', // REQUIRED
    'DataDelayOffsetInMinutes' => <integer>,
    'DataInputConfiguration' => [ // REQUIRED
        'InferenceInputNameConfiguration' => [
            'ComponentTimestampDelimiter' => '<string>',
            'TimestampFormat' => '<string>',
        ],
        'InputTimeZoneOffset' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'DataOutputConfiguration' => [ // REQUIRED
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [ // REQUIRED
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'DataUploadFrequency' => 'PT5M|PT10M|PT15M|PT30M|PT1H', // REQUIRED
    'InferenceSchedulerName' => '<string>', // REQUIRED
    'ModelName' => '<string>', // REQUIRED
    'RoleArn' => '<string>', // REQUIRED
    'ServerSideKmsKeyId' => '<string>',
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DataDelayOffsetInMinutes
Type: long (int|float)

The interval (in minutes) of planned delay at the start of each inference segment. For example, if inference is set to run every ten minutes, the delay is set to five minutes and the time is 09:08. The inference scheduler will wake up at the configured interval (which, without a delay configured, would be 09:10) plus the additional five minute delay time (so 09:15) to check your Amazon S3 bucket. The delay provides a buffer for you to upload data at the same frequency, so that you don't have to stop and restart the scheduler when uploading new data.

For more information, see Understanding the inference process.

DataInputConfiguration
Required: Yes
Type: InferenceInputConfiguration structure

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

DataOutputConfiguration
Required: Yes
Type: InferenceOutputConfiguration structure

Specifies configuration information for the output results for the inference scheduler, including the S3 location for the output.

DataUploadFrequency
Required: Yes
Type: string

How often data is uploaded to the source Amazon 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 runs inference on your data.

For more information, see Understanding the inference process.

InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler being created.

ModelName
Required: Yes
Type: string

The name of the previously trained machine learning model being used to create the inference scheduler.

RoleArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source being used for the inference.

ServerSideKmsKeyId
Type: string

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

Tags
Type: Array of Tag structures

Any tags associated with the inference scheduler.

Result Syntax

[
    'InferenceSchedulerArn' => '<string>',
    'InferenceSchedulerName' => '<string>',
    'ModelQuality' => 'QUALITY_THRESHOLD_MET|CANNOT_DETERMINE_QUALITY|POOR_QUALITY_DETECTED',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler being created.

InferenceSchedulerName
Type: string

The name of inference scheduler being created.

ModelQuality
Type: string

Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

For information about using labels with your models, see Understanding labeling.

For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

Status
Type: string

Indicates the status of the CreateInferenceScheduler operation.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

CreateLabel

$result = $client->createLabel([/* ... */]);
$promise = $client->createLabelAsync([/* ... */]);

Creates a label for an event.

Parameter Syntax

$result = $client->createLabel([
    'ClientToken' => '<string>', // REQUIRED
    'EndTime' => <integer || string || DateTime>, // REQUIRED
    'Equipment' => '<string>',
    'FaultCode' => '<string>',
    'LabelGroupName' => '<string>', // REQUIRED
    'Notes' => '<string>',
    'Rating' => 'ANOMALY|NO_ANOMALY|NEUTRAL', // REQUIRED
    'StartTime' => <integer || string || DateTime>, // REQUIRED
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request to create a label. If you do not set the client request token, Lookout for Equipment generates one.

EndTime
Required: Yes
Type: timestamp (string|DateTime or anything parsable by strtotime)

The end time of the labeled event.

Equipment
Type: string

Indicates that a label pertains to a particular piece of equipment.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

FaultCode
Type: string

Provides additional information about the label. The fault code must be defined in the FaultCodes attribute of the label group.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelGroupName
Required: Yes
Type: string

The name of a group of labels.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Notes
Type: string

Metadata providing additional information about the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Rating
Required: Yes
Type: string

Indicates whether a labeled event represents an anomaly.

StartTime
Required: Yes
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start time of the labeled event.

Result Syntax

[
    'LabelId' => '<string>',
]

Result Details

Members
LabelId
Type: string

The ID of the label that you have created.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

CreateLabelGroup

$result = $client->createLabelGroup([/* ... */]);
$promise = $client->createLabelGroupAsync([/* ... */]);

Creates a group of labels.

Parameter Syntax

$result = $client->createLabelGroup([
    'ClientToken' => '<string>', // REQUIRED
    'FaultCodes' => ['<string>', ...],
    'LabelGroupName' => '<string>', // REQUIRED
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request to create a label group. If you do not set the client request token, Lookout for Equipment generates one.

FaultCodes
Type: Array of strings

The acceptable fault codes (indicating the type of anomaly associated with the label) that can be used with this label group.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelGroupName
Required: Yes
Type: string

Names a group of labels.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Tags
Type: Array of Tag structures

Tags that provide metadata about the label group you are creating.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Result Syntax

[
    'LabelGroupArn' => '<string>',
    'LabelGroupName' => '<string>',
]

Result Details

Members
LabelGroupArn
Type: string

The Amazon Resource Name (ARN) of the label group that you have created.

LabelGroupName
Type: string

The name of the label group that you have created. Data in this field will be retained for service usage. Follow best practices for the security of your data.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

CreateModel

$result = $client->createModel([/* ... */]);
$promise = $client->createModelAsync([/* ... */]);

Creates a machine learning 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.

Parameter Syntax

$result = $client->createModel([
    'ClientToken' => '<string>', // REQUIRED
    'DataPreProcessingConfiguration' => [
        'TargetSamplingRate' => 'PT1S|PT5S|PT10S|PT15S|PT30S|PT1M|PT5M|PT10M|PT15M|PT30M|PT1H',
    ],
    'DatasetName' => '<string>', // REQUIRED
    'DatasetSchema' => [
        'InlineDataSchema' => '<string>',
    ],
    'EvaluationDataEndTime' => <integer || string || DateTime>,
    'EvaluationDataStartTime' => <integer || string || DateTime>,
    'LabelsInputConfiguration' => [
        'LabelGroupName' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'ModelDiagnosticsOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [ // REQUIRED
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'ModelName' => '<string>', // REQUIRED
    'OffCondition' => '<string>',
    'RoleArn' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
    'TrainingDataEndTime' => <integer || string || DateTime>,
    'TrainingDataStartTime' => <integer || string || DateTime>,
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DataPreProcessingConfiguration

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

DatasetName
Required: Yes
Type: string

The name of the dataset for the machine learning model being created.

DatasetSchema
Type: DatasetSchema structure

The data schema for the machine learning model being created.

EvaluationDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that should be used to end the subset of evaluation data for the machine learning model.

EvaluationDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that should be used to begin the subset of evaluation data for the machine learning model.

LabelsInputConfiguration
Type: LabelsInputConfiguration structure

The input configuration for the labels being used for the machine learning model that's being created.

ModelDiagnosticsOutputConfiguration

The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics. You must also specify the RoleArn request parameter.

ModelName
Required: Yes
Type: string

The name for the machine learning model to be created.

OffCondition
Type: 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.

RoleArn
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model.

ServerSideKmsKeyId
Type: string

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

Tags
Type: Array of Tag structures

Any tags associated with the machine learning model being created.

TrainingDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that should be used to end the subset of training data for the machine learning model.

TrainingDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that should be used to begin the subset of training data for the machine learning model.

Result Syntax

[
    'ModelArn' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
]

Result Details

Members
ModelArn
Type: string

The Amazon Resource Name (ARN) of the model being created.

Status
Type: string

Indicates the status of the CreateModel operation.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

CreateRetrainingScheduler

$result = $client->createRetrainingScheduler([/* ... */]);
$promise = $client->createRetrainingSchedulerAsync([/* ... */]);

Creates a retraining scheduler on the specified model.

Parameter Syntax

$result = $client->createRetrainingScheduler([
    'ClientToken' => '<string>', // REQUIRED
    'LookbackWindow' => '<string>', // REQUIRED
    'ModelName' => '<string>', // REQUIRED
    'PromoteMode' => 'MANAGED|MANUAL',
    'RetrainingFrequency' => '<string>', // REQUIRED
    'RetrainingStartDate' => <integer || string || DateTime>,
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

LookbackWindow
Required: Yes
Type: string

The number of past days of data that will be used for retraining.

ModelName
Required: Yes
Type: string

The name of the model to add the retraining scheduler to.

PromoteMode
Type: string

Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

RetrainingFrequency
Required: Yes
Type: string

This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

  • P3M15D – Every 3 months and 15 days

  • P2M – Every 2 months

  • P150D – Every 150 days

RetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

Result Syntax

[
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
ModelArn
Type: string

The ARN of the model that you added the retraining scheduler to.

ModelName
Type: string

The name of the model that you added the retraining scheduler to.

Status
Type: string

The status of the retraining scheduler.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Creates a retraining scheduler with manual promote mode

$result = $client->createRetrainingScheduler([
    'ClientToken' => 'sample-client-token',
    'LookbackWindow' => 'P360D',
    'ModelName' => 'sample-model',
    'PromoteMode' => 'MANUAL',
    'RetrainingFrequency' => 'P1M',
]);

Result syntax:

[
    'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
    'ModelName' => 'sample-model',
    'Status' => 'PENDING',
]
Example 2: Creates a retraining scheduler with a specific start date

$result = $client->createRetrainingScheduler([
    'ClientToken' => 'sample-client-token',
    'LookbackWindow' => 'P360D',
    'ModelName' => 'sample-model',
    'RetrainingFrequency' => 'P1M',
    'RetrainingStartDate' => ,
]);

Result syntax:

[
    'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
    'ModelName' => 'sample-model',
    'Status' => 'PENDING',
]

DeleteDataset

$result = $client->deleteDataset([/* ... */]);
$promise = $client->deleteDatasetAsync([/* ... */]);

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.

Parameter Syntax

$result = $client->deleteDataset([
    'DatasetName' => '<string>', // REQUIRED
]);

Parameter Details

Members
DatasetName
Required: Yes
Type: string

The name of the dataset to be deleted.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

DeleteInferenceScheduler

$result = $client->deleteInferenceScheduler([/* ... */]);
$promise = $client->deleteInferenceSchedulerAsync([/* ... */]);

Deletes an inference scheduler that has been set up. Prior inference results will not be deleted.

Parameter Syntax

$result = $client->deleteInferenceScheduler([
    'InferenceSchedulerName' => '<string>', // REQUIRED
]);

Parameter Details

Members
InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler to be deleted.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DeleteLabel

$result = $client->deleteLabel([/* ... */]);
$promise = $client->deleteLabelAsync([/* ... */]);

Deletes a label.

Parameter Syntax

$result = $client->deleteLabel([
    'LabelGroupName' => '<string>', // REQUIRED
    'LabelId' => '<string>', // REQUIRED
]);

Parameter Details

Members
LabelGroupName
Required: Yes
Type: string

The name of the label group that contains the label that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelId
Required: Yes
Type: string

The ID of the label that you want to delete.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

DeleteLabelGroup

$result = $client->deleteLabelGroup([/* ... */]);
$promise = $client->deleteLabelGroupAsync([/* ... */]);

Deletes a group of labels.

Parameter Syntax

$result = $client->deleteLabelGroup([
    'LabelGroupName' => '<string>', // REQUIRED
]);

Parameter Details

Members
LabelGroupName
Required: Yes
Type: string

The name of the label group that you want to delete. Data in this field will be retained for service usage. Follow best practices for the security of your data.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

DeleteModel

$result = $client->deleteModel([/* ... */]);
$promise = $client->deleteModelAsync([/* ... */]);

Deletes a machine learning 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.

Parameter Syntax

$result = $client->deleteModel([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the machine learning model to be deleted.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

DeleteResourcePolicy

$result = $client->deleteResourcePolicy([/* ... */]);
$promise = $client->deleteResourcePolicyAsync([/* ... */]);

Deletes the resource policy attached to the resource.

Parameter Syntax

$result = $client->deleteResourcePolicy([
    'ResourceArn' => '<string>', // REQUIRED
]);

Parameter Details

Members
ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the resource for which the resource policy should be deleted.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

DeleteRetrainingScheduler

$result = $client->deleteRetrainingScheduler([/* ... */]);
$promise = $client->deleteRetrainingSchedulerAsync([/* ... */]);

Deletes a retraining scheduler from a model. The retraining scheduler must be in the STOPPED status.

Parameter Syntax

$result = $client->deleteRetrainingScheduler([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the model whose retraining scheduler you want to delete.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Deletes a retraining scheduler

$result = $client->deleteRetrainingScheduler([
    'ModelName' => 'sample-model',
]);

DescribeDataIngestionJob

$result = $client->describeDataIngestionJob([/* ... */]);
$promise = $client->describeDataIngestionJobAsync([/* ... */]);

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

Parameter Syntax

$result = $client->describeDataIngestionJob([
    'JobId' => '<string>', // REQUIRED
]);

Parameter Details

Members
JobId
Required: Yes
Type: string

The job ID of the data ingestion job.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'DataEndTime' => <DateTime>,
    'DataQualitySummary' => [
        'DuplicateTimestamps' => [
            'TotalNumberOfDuplicateTimestamps' => <integer>,
        ],
        'InsufficientSensorData' => [
            'MissingCompleteSensorData' => [
                'AffectedSensorCount' => <integer>,
            ],
            'SensorsWithShortDateRange' => [
                'AffectedSensorCount' => <integer>,
            ],
        ],
        'InvalidSensorData' => [
            'AffectedSensorCount' => <integer>,
            'TotalNumberOfInvalidValues' => <integer>,
        ],
        'MissingSensorData' => [
            'AffectedSensorCount' => <integer>,
            'TotalNumberOfMissingValues' => <integer>,
        ],
        'UnsupportedTimestamps' => [
            'TotalNumberOfUnsupportedTimestamps' => <integer>,
        ],
    ],
    'DataStartTime' => <DateTime>,
    'DatasetArn' => '<string>',
    'FailedReason' => '<string>',
    'IngestedDataSize' => <integer>,
    'IngestedFilesSummary' => [
        'DiscardedFiles' => [
            [
                'Bucket' => '<string>',
                'Key' => '<string>',
            ],
            // ...
        ],
        'IngestedNumberOfFiles' => <integer>,
        'TotalNumberOfFiles' => <integer>,
    ],
    'IngestionInputConfiguration' => [
        'S3InputConfiguration' => [
            'Bucket' => '<string>',
            'KeyPattern' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'JobId' => '<string>',
    'RoleArn' => '<string>',
    'SourceDatasetArn' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
    'StatusDetail' => '<string>',
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the data ingestion job was created.

DataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the latest timestamp corresponding to data that was successfully ingested during this specific ingestion job.

DataQualitySummary
Type: DataQualitySummary structure

Gives statistics about a completed ingestion job. These statistics primarily relate to quantifying incorrect data such as MissingCompleteSensorData, MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, and DuplicateTimeStamps.

DataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the earliest timestamp corresponding to data that was successfully ingested during this specific ingestion job.

DatasetArn
Type: string

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

FailedReason
Type: string

Specifies the reason for failure when a data ingestion job has failed.

IngestedDataSize
Type: long (int|float)

Indicates the size of the ingested dataset.

IngestedFilesSummary
Type: IngestedFilesSummary structure

Gives statistics about how many files have been ingested, and which files have not been ingested, for a particular ingestion job.

IngestionInputConfiguration
Type: IngestionInputConfiguration structure

Specifies the S3 location configuration for the data input for the data ingestion job.

JobId
Type: string

Indicates the job ID of the data ingestion job.

RoleArn
Type: string

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

SourceDatasetArn
Type: string

The Amazon Resource Name (ARN) of the source dataset from which the data used for the data ingestion job was imported from.

Status
Type: string

Indicates the status of the DataIngestionJob operation.

StatusDetail
Type: string

Provides details about status of the ingestion job that is currently in progress.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeDataset

$result = $client->describeDataset([/* ... */]);
$promise = $client->describeDatasetAsync([/* ... */]);

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

Parameter Syntax

$result = $client->describeDataset([
    'DatasetName' => '<string>', // REQUIRED
]);

Parameter Details

Members
DatasetName
Required: Yes
Type: string

The name of the dataset to be described.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'DataEndTime' => <DateTime>,
    'DataQualitySummary' => [
        'DuplicateTimestamps' => [
            'TotalNumberOfDuplicateTimestamps' => <integer>,
        ],
        'InsufficientSensorData' => [
            'MissingCompleteSensorData' => [
                'AffectedSensorCount' => <integer>,
            ],
            'SensorsWithShortDateRange' => [
                'AffectedSensorCount' => <integer>,
            ],
        ],
        'InvalidSensorData' => [
            'AffectedSensorCount' => <integer>,
            'TotalNumberOfInvalidValues' => <integer>,
        ],
        'MissingSensorData' => [
            'AffectedSensorCount' => <integer>,
            'TotalNumberOfMissingValues' => <integer>,
        ],
        'UnsupportedTimestamps' => [
            'TotalNumberOfUnsupportedTimestamps' => <integer>,
        ],
    ],
    'DataStartTime' => <DateTime>,
    'DatasetArn' => '<string>',
    'DatasetName' => '<string>',
    'IngestedFilesSummary' => [
        'DiscardedFiles' => [
            [
                'Bucket' => '<string>',
                'Key' => '<string>',
            ],
            // ...
        ],
        'IngestedNumberOfFiles' => <integer>,
        'TotalNumberOfFiles' => <integer>,
    ],
    'IngestionInputConfiguration' => [
        'S3InputConfiguration' => [
            'Bucket' => '<string>',
            'KeyPattern' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'LastUpdatedAt' => <DateTime>,
    'RoleArn' => '<string>',
    'Schema' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'SourceDatasetArn' => '<string>',
    'Status' => 'CREATED|INGESTION_IN_PROGRESS|ACTIVE|IMPORT_IN_PROGRESS',
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Specifies the time the dataset was created in Lookout for Equipment.

DataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the latest timestamp corresponding to data that was successfully ingested during the most recent ingestion of this particular dataset.

DataQualitySummary
Type: DataQualitySummary structure

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.

DataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the earliest timestamp corresponding to data that was successfully ingested during the most recent ingestion of this particular dataset.

DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset being described.

DatasetName
Type: string

The name of the dataset being described.

IngestedFilesSummary
Type: IngestedFilesSummary structure

IngestedFilesSummary associated with the given dataset for the latest successful associated ingestion job id.

IngestionInputConfiguration
Type: IngestionInputConfiguration structure

Specifies the S3 location configuration for the data input for the data ingestion job.

LastUpdatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Specifies the time the dataset was last updated, if it was.

RoleArn
Type: string

The Amazon Resource Name (ARN) of the IAM role that you are using for this the data ingestion job.

Schema
Type: string (string|number|array|map or anything parsable by json_encode)

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

ServerSideKmsKeyId
Type: string

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

SourceDatasetArn
Type: string

The Amazon Resource Name (ARN) of the source dataset from which the current data being described was imported from.

Status
Type: string

Indicates the status of the dataset.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeInferenceScheduler

$result = $client->describeInferenceScheduler([/* ... */]);
$promise = $client->describeInferenceSchedulerAsync([/* ... */]);

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

Parameter Syntax

$result = $client->describeInferenceScheduler([
    'InferenceSchedulerName' => '<string>', // REQUIRED
]);

Parameter Details

Members
InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler being described.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'DataDelayOffsetInMinutes' => <integer>,
    'DataInputConfiguration' => [
        'InferenceInputNameConfiguration' => [
            'ComponentTimestampDelimiter' => '<string>',
            'TimestampFormat' => '<string>',
        ],
        'InputTimeZoneOffset' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'DataOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'DataUploadFrequency' => 'PT5M|PT10M|PT15M|PT30M|PT1H',
    'InferenceSchedulerArn' => '<string>',
    'InferenceSchedulerName' => '<string>',
    'LatestInferenceResult' => 'ANOMALOUS|NORMAL',
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'RoleArn' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
    'UpdatedAt' => <DateTime>,
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Specifies the time at which the inference scheduler was created.

DataDelayOffsetInMinutes
Type: long (int|float)

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.

DataInputConfiguration
Type: InferenceInputConfiguration structure

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

DataOutputConfiguration

Specifies information for the output results for the inference scheduler, including the output S3 location.

DataUploadFrequency
Type: string

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.

InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler being described.

InferenceSchedulerName
Type: string

The name of the inference scheduler being described.

LatestInferenceResult
Type: string

Indicates whether the latest execution for the inference scheduler was Anomalous (anomalous events found) or Normal (no anomalous events found).

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model of the inference scheduler being described.

ModelName
Type: string

The name of the machine learning model of the inference scheduler being described.

RoleArn
Type: string

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

ServerSideKmsKeyId
Type: string

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

Status
Type: string

Indicates the status of the inference scheduler.

UpdatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Specifies the time at which the inference scheduler was last updated, if it was.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeLabel

$result = $client->describeLabel([/* ... */]);
$promise = $client->describeLabelAsync([/* ... */]);

Returns the name of the label.

Parameter Syntax

$result = $client->describeLabel([
    'LabelGroupName' => '<string>', // REQUIRED
    'LabelId' => '<string>', // REQUIRED
]);

Parameter Details

Members
LabelGroupName
Required: Yes
Type: string

Returns the name of the group containing the label.

LabelId
Required: Yes
Type: string

Returns the ID of the label.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'EndTime' => <DateTime>,
    'Equipment' => '<string>',
    'FaultCode' => '<string>',
    'LabelGroupArn' => '<string>',
    'LabelGroupName' => '<string>',
    'LabelId' => '<string>',
    'Notes' => '<string>',
    'Rating' => 'ANOMALY|NO_ANOMALY|NEUTRAL',
    'StartTime' => <DateTime>,
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label was created.

EndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The end time of the requested label.

Equipment
Type: string

Indicates that a label pertains to a particular piece of equipment.

FaultCode
Type: string

Indicates the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelGroupArn
Type: string

The Amazon Resource Name (ARN) of the requested label group.

LabelGroupName
Type: string

The name of the requested label group.

LabelId
Type: string

The ID of the requested label.

Notes
Type: string

Metadata providing additional information about the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

Rating
Type: string

Indicates whether a labeled event represents an anomaly.

StartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start time of the requested label.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeLabelGroup

$result = $client->describeLabelGroup([/* ... */]);
$promise = $client->describeLabelGroupAsync([/* ... */]);

Returns information about the label group.

Parameter Syntax

$result = $client->describeLabelGroup([
    'LabelGroupName' => '<string>', // REQUIRED
]);

Parameter Details

Members
LabelGroupName
Required: Yes
Type: string

Returns the name of the label group.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'FaultCodes' => ['<string>', ...],
    'LabelGroupArn' => '<string>',
    'LabelGroupName' => '<string>',
    'UpdatedAt' => <DateTime>,
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label group was created.

FaultCodes
Type: Array of strings

Codes indicating the type of anomaly associated with the labels in the lagbel group.

LabelGroupArn
Type: string

The Amazon Resource Name (ARN) of the label group.

LabelGroupName
Type: string

The name of the label group.

UpdatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label group was updated.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeModel

$result = $client->describeModel([/* ... */]);
$promise = $client->describeModelAsync([/* ... */]);

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

Parameter Syntax

$result = $client->describeModel([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the machine learning model to be described.

Result Syntax

[
    'AccumulatedInferenceDataEndTime' => <DateTime>,
    'AccumulatedInferenceDataStartTime' => <DateTime>,
    'ActiveModelVersion' => <integer>,
    'ActiveModelVersionArn' => '<string>',
    'CreatedAt' => <DateTime>,
    'DataPreProcessingConfiguration' => [
        'TargetSamplingRate' => 'PT1S|PT5S|PT10S|PT15S|PT30S|PT1M|PT5M|PT10M|PT15M|PT30M|PT1H',
    ],
    'DatasetArn' => '<string>',
    'DatasetName' => '<string>',
    'EvaluationDataEndTime' => <DateTime>,
    'EvaluationDataStartTime' => <DateTime>,
    'FailedReason' => '<string>',
    'ImportJobEndTime' => <DateTime>,
    'ImportJobStartTime' => <DateTime>,
    'LabelsInputConfiguration' => [
        'LabelGroupName' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'LastUpdatedTime' => <DateTime>,
    'LatestScheduledRetrainingAvailableDataInDays' => <integer>,
    'LatestScheduledRetrainingFailedReason' => '<string>',
    'LatestScheduledRetrainingModelVersion' => <integer>,
    'LatestScheduledRetrainingStartTime' => <DateTime>,
    'LatestScheduledRetrainingStatus' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
    'ModelArn' => '<string>',
    'ModelDiagnosticsOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'ModelMetrics' => '<string>',
    'ModelName' => '<string>',
    'ModelQuality' => 'QUALITY_THRESHOLD_MET|CANNOT_DETERMINE_QUALITY|POOR_QUALITY_DETECTED',
    'ModelVersionActivatedAt' => <DateTime>,
    'NextScheduledRetrainingStartDate' => <DateTime>,
    'OffCondition' => '<string>',
    'PreviousActiveModelVersion' => <integer>,
    'PreviousActiveModelVersionArn' => '<string>',
    'PreviousModelVersionActivatedAt' => <DateTime>,
    'PriorModelMetrics' => '<string>',
    'RetrainingSchedulerStatus' => 'PENDING|RUNNING|STOPPING|STOPPED',
    'RoleArn' => '<string>',
    'Schema' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'SourceModelVersionArn' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
    'TrainingDataEndTime' => <DateTime>,
    'TrainingDataStartTime' => <DateTime>,
    'TrainingExecutionEndTime' => <DateTime>,
    'TrainingExecutionStartTime' => <DateTime>,
]

Result Details

Members
AccumulatedInferenceDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the end time of the inference data that has been accumulated.

AccumulatedInferenceDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the start time of the inference data that has been accumulated.

ActiveModelVersion
Type: long (int|float)

The name of the model version used by the inference schedular when running a scheduled inference execution.

ActiveModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the model version used by the inference scheduler when running a scheduled inference execution.

CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time and date at which the machine learning model was created.

DataPreProcessingConfiguration

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

DatasetArn
Type: string

The Amazon Resouce Name (ARN) of the dataset used to create the machine learning model being described.

DatasetName
Type: string

The name of the dataset being used by the machine learning being described.

EvaluationDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that was used to end the subset of evaluation data for the machine learning model.

EvaluationDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that was used to begin the subset of evaluation data for the machine learning model.

FailedReason
Type: string

If the training of the machine learning model failed, this indicates the reason for that failure.

ImportJobEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date and time when the import job was completed. This field appears if the active model version was imported.

ImportJobStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date and time when the import job was started. This field appears if the active model version was imported.

LabelsInputConfiguration
Type: LabelsInputConfiguration structure

Specifies configuration information about the labels input, including its S3 location.

LastUpdatedTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the last time the machine learning model was updated. The type of update is not specified.

LatestScheduledRetrainingAvailableDataInDays
Type: int

Indicates the number of days of data used in the most recent scheduled retraining run.

LatestScheduledRetrainingFailedReason
Type: string

If the model version was generated by retraining and the training failed, this indicates the reason for that failure.

LatestScheduledRetrainingModelVersion
Type: long (int|float)

Indicates the most recent model version that was generated by retraining.

LatestScheduledRetrainingStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the start time of the most recent scheduled retraining run.

LatestScheduledRetrainingStatus
Type: string

Indicates the status of the most recent scheduled retraining run.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model being described.

ModelDiagnosticsOutputConfiguration

Configuration information for the model's pointwise model diagnostics.

ModelMetrics
Type: string (string|number|array|map or anything parsable by json_encode)

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.

ModelName
Type: string

The name of the machine learning model being described.

ModelQuality
Type: string

Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

For information about using labels with your models, see Understanding labeling.

For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

ModelVersionActivatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date the active model version was activated.

NextScheduledRetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the date and time that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.

OffCondition
Type: 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.

PreviousActiveModelVersion
Type: long (int|float)

The model version that was set as the active model version prior to the current active model version.

PreviousActiveModelVersionArn
Type: string

The ARN of the model version that was set as the active model version prior to the current active model version.

PreviousModelVersionActivatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date and time when the previous active model version was activated.

PriorModelMetrics
Type: string (string|number|array|map or anything parsable by json_encode)

If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.

RetrainingSchedulerStatus
Type: string

Indicates the status of the retraining scheduler.

RoleArn
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source for the machine learning model being described.

Schema
Type: string (string|number|array|map or anything parsable by json_encode)

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

ServerSideKmsKeyId
Type: string

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

SourceModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the source model version. This field appears if the active model version was imported.

Status
Type: string

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

TrainingDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that was used to end the subset of training data for the machine learning model.

TrainingDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset that was used to begin the subset of training data for the machine learning model.

TrainingExecutionEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time at which the training of the machine learning model was completed.

TrainingExecutionStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time at which the training of the machine learning model began.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeModelVersion

$result = $client->describeModelVersion([/* ... */]);
$promise = $client->describeModelVersionAsync([/* ... */]);

Retrieves information about a specific machine learning model version.

Parameter Syntax

$result = $client->describeModelVersion([
    'ModelName' => '<string>', // REQUIRED
    'ModelVersion' => <integer>, // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the machine learning model that this version belongs to.

ModelVersion
Required: Yes
Type: long (int|float)

The version of the machine learning model.

Result Syntax

[
    'AutoPromotionResult' => 'MODEL_PROMOTED|MODEL_NOT_PROMOTED|RETRAINING_INTERNAL_ERROR|RETRAINING_CUSTOMER_ERROR|RETRAINING_CANCELLED',
    'AutoPromotionResultReason' => '<string>',
    'CreatedAt' => <DateTime>,
    'DataPreProcessingConfiguration' => [
        'TargetSamplingRate' => 'PT1S|PT5S|PT10S|PT15S|PT30S|PT1M|PT5M|PT10M|PT15M|PT30M|PT1H',
    ],
    'DatasetArn' => '<string>',
    'DatasetName' => '<string>',
    'EvaluationDataEndTime' => <DateTime>,
    'EvaluationDataStartTime' => <DateTime>,
    'FailedReason' => '<string>',
    'ImportJobEndTime' => <DateTime>,
    'ImportJobStartTime' => <DateTime>,
    'ImportedDataSizeInBytes' => <integer>,
    'LabelsInputConfiguration' => [
        'LabelGroupName' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'LastUpdatedTime' => <DateTime>,
    'ModelArn' => '<string>',
    'ModelDiagnosticsOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [
            'Bucket' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'ModelDiagnosticsResultsObject' => [
        'Bucket' => '<string>',
        'Key' => '<string>',
    ],
    'ModelMetrics' => '<string>',
    'ModelName' => '<string>',
    'ModelQuality' => 'QUALITY_THRESHOLD_MET|CANNOT_DETERMINE_QUALITY|POOR_QUALITY_DETECTED',
    'ModelVersion' => <integer>,
    'ModelVersionArn' => '<string>',
    'OffCondition' => '<string>',
    'PriorModelMetrics' => '<string>',
    'RetrainingAvailableDataInDays' => <integer>,
    'RoleArn' => '<string>',
    'Schema' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'SourceModelVersionArn' => '<string>',
    'SourceType' => 'TRAINING|RETRAINING|IMPORT',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
    'TrainingDataEndTime' => <DateTime>,
    'TrainingDataStartTime' => <DateTime>,
    'TrainingExecutionEndTime' => <DateTime>,
    'TrainingExecutionStartTime' => <DateTime>,
]

Result Details

Members
AutoPromotionResult
Type: string

Indicates whether the model version was promoted to be the active version after retraining or if there was an error with or cancellation of the retraining.

AutoPromotionResultReason
Type: string

Indicates the reason for the AutoPromotionResult. For example, a model might not be promoted if its performance was worse than the active version, if there was an error during training, or if the retraining scheduler was using MANUAL promote mode. The model will be promoted in MANAGED promote mode if the performance is better than the previous model.

CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time and date at which the machine learning model version was created.

DataPreProcessingConfiguration

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

DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset used to train the model version.

DatasetName
Type: string

The name of the dataset used to train the model version.

EvaluationDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date on which the data in the evaluation set began being gathered. If you imported the version, this is the date that the evaluation set data in the source version finished being gathered.

EvaluationDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date on which the data in the evaluation set began being gathered. If you imported the version, this is the date that the evaluation set data in the source version began being gathered.

FailedReason
Type: string

The failure message if the training of the model version failed.

ImportJobEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date and time when the import job completed. This field appears if the model version was imported.

ImportJobStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date and time when the import job began. This field appears if the model version was imported.

ImportedDataSizeInBytes
Type: long (int|float)

The size in bytes of the imported data. This field appears if the model version was imported.

LabelsInputConfiguration
Type: LabelsInputConfiguration structure

Contains the configuration information for the S3 location being used to hold label data.

LastUpdatedTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the last time the machine learning model version was updated.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the parent machine learning model that this version belong to.

ModelDiagnosticsOutputConfiguration

The Amazon S3 location where Amazon Lookout for Equipment saves the pointwise model diagnostics for the model version.

ModelDiagnosticsResultsObject
Type: S3Object structure

The Amazon S3 output prefix for where Lookout for Equipment saves the pointwise model diagnostics for the model version.

ModelMetrics
Type: string

Shows an aggregated summary, in JSON format, of the model's performance within the evaluation time range. These metrics are created when evaluating the model.

ModelName
Type: string

The name of the machine learning model that this version belongs to.

ModelQuality
Type: string

Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

For information about using labels with your models, see Understanding labeling.

For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

ModelVersion
Type: long (int|float)

The version of the machine learning model.

ModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the model version.

OffCondition
Type: 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.

PriorModelMetrics
Type: string

If the model version was retrained, this field shows a summary of the performance of the prior model on the new training range. You can use the information in this JSON-formatted object to compare the new model version and the prior model version.

RetrainingAvailableDataInDays
Type: int

Indicates the number of days of data used in the most recent scheduled retraining run.

RoleArn
Type: string

The Amazon Resource Name (ARN) of the role that was used to train the model version.

Schema
Type: string

The schema of the data used to train the model version.

ServerSideKmsKeyId
Type: string

The identifier of the KMS key key used to encrypt model version data by Amazon Lookout for Equipment.

SourceModelVersionArn
Type: string

If model version was imported, then this field is the arn of the source model version.

SourceType
Type: string

Indicates whether this model version was created by training or by importing.

Status
Type: string

The current status of the model version.

TrainingDataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date on which the training data finished being gathered. If you imported the version, this is the date that the training data in the source version finished being gathered.

TrainingDataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The date on which the training data began being gathered. If you imported the version, this is the date that the training data in the source version began being gathered.

TrainingExecutionEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time when the training of the version completed.

TrainingExecutionStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time when the training of the version began.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeResourcePolicy

$result = $client->describeResourcePolicy([/* ... */]);
$promise = $client->describeResourcePolicyAsync([/* ... */]);

Provides the details of a resource policy attached to a resource.

Parameter Syntax

$result = $client->describeResourcePolicy([
    'ResourceArn' => '<string>', // REQUIRED
]);

Parameter Details

Members
ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the resource that is associated with the resource policy.

Result Syntax

[
    'CreationTime' => <DateTime>,
    'LastModifiedTime' => <DateTime>,
    'PolicyRevisionId' => '<string>',
    'ResourcePolicy' => '<string>',
]

Result Details

Members
CreationTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time when the resource policy was created.

LastModifiedTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time when the resource policy was last modified.

PolicyRevisionId
Type: string

A unique identifier for a revision of the resource policy.

ResourcePolicy
Type: string

The resource policy in a JSON-formatted string.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

DescribeRetrainingScheduler

$result = $client->describeRetrainingScheduler([/* ... */]);
$promise = $client->describeRetrainingSchedulerAsync([/* ... */]);

Provides a description of the retraining scheduler, including information such as the model name and retraining parameters.

Parameter Syntax

$result = $client->describeRetrainingScheduler([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the model that the retraining scheduler is attached to.

Result Syntax

[
    'CreatedAt' => <DateTime>,
    'LookbackWindow' => '<string>',
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'PromoteMode' => 'MANAGED|MANUAL',
    'RetrainingFrequency' => '<string>',
    'RetrainingStartDate' => <DateTime>,
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
    'UpdatedAt' => <DateTime>,
]

Result Details

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time and date at which the retraining scheduler was created.

LookbackWindow
Type: string

The number of past days of data used for retraining.

ModelArn
Type: string

The ARN of the model that the retraining scheduler is attached to.

ModelName
Type: string

The name of the model that the retraining scheduler is attached to.

PromoteMode
Type: string

Indicates how the service uses new models. In MANAGED mode, new models are used for inference if they have better performance than the current model. In MANUAL mode, the new models are not used until they are manually activated.

RetrainingFrequency
Type: string

The frequency at which the model retraining is set. This follows the ISO 8601 guidelines.

RetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

Status
Type: string

The status of the retraining scheduler.

UpdatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time and date at which the retraining scheduler was updated.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Describes a retraining scheduler

$result = $client->describeRetrainingScheduler([
    'ModelName' => 'sample-model',
]);

Result syntax:

[
    'CreatedAt' => ,
    'LookbackWindow' => 'P360D',
    'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
    'ModelName' => 'sample-model',
    'PromoteMode' => 'MANAGED',
    'RetrainingFrequency' => 'P1M',
    'RetrainingStartDate' => ,
    'Status' => 'RUNNING',
    'UpdatedAt' => ,
]

ImportDataset

$result = $client->importDataset([/* ... */]);
$promise = $client->importDatasetAsync([/* ... */]);

Imports a dataset.

Parameter Syntax

$result = $client->importDataset([
    'ClientToken' => '<string>', // REQUIRED
    'DatasetName' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'SourceDatasetArn' => '<string>', // REQUIRED
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DatasetName
Type: string

The name of the machine learning dataset to be created. If the dataset already exists, Amazon Lookout for Equipment overwrites the existing dataset. If you don't specify this field, it is filled with the name of the source dataset.

ServerSideKmsKeyId
Type: string

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

SourceDatasetArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the dataset to import.

Tags
Type: Array of Tag structures

Any tags associated with the dataset to be created.

Result Syntax

[
    'DatasetArn' => '<string>',
    'DatasetName' => '<string>',
    'JobId' => '<string>',
    'Status' => 'CREATED|INGESTION_IN_PROGRESS|ACTIVE|IMPORT_IN_PROGRESS',
]

Result Details

Members
DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset that was imported.

DatasetName
Type: string

The name of the created machine learning dataset.

JobId
Type: string

A unique identifier for the job of importing the dataset.

Status
Type: string

The status of the ImportDataset operation.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ImportModelVersion

$result = $client->importModelVersion([/* ... */]);
$promise = $client->importModelVersionAsync([/* ... */]);

Imports a model that has been trained successfully.

Parameter Syntax

$result = $client->importModelVersion([
    'ClientToken' => '<string>', // REQUIRED
    'DatasetName' => '<string>', // REQUIRED
    'InferenceDataImportStrategy' => 'NO_IMPORT|ADD_WHEN_EMPTY|OVERWRITE',
    'LabelsInputConfiguration' => [
        'LabelGroupName' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'ModelName' => '<string>',
    'RoleArn' => '<string>',
    'ServerSideKmsKeyId' => '<string>',
    'SourceModelVersionArn' => '<string>', // REQUIRED
    'Tags' => [
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DatasetName
Required: Yes
Type: string

The name of the dataset for the machine learning model being imported.

InferenceDataImportStrategy
Type: string

Indicates how to import the accumulated inference data when a model version is imported. The possible values are as follows:

  • NO_IMPORT – Don't import the data.

  • ADD_WHEN_EMPTY – Only import the data from the source model if there is no existing data in the target model.

  • OVERWRITE – Import the data from the source model and overwrite the existing data in the target model.

LabelsInputConfiguration
Type: LabelsInputConfiguration structure

Contains the configuration information for the S3 location being used to hold label data.

ModelName
Type: string

The name for the machine learning model to be created. If the model already exists, Amazon Lookout for Equipment creates a new version. If you do not specify this field, it is filled with the name of the source model.

RoleArn
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source being used to create the machine learning model.

ServerSideKmsKeyId
Type: string

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

SourceModelVersionArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the model version to import.

Tags
Type: Array of Tag structures

The tags associated with the machine learning model to be created.

Result Syntax

[
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'ModelVersion' => <integer>,
    'ModelVersionArn' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
]

Result Details

Members
ModelArn
Type: string

The Amazon Resource Name (ARN) of the model being created.

ModelName
Type: string

The name for the machine learning model.

ModelVersion
Type: long (int|float)

The version of the model being created.

ModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the model version being created.

Status
Type: string

The status of the ImportModelVersion operation.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListDataIngestionJobs

$result = $client->listDataIngestionJobs([/* ... */]);
$promise = $client->listDataIngestionJobsAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listDataIngestionJobs([
    'DatasetName' => '<string>',
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
]);

Parameter Details

Members
DatasetName
Type: string

The name of the dataset being used for the data ingestion job.

MaxResults
Type: int

Specifies the maximum number of data ingestion jobs to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

Status
Type: string

Indicates the status of the data ingestion job.

Result Syntax

[
    'DataIngestionJobSummaries' => [
        [
            'DatasetArn' => '<string>',
            'DatasetName' => '<string>',
            'IngestionInputConfiguration' => [
                'S3InputConfiguration' => [
                    'Bucket' => '<string>',
                    'KeyPattern' => '<string>',
                    'Prefix' => '<string>',
                ],
            ],
            'JobId' => '<string>',
            'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
DataIngestionJobSummaries
Type: Array of DataIngestionJobSummary structures

Specifies information about the specific data ingestion job, including dataset name and status.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of data ingestion jobs.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListDatasets

$result = $client->listDatasets([/* ... */]);
$promise = $client->listDatasetsAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listDatasets([
    'DatasetNameBeginsWith' => '<string>',
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members
DatasetNameBeginsWith
Type: string

The beginning of the name of the datasets to be listed.

MaxResults
Type: int

Specifies the maximum number of datasets to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of datasets.

Result Syntax

[
    'DatasetSummaries' => [
        [
            'CreatedAt' => <DateTime>,
            'DatasetArn' => '<string>',
            'DatasetName' => '<string>',
            'Status' => 'CREATED|INGESTION_IN_PROGRESS|ACTIVE|IMPORT_IN_PROGRESS',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
DatasetSummaries
Type: Array of DatasetSummary structures

Provides information about the specified dataset, including creation time, dataset ARN, and status.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of datasets.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListInferenceEvents

$result = $client->listInferenceEvents([/* ... */]);
$promise = $client->listInferenceEventsAsync([/* ... */]);

Lists all inference events that have been found for the specified inference scheduler.

Parameter Syntax

$result = $client->listInferenceEvents([
    'InferenceSchedulerName' => '<string>', // REQUIRED
    'IntervalEndTime' => <integer || string || DateTime>, // REQUIRED
    'IntervalStartTime' => <integer || string || DateTime>, // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members
InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler for the inference events listed.

IntervalEndTime
Required: Yes
Type: timestamp (string|DateTime or anything parsable by strtotime)

Returns all the inference events with an end start time equal to or greater than less than the end time given.

IntervalStartTime
Required: Yes
Type: timestamp (string|DateTime or anything parsable by strtotime)

Lookout for Equipment will return all the inference events with an end time equal to or greater than the start time given.

MaxResults
Type: int

Specifies the maximum number of inference events to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference events.

Result Syntax

[
    'InferenceEventSummaries' => [
        [
            'Diagnostics' => '<string>',
            'EventDurationInSeconds' => <integer>,
            'EventEndTime' => <DateTime>,
            'EventStartTime' => <DateTime>,
            'InferenceSchedulerArn' => '<string>',
            'InferenceSchedulerName' => '<string>',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
InferenceEventSummaries
Type: Array of InferenceEventSummary structures

Provides an array of information about the individual inference events returned from the ListInferenceEvents operation, including scheduler used, event start time, event end time, diagnostics, and so on.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference executions.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListInferenceExecutions

$result = $client->listInferenceExecutions([/* ... */]);
$promise = $client->listInferenceExecutionsAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listInferenceExecutions([
    'DataEndTimeBefore' => <integer || string || DateTime>,
    'DataStartTimeAfter' => <integer || string || DateTime>,
    'InferenceSchedulerName' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED',
]);

Parameter Details

Members
DataEndTimeBefore
Type: timestamp (string|DateTime or anything parsable by strtotime)

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

DataStartTimeAfter
Type: timestamp (string|DateTime or anything parsable by strtotime)

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

InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler for the inference execution listed.

MaxResults
Type: int

Specifies the maximum number of inference executions to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference executions.

Status
Type: string

The status of the inference execution.

Result Syntax

[
    'InferenceExecutionSummaries' => [
        [
            'CustomerResultObject' => [
                'Bucket' => '<string>',
                'Key' => '<string>',
            ],
            'DataEndTime' => <DateTime>,
            'DataInputConfiguration' => [
                'InferenceInputNameConfiguration' => [
                    'ComponentTimestampDelimiter' => '<string>',
                    'TimestampFormat' => '<string>',
                ],
                'InputTimeZoneOffset' => '<string>',
                'S3InputConfiguration' => [
                    'Bucket' => '<string>',
                    'Prefix' => '<string>',
                ],
            ],
            'DataOutputConfiguration' => [
                'KmsKeyId' => '<string>',
                'S3OutputConfiguration' => [
                    'Bucket' => '<string>',
                    'Prefix' => '<string>',
                ],
            ],
            'DataStartTime' => <DateTime>,
            'FailedReason' => '<string>',
            'InferenceSchedulerArn' => '<string>',
            'InferenceSchedulerName' => '<string>',
            'ModelArn' => '<string>',
            'ModelName' => '<string>',
            'ModelVersion' => <integer>,
            'ModelVersionArn' => '<string>',
            'ScheduledStartTime' => <DateTime>,
            'Status' => 'IN_PROGRESS|SUCCESS|FAILED',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
InferenceExecutionSummaries
Type: Array of InferenceExecutionSummary structures

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.

If you don't supply the InferenceSchedulerName request parameter, or if you supply the name of an inference scheduler that doesn't exist, ListInferenceExecutions returns an empty array in InferenceExecutionSummaries.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference executions.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListInferenceSchedulers

$result = $client->listInferenceSchedulers([/* ... */]);
$promise = $client->listInferenceSchedulersAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listInferenceSchedulers([
    'InferenceSchedulerNameBeginsWith' => '<string>',
    'MaxResults' => <integer>,
    'ModelName' => '<string>',
    'NextToken' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]);

Parameter Details

Members
InferenceSchedulerNameBeginsWith
Type: string

The beginning of the name of the inference schedulers to be listed.

MaxResults
Type: int

Specifies the maximum number of inference schedulers to list.

ModelName
Type: string

The name of the machine learning model used by the inference scheduler to be listed.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference schedulers.

Status
Type: string

Specifies the current status of the inference schedulers.

Result Syntax

[
    'InferenceSchedulerSummaries' => [
        [
            'DataDelayOffsetInMinutes' => <integer>,
            'DataUploadFrequency' => 'PT5M|PT10M|PT15M|PT30M|PT1H',
            'InferenceSchedulerArn' => '<string>',
            'InferenceSchedulerName' => '<string>',
            'LatestInferenceResult' => 'ANOMALOUS|NORMAL',
            'ModelArn' => '<string>',
            'ModelName' => '<string>',
            'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
InferenceSchedulerSummaries
Type: Array of InferenceSchedulerSummary structures

Provides information about the specified inference scheduler, including data upload frequency, model name and ARN, and status.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of inference schedulers.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListLabelGroups

$result = $client->listLabelGroups([/* ... */]);
$promise = $client->listLabelGroupsAsync([/* ... */]);

Returns a list of the label groups.

Parameter Syntax

$result = $client->listLabelGroups([
    'LabelGroupNameBeginsWith' => '<string>',
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members
LabelGroupNameBeginsWith
Type: string

The beginning of the name of the label groups to be listed.

MaxResults
Type: int

Specifies the maximum number of label groups to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of label groups.

Result Syntax

[
    'LabelGroupSummaries' => [
        [
            'CreatedAt' => <DateTime>,
            'LabelGroupArn' => '<string>',
            'LabelGroupName' => '<string>',
            'UpdatedAt' => <DateTime>,
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
LabelGroupSummaries
Type: Array of LabelGroupSummary structures

A summary of the label groups.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of label groups.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListLabels

$result = $client->listLabels([/* ... */]);
$promise = $client->listLabelsAsync([/* ... */]);

Provides a list of labels.

Parameter Syntax

$result = $client->listLabels([
    'Equipment' => '<string>',
    'FaultCode' => '<string>',
    'IntervalEndTime' => <integer || string || DateTime>,
    'IntervalStartTime' => <integer || string || DateTime>,
    'LabelGroupName' => '<string>', // REQUIRED
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members
Equipment
Type: string

Lists the labels that pertain to a particular piece of equipment.

FaultCode
Type: string

Returns labels with a particular fault code.

IntervalEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Returns all labels with a start time earlier than the end time given.

IntervalStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Returns all the labels with a end time equal to or later than the start time given.

LabelGroupName
Required: Yes
Type: string

Returns the name of the label group.

MaxResults
Type: int

Specifies the maximum number of labels to list.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of label groups.

Result Syntax

[
    'LabelSummaries' => [
        [
            'CreatedAt' => <DateTime>,
            'EndTime' => <DateTime>,
            'Equipment' => '<string>',
            'FaultCode' => '<string>',
            'LabelGroupArn' => '<string>',
            'LabelGroupName' => '<string>',
            'LabelId' => '<string>',
            'Rating' => 'ANOMALY|NO_ANOMALY|NEUTRAL',
            'StartTime' => <DateTime>,
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
LabelSummaries
Type: Array of LabelSummary structures

A summary of the items in the label group.

If you don't supply the LabelGroupName request parameter, or if you supply the name of a label group that doesn't exist, ListLabels returns an empty array in LabelSummaries.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of datasets.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListModelVersions

$result = $client->listModelVersions([/* ... */]);
$promise = $client->listModelVersionsAsync([/* ... */]);

Generates a list of all model versions for a given model, including the model version, model version ARN, and status. To list a subset of versions, use the MaxModelVersion and MinModelVersion fields.

Parameter Syntax

$result = $client->listModelVersions([
    'CreatedAtEndTime' => <integer || string || DateTime>,
    'CreatedAtStartTime' => <integer || string || DateTime>,
    'MaxModelVersion' => <integer>,
    'MaxResults' => <integer>,
    'MinModelVersion' => <integer>,
    'ModelName' => '<string>', // REQUIRED
    'NextToken' => '<string>',
    'SourceType' => 'TRAINING|RETRAINING|IMPORT',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
]);

Parameter Details

Members
CreatedAtEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Filter results to return all the model versions created before this time.

CreatedAtStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Filter results to return all the model versions created after this time.

MaxModelVersion
Type: long (int|float)

Specifies the highest version of the model to return in the list.

MaxResults
Type: int

Specifies the maximum number of machine learning model versions to list.

MinModelVersion
Type: long (int|float)

Specifies the lowest version of the model to return in the list.

ModelName
Required: Yes
Type: string

Then name of the machine learning model for which the model versions are to be listed.

NextToken
Type: string

If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versions. Use this token in the NextToken field in the request to list the next page of results.

SourceType
Type: string

Filter the results based on the way the model version was generated.

Status
Type: string

Filter the results based on the current status of the model version.

Result Syntax

[
    'ModelVersionSummaries' => [
        [
            'CreatedAt' => <DateTime>,
            'ModelArn' => '<string>',
            'ModelName' => '<string>',
            'ModelQuality' => 'QUALITY_THRESHOLD_MET|CANNOT_DETERMINE_QUALITY|POOR_QUALITY_DETECTED',
            'ModelVersion' => <integer>,
            'ModelVersionArn' => '<string>',
            'SourceType' => 'TRAINING|RETRAINING|IMPORT',
            'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
ModelVersionSummaries
Type: Array of ModelVersionSummary structures

Provides information on the specified model version, including the created time, model and dataset ARNs, and status.

If you don't supply the ModelName request parameter, or if you supply the name of a model that doesn't exist, ListModelVersions returns an empty array in ModelVersionSummaries.

NextToken
Type: string

If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versions. Use this token in the NextToken field in the request to list the next page of results.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListModels

$result = $client->listModels([/* ... */]);
$promise = $client->listModelsAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listModels([
    'DatasetNameBeginsWith' => '<string>',
    'MaxResults' => <integer>,
    'ModelNameBeginsWith' => '<string>',
    'NextToken' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
]);

Parameter Details

Members
DatasetNameBeginsWith
Type: string

The beginning of the name of the dataset of the machine learning models to be listed.

MaxResults
Type: int

Specifies the maximum number of machine learning models to list.

ModelNameBeginsWith
Type: string

The beginning of the name of the machine learning models being listed.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of machine learning models.

Status
Type: string

The status of the machine learning model.

Result Syntax

[
    'ModelSummaries' => [
        [
            'ActiveModelVersion' => <integer>,
            'ActiveModelVersionArn' => '<string>',
            'CreatedAt' => <DateTime>,
            'DatasetArn' => '<string>',
            'DatasetName' => '<string>',
            'LatestScheduledRetrainingModelVersion' => <integer>,
            'LatestScheduledRetrainingStartTime' => <DateTime>,
            'LatestScheduledRetrainingStatus' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS|CANCELED',
            'ModelArn' => '<string>',
            'ModelDiagnosticsOutputConfiguration' => [
                'KmsKeyId' => '<string>',
                'S3OutputConfiguration' => [
                    'Bucket' => '<string>',
                    'Prefix' => '<string>',
                ],
            ],
            'ModelName' => '<string>',
            'ModelQuality' => 'QUALITY_THRESHOLD_MET|CANNOT_DETERMINE_QUALITY|POOR_QUALITY_DETECTED',
            'NextScheduledRetrainingStartDate' => <DateTime>,
            'RetrainingSchedulerStatus' => 'PENDING|RUNNING|STOPPING|STOPPED',
            'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
        ],
        // ...
    ],
    'NextToken' => '<string>',
]

Result Details

Members
ModelSummaries
Type: Array of ModelSummary structures

Provides information on the specified model, including created time, model and dataset ARNs, and status.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of machine learning models.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListRetrainingSchedulers

$result = $client->listRetrainingSchedulers([/* ... */]);
$promise = $client->listRetrainingSchedulersAsync([/* ... */]);

Lists all retraining schedulers in your account, filtering by model name prefix and status.

Parameter Syntax

$result = $client->listRetrainingSchedulers([
    'MaxResults' => <integer>,
    'ModelNameBeginsWith' => '<string>',
    'NextToken' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]);

Parameter Details

Members
MaxResults
Type: int

Specifies the maximum number of retraining schedulers to list.

ModelNameBeginsWith
Type: string

Specify this field to only list retraining schedulers whose machine learning models begin with the value you specify.

NextToken
Type: string

If the number of results exceeds the maximum, a pagination token is returned. Use the token in the request to show the next page of retraining schedulers.

Status
Type: string

Specify this field to only list retraining schedulers whose status matches the value you specify.

Result Syntax

[
    'NextToken' => '<string>',
    'RetrainingSchedulerSummaries' => [
        [
            'LookbackWindow' => '<string>',
            'ModelArn' => '<string>',
            'ModelName' => '<string>',
            'RetrainingFrequency' => '<string>',
            'RetrainingStartDate' => <DateTime>,
            'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
        ],
        // ...
    ],
]

Result Details

Members
NextToken
Type: string

If the number of results exceeds the maximum, this pagination token is returned. Use this token in the request to show the next page of retraining schedulers.

RetrainingSchedulerSummaries
Type: Array of RetrainingSchedulerSummary structures

Provides information on the specified retraining scheduler, including the model name, model ARN, status, and start date.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Listing retraining schedulers

$result = $client->listRetrainingSchedulers([
    'MaxResults' => 50,
]);

Result syntax:

[
    'RetrainingSchedulerSummaries' => [
        [
            'LookbackWindow' => 'P180D',
            'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-1/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
            'ModelName' => 'sample-model-1',
            'RetrainingFrequency' => 'P1M',
            'RetrainingStartDate' => ,
            'Status' => 'RUNNING',
        ],
        [
            'LookbackWindow' => 'P180D',
            'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-2/a1b2c3d4-5678-90ab-cdef-EXAMPLE22222',
            'ModelName' => 'sample-model-2',
            'RetrainingFrequency' => 'P30D',
            'RetrainingStartDate' => ,
            'Status' => 'RUNNING',
        ],
        [
            'LookbackWindow' => 'P360D',
            'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model-3/a1b2c3d4-5678-90ab-cdef-EXAMPLE33333',
            'ModelName' => 'sample-model-3',
            'RetrainingFrequency' => 'P1M',
            'RetrainingStartDate' => ,
            'Status' => 'STOPPED',
        ],
    ],
]

ListSensorStatistics

$result = $client->listSensorStatistics([/* ... */]);
$promise = $client->listSensorStatisticsAsync([/* ... */]);

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.

Parameter Syntax

$result = $client->listSensorStatistics([
    'DatasetName' => '<string>', // REQUIRED
    'IngestionJobId' => '<string>',
    'MaxResults' => <integer>,
    'NextToken' => '<string>',
]);

Parameter Details

Members
DatasetName
Required: Yes
Type: string

The name of the dataset associated with the list of Sensor Statistics.

IngestionJobId
Type: 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.

MaxResults
Type: int

Specifies the maximum number of sensors for which to retrieve statistics.

NextToken
Type: string

An opaque pagination token indicating where to continue the listing of sensor statistics.

Result Syntax

[
    'NextToken' => '<string>',
    'SensorStatisticsSummaries' => [
        [
            'CategoricalValues' => [
                'NumberOfCategory' => <integer>,
                'Status' => 'POTENTIAL_ISSUE_DETECTED|NO_ISSUE_DETECTED',
            ],
            'ComponentName' => '<string>',
            'DataEndTime' => <DateTime>,
            'DataExists' => true || false,
            'DataStartTime' => <DateTime>,
            'DuplicateTimestamps' => [
                'Count' => <integer>,
                'Percentage' => <float>,
            ],
            'InvalidDateEntries' => [
                'Count' => <integer>,
                'Percentage' => <float>,
            ],
            'InvalidValues' => [
                'Count' => <integer>,
                'Percentage' => <float>,
            ],
            'LargeTimestampGaps' => [
                'MaxTimestampGapInDays' => <integer>,
                'NumberOfLargeTimestampGaps' => <integer>,
                'Status' => 'POTENTIAL_ISSUE_DETECTED|NO_ISSUE_DETECTED',
            ],
            'MissingValues' => [
                'Count' => <integer>,
                'Percentage' => <float>,
            ],
            'MonotonicValues' => [
                'Monotonicity' => 'DECREASING|INCREASING|STATIC',
                'Status' => 'POTENTIAL_ISSUE_DETECTED|NO_ISSUE_DETECTED',
            ],
            'MultipleOperatingModes' => [
                'Status' => 'POTENTIAL_ISSUE_DETECTED|NO_ISSUE_DETECTED',
            ],
            'SensorName' => '<string>',
        ],
        // ...
    ],
]

Result Details

Members
NextToken
Type: string

An opaque pagination token indicating where to continue the listing of sensor statistics.

SensorStatisticsSummaries
Type: Array of SensorStatisticsSummary structures

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.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ListTagsForResource

$result = $client->listTagsForResource([/* ... */]);
$promise = $client->listTagsForResourceAsync([/* ... */]);

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

Parameter Syntax

$result = $client->listTagsForResource([
    'ResourceArn' => '<string>', // REQUIRED
]);

Parameter Details

Members
ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the resource (such as the dataset or model) that is the focus of the ListTagsForResource operation.

Result Syntax

[
    'Tags' => [
        [
            'Key' => '<string>',
            'Value' => '<string>',
        ],
        // ...
    ],
]

Result Details

Members
Tags
Type: Array of Tag structures

Any tags associated with the resource.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

PutResourcePolicy

$result = $client->putResourcePolicy([/* ... */]);
$promise = $client->putResourcePolicyAsync([/* ... */]);

Creates a resource control policy for a given resource.

Parameter Syntax

$result = $client->putResourcePolicy([
    'ClientToken' => '<string>', // REQUIRED
    'PolicyRevisionId' => '<string>',
    'ResourceArn' => '<string>', // REQUIRED
    'ResourcePolicy' => '<string>', // REQUIRED
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

PolicyRevisionId
Type: string

A unique identifier for a revision of the resource policy.

ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the resource for which the policy is being created.

ResourcePolicy
Required: Yes
Type: string

The JSON-formatted resource policy to create.

Result Syntax

[
    'PolicyRevisionId' => '<string>',
    'ResourceArn' => '<string>',
]

Result Details

Members
PolicyRevisionId
Type: string

A unique identifier for a revision of the resource policy.

ResourceArn
Type: string

The Amazon Resource Name (ARN) of the resource for which the policy was created.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

StartDataIngestionJob

$result = $client->startDataIngestionJob([/* ... */]);
$promise = $client->startDataIngestionJobAsync([/* ... */]);

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

Parameter Syntax

$result = $client->startDataIngestionJob([
    'ClientToken' => '<string>', // REQUIRED
    'DatasetName' => '<string>', // REQUIRED
    'IngestionInputConfiguration' => [ // REQUIRED
        'S3InputConfiguration' => [ // REQUIRED
            'Bucket' => '<string>', // REQUIRED
            'KeyPattern' => '<string>',
            'Prefix' => '<string>',
        ],
    ],
    'RoleArn' => '<string>', // REQUIRED
]);

Parameter Details

Members
ClientToken
Required: Yes
Type: string

A unique identifier for the request. If you do not set the client request token, Amazon Lookout for Equipment generates one.

DatasetName
Required: Yes
Type: string

The name of the dataset being used by the data ingestion job.

IngestionInputConfiguration
Required: Yes
Type: IngestionInputConfiguration structure

Specifies information for the input data for the data ingestion job, including dataset S3 location.

RoleArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source for the data ingestion job.

Result Syntax

[
    'JobId' => '<string>',
    'Status' => 'IN_PROGRESS|SUCCESS|FAILED|IMPORT_IN_PROGRESS',
]

Result Details

Members
JobId
Type: string

Indicates the job ID of the data ingestion job.

Status
Type: string

Indicates the status of the StartDataIngestionJob operation.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

StartInferenceScheduler

$result = $client->startInferenceScheduler([/* ... */]);
$promise = $client->startInferenceSchedulerAsync([/* ... */]);

Starts an inference scheduler.

Parameter Syntax

$result = $client->startInferenceScheduler([
    'InferenceSchedulerName' => '<string>', // REQUIRED
]);

Parameter Details

Members
InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler to be started.

Result Syntax

[
    'InferenceSchedulerArn' => '<string>',
    'InferenceSchedulerName' => '<string>',
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler being started.

InferenceSchedulerName
Type: string

The name of the inference scheduler being started.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model being used by the inference scheduler.

ModelName
Type: string

The name of the machine learning model being used by the inference scheduler.

Status
Type: string

Indicates the status of the inference scheduler.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

StartRetrainingScheduler

$result = $client->startRetrainingScheduler([/* ... */]);
$promise = $client->startRetrainingSchedulerAsync([/* ... */]);

Starts a retraining scheduler.

Parameter Syntax

$result = $client->startRetrainingScheduler([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the model whose retraining scheduler you want to start.

Result Syntax

[
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
ModelArn
Type: string

The ARN of the model whose retraining scheduler is being started.

ModelName
Type: string

The name of the model whose retraining scheduler is being started.

Status
Type: string

The status of the retraining scheduler.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Starts a retraining scheduler

$result = $client->startRetrainingScheduler([
    'ModelName' => 'sample-model',
]);

Result syntax:

[
    'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
    'ModelName' => 'sample-model',
    'Status' => 'PENDING',
]

StopInferenceScheduler

$result = $client->stopInferenceScheduler([/* ... */]);
$promise = $client->stopInferenceSchedulerAsync([/* ... */]);

Stops an inference scheduler.

Parameter Syntax

$result = $client->stopInferenceScheduler([
    'InferenceSchedulerName' => '<string>', // REQUIRED
]);

Parameter Details

Members
InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler to be stopped.

Result Syntax

[
    'InferenceSchedulerArn' => '<string>',
    'InferenceSchedulerName' => '<string>',
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference schedule being stopped.

InferenceSchedulerName
Type: string

The name of the inference scheduler being stopped.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler being stopped.

ModelName
Type: string

The name of the machine learning model used by the inference scheduler being stopped.

Status
Type: string

Indicates the status of the inference scheduler.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

StopRetrainingScheduler

$result = $client->stopRetrainingScheduler([/* ... */]);
$promise = $client->stopRetrainingSchedulerAsync([/* ... */]);

Stops a retraining scheduler.

Parameter Syntax

$result = $client->stopRetrainingScheduler([
    'ModelName' => '<string>', // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the model whose retraining scheduler you want to stop.

Result Syntax

[
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'Status' => 'PENDING|RUNNING|STOPPING|STOPPED',
]

Result Details

Members
ModelArn
Type: string

The ARN of the model whose retraining scheduler is being stopped.

ModelName
Type: string

The name of the model whose retraining scheduler is being stopped.

Status
Type: string

The status of the retraining scheduler.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Stops a retraining scheduler

$result = $client->stopRetrainingScheduler([
    'ModelName' => 'sample-model',
]);

Result syntax:

[
    'ModelArn' => 'arn:aws:lookoutequipment:us-east-1:123456789012:model/sample-model/a1b2c3d4-5678-90ab-cdef-EXAMPLE11111',
    'ModelName' => 'sample-model',
    'Status' => 'STOPPING',
]

TagResource

$result = $client->tagResource([/* ... */]);
$promise = $client->tagResourceAsync([/* ... */]);

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.

Parameter Syntax

$result = $client->tagResource([
    'ResourceArn' => '<string>', // REQUIRED
    'Tags' => [ // REQUIRED
        [
            'Key' => '<string>', // REQUIRED
            'Value' => '<string>', // REQUIRED
        ],
        // ...
    ],
]);

Parameter Details

Members
ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the specific resource to which the tag should be associated.

Tags
Required: Yes
Type: Array of Tag structures

The tag or tags to be associated with a specific resource. Both the tag key and value are specified.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ServiceQuotaExceededException:

Resource limitations have been exceeded.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

UntagResource

$result = $client->untagResource([/* ... */]);
$promise = $client->untagResourceAsync([/* ... */]);

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

Parameter Syntax

$result = $client->untagResource([
    'ResourceArn' => '<string>', // REQUIRED
    'TagKeys' => ['<string>', ...], // REQUIRED
]);

Parameter Details

Members
ResourceArn
Required: Yes
Type: string

The Amazon Resource Name (ARN) of the resource to which the tag is currently associated.

TagKeys
Required: Yes
Type: Array of strings

Specifies the key of the tag to be removed from a specified resource.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

UpdateActiveModelVersion

$result = $client->updateActiveModelVersion([/* ... */]);
$promise = $client->updateActiveModelVersionAsync([/* ... */]);

Sets the active model version for a given machine learning model.

Parameter Syntax

$result = $client->updateActiveModelVersion([
    'ModelName' => '<string>', // REQUIRED
    'ModelVersion' => <integer>, // REQUIRED
]);

Parameter Details

Members
ModelName
Required: Yes
Type: string

The name of the machine learning model for which the active model version is being set.

ModelVersion
Required: Yes
Type: long (int|float)

The version of the machine learning model for which the active model version is being set.

Result Syntax

[
    'CurrentActiveVersion' => <integer>,
    'CurrentActiveVersionArn' => '<string>',
    'ModelArn' => '<string>',
    'ModelName' => '<string>',
    'PreviousActiveVersion' => <integer>,
    'PreviousActiveVersionArn' => '<string>',
]

Result Details

Members
CurrentActiveVersion
Type: long (int|float)

The version that is currently active of the machine learning model for which the active model version was set.

CurrentActiveVersionArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model version that is the current active model version.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model for which the active model version was set.

ModelName
Type: string

The name of the machine learning model for which the active model version was set.

PreviousActiveVersion
Type: long (int|float)

The previous version that was active of the machine learning model for which the active model version was set.

PreviousActiveVersionArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model version that was the previous active model version.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

UpdateInferenceScheduler

$result = $client->updateInferenceScheduler([/* ... */]);
$promise = $client->updateInferenceSchedulerAsync([/* ... */]);

Updates an inference scheduler.

Parameter Syntax

$result = $client->updateInferenceScheduler([
    'DataDelayOffsetInMinutes' => <integer>,
    'DataInputConfiguration' => [
        'InferenceInputNameConfiguration' => [
            'ComponentTimestampDelimiter' => '<string>',
            'TimestampFormat' => '<string>',
        ],
        'InputTimeZoneOffset' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'DataOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [ // REQUIRED
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'DataUploadFrequency' => 'PT5M|PT10M|PT15M|PT30M|PT1H',
    'InferenceSchedulerName' => '<string>', // REQUIRED
    'RoleArn' => '<string>',
]);

Parameter Details

Members
DataDelayOffsetInMinutes
Type: long (int|float)

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.

DataInputConfiguration
Type: InferenceInputConfiguration structure

Specifies information for the input data for the inference scheduler, including delimiter, format, and dataset location.

DataOutputConfiguration

Specifies information for the output results from the inference scheduler, including the output S3 location.

DataUploadFrequency
Type: string

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.

InferenceSchedulerName
Required: Yes
Type: string

The name of the inference scheduler to be updated.

RoleArn
Type: string

The Amazon Resource Name (ARN) of a role with permission to access the data source for the inference scheduler.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

UpdateLabelGroup

$result = $client->updateLabelGroup([/* ... */]);
$promise = $client->updateLabelGroupAsync([/* ... */]);

Updates the label group.

Parameter Syntax

$result = $client->updateLabelGroup([
    'FaultCodes' => ['<string>', ...],
    'LabelGroupName' => '<string>', // REQUIRED
]);

Parameter Details

Members
FaultCodes
Type: Array of strings

Updates the code indicating the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelGroupName
Required: Yes
Type: string

The name of the label group to be updated.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

UpdateModel

$result = $client->updateModel([/* ... */]);
$promise = $client->updateModelAsync([/* ... */]);

Updates a model in the account.

Parameter Syntax

$result = $client->updateModel([
    'LabelsInputConfiguration' => [
        'LabelGroupName' => '<string>',
        'S3InputConfiguration' => [
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'ModelDiagnosticsOutputConfiguration' => [
        'KmsKeyId' => '<string>',
        'S3OutputConfiguration' => [ // REQUIRED
            'Bucket' => '<string>', // REQUIRED
            'Prefix' => '<string>',
        ],
    ],
    'ModelName' => '<string>', // REQUIRED
    'RoleArn' => '<string>',
]);

Parameter Details

Members
LabelsInputConfiguration
Type: LabelsInputConfiguration structure

Contains the configuration information for the S3 location being used to hold label data.

ModelDiagnosticsOutputConfiguration

The Amazon S3 location where you want Amazon Lookout for Equipment to save the pointwise model diagnostics for the model. You must also specify the RoleArn request parameter.

ModelName
Required: Yes
Type: string

The name of the model to update.

RoleArn
Type: string

The ARN of the model to update.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Updates a model

$result = $client->updateModel([
    'LabelsInputConfiguration' => [
        'LabelGroupName' => 'sample-label-group',
    ],
    'ModelName' => 'sample-model',
]);

UpdateRetrainingScheduler

$result = $client->updateRetrainingScheduler([/* ... */]);
$promise = $client->updateRetrainingSchedulerAsync([/* ... */]);

Updates a retraining scheduler.

Parameter Syntax

$result = $client->updateRetrainingScheduler([
    'LookbackWindow' => '<string>',
    'ModelName' => '<string>', // REQUIRED
    'PromoteMode' => 'MANAGED|MANUAL',
    'RetrainingFrequency' => '<string>',
    'RetrainingStartDate' => <integer || string || DateTime>,
]);

Parameter Details

Members
LookbackWindow
Type: string

The number of past days of data that will be used for retraining.

ModelName
Required: Yes
Type: string

The name of the model whose retraining scheduler you want to update.

PromoteMode
Type: string

Indicates how the service will use new models. In MANAGED mode, new models will automatically be used for inference if they have better performance than the current model. In MANUAL mode, the new models will not be used until they are manually activated.

RetrainingFrequency
Type: string

This parameter uses the ISO 8601 standard to set the frequency at which you want retraining to occur in terms of Years, Months, and/or Days (note: other parameters like Time are not currently supported). The minimum value is 30 days (P30D) and the maximum value is 1 year (P1Y). For example, the following values are valid:

  • P3M15D – Every 3 months and 15 days

  • P2M – Every 2 months

  • P150D – Every 150 days

RetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

Result Syntax

[]

Result Details

The results for this operation are always empty.

Errors

ValidationException:

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

ResourceNotFoundException:

The resource requested could not be found. Verify the resource ID and retry your request.

ConflictException:

The request could not be completed due to a conflict with the current state of the target resource.

ThrottlingException:

The request was denied due to request throttling.

AccessDeniedException:

The request could not be completed because you do not have access to the resource.

InternalServerException:

Processing of the request has failed because of an unknown error, exception or failure.

Examples

Example 1: Updates a retraining scheduler

$result = $client->updateRetrainingScheduler([
    'ModelName' => 'sample-model',
    'RetrainingFrequency' => 'P1Y',
    'RetrainingStartDate' => ,
]);

Shapes

AccessDeniedException

Description

The request could not be completed because you do not have access to the resource.

Members
Message
Required: Yes
Type: string

CategoricalValues

Description

Entity that comprises information on categorical values in data.

Members
NumberOfCategory
Type: int

Indicates the number of categories in the data.

Status
Required: Yes
Type: string

Indicates whether there is a potential data issue related to categorical values.

ConflictException

Description

The request could not be completed due to a conflict with the current state of the target resource.

Members
Message
Required: Yes
Type: string

CountPercent

Description

Entity that comprises information of count and percentage.

Members
Count
Required: Yes
Type: int

Indicates the count of occurences of the given statistic.

Percentage
Required: Yes
Type: float

Indicates the percentage of occurances of the given statistic.

DataIngestionJobSummary

Description

Provides information about a specified data ingestion job, including dataset information, data ingestion configuration, and status.

Members
DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset used in the data ingestion job.

DatasetName
Type: string

The name of the dataset used for the data ingestion job.

IngestionInputConfiguration
Type: IngestionInputConfiguration structure

Specifies information for the input data for the data inference job, including data Amazon S3 location parameters.

JobId
Type: string

Indicates the job ID of the data ingestion job.

Status
Type: string

Indicates the status of the data ingestion job.

DataPreProcessingConfiguration

Description

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

Members
TargetSamplingRate
Type: string

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

DataQualitySummary

Description

DataQualitySummary gives aggregated statistics over all the sensors about a completed ingestion job. It primarily gives more information about statistics over different incorrect data like MissingCompleteSensorData, MissingSensorData, UnsupportedDateFormats, InsufficientSensorData, DuplicateTimeStamps.

Members
DuplicateTimestamps
Required: Yes
Type: DuplicateTimestamps structure

Parameter that gives information about duplicate timestamps in the input data.

InsufficientSensorData
Required: Yes
Type: InsufficientSensorData structure

Parameter that gives information about insufficient data for sensors in the dataset. This includes information about those sensors that have complete data missing and those with a short date range.

InvalidSensorData
Required: Yes
Type: InvalidSensorData structure

Parameter that gives information about data that is invalid over all the sensors in the input data.

MissingSensorData
Required: Yes
Type: MissingSensorData structure

Parameter that gives information about data that is missing over all the sensors in the input data.

UnsupportedTimestamps
Required: Yes
Type: UnsupportedTimestamps structure

Parameter that gives information about unsupported timestamps in the input data.

DatasetSchema

Description

Provides information about the data schema used with the given dataset.

Members
InlineDataSchema
Type: string (string|number|array|map or anything parsable by json_encode)

The data schema used within the given dataset.

DatasetSummary

Description

Contains information about the specific data set, including name, ARN, and status.

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the dataset was created in Amazon Lookout for Equipment.

DatasetArn
Type: string

The Amazon Resource Name (ARN) of the specified dataset.

DatasetName
Type: string

The name of the dataset.

Status
Type: string

Indicates the status of the dataset.

DuplicateTimestamps

Description

Entity that comprises information abount duplicate timestamps in the dataset.

Members
TotalNumberOfDuplicateTimestamps
Required: Yes
Type: int

Indicates the total number of duplicate timestamps.

InferenceEventSummary

Description

Contains information about the specific inference event, including start and end time, diagnostics information, event duration and so on.

Members
Diagnostics
Type: string

An array which specifies the names and values of all sensors contributing to an inference event.

EventDurationInSeconds
Type: long (int|float)

Indicates the size of an inference event in seconds.

EventEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the ending time of an inference event.

EventStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the starting time of an inference event.

InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler being used for the inference event.

InferenceSchedulerName
Type: string

The name of the inference scheduler being used for the inference events.

InferenceExecutionSummary

Description

Contains information about the specific inference execution, including input and output data configuration, inference scheduling information, status, and so on.

Members
CustomerResultObject
Type: S3Object structure

The S3 object that the inference execution results were uploaded to.

DataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset at which the inference execution stopped.

DataInputConfiguration
Type: InferenceInputConfiguration structure

Specifies configuration information for the input data for the inference scheduler, including delimiter, format, and dataset location.

DataOutputConfiguration

Specifies configuration information for the output results from for the inference execution, including the output Amazon S3 location.

DataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference in the dataset at which the inference execution began.

FailedReason
Type: string

Specifies the reason for failure when an inference execution has failed.

InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler being used for the inference execution.

InferenceSchedulerName
Type: string

The name of the inference scheduler being used for the inference execution.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model used for the inference execution.

ModelName
Type: string

The name of the machine learning model being used for the inference execution.

ModelVersion
Type: long (int|float)

The model version used for the inference execution.

ModelVersionArn
Type: string

The Amazon Resource Number (ARN) of the model version used for the inference execution.

ScheduledStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the start time at which the inference scheduler began the specific inference execution.

Status
Type: string

Indicates the status of the inference execution.

InferenceInputConfiguration

Description

Specifies configuration information for the input data for the inference, including Amazon S3 location of input data..

Members
InferenceInputNameConfiguration

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

InputTimeZoneOffset
Type: string

Indicates the difference between your time zone and Coordinated Universal Time (UTC).

S3InputConfiguration

Specifies configuration information for the input data for the inference, including Amazon S3 location of input data.

InferenceInputNameConfiguration

Description

Specifies configuration information for the input data for the inference, including timestamp format and delimiter.

Members
ComponentTimestampDelimiter
Type: string

Indicates the delimiter character used between items in the data.

TimestampFormat
Type: string

The format of the timestamp, whether Epoch time, or standard, with or without hyphens (-).

InferenceOutputConfiguration

Description

Specifies configuration information for the output results from for the inference, including KMS key ID and output S3 location.

Members
KmsKeyId
Type: string

The ID number for the KMS key key used to encrypt the inference output.

S3OutputConfiguration
Required: Yes
Type: InferenceS3OutputConfiguration structure

Specifies configuration information for the output results from for the inference, output S3 location.

InferenceS3InputConfiguration

Description

Specifies configuration information for the input data for the inference, including input data S3 location.

Members
Bucket
Required: Yes
Type: string

The bucket containing the input dataset for the inference.

Prefix
Type: string

The prefix for the S3 bucket used for the input data for the inference.

InferenceS3OutputConfiguration

Description

Specifies configuration information for the output results from the inference, including output S3 location.

Members
Bucket
Required: Yes
Type: string

The bucket containing the output results from the inference

Prefix
Type: string

The prefix for the S3 bucket used for the output results from the inference.

InferenceSchedulerSummary

Description

Contains information about the specific inference scheduler, including data delay offset, model name and ARN, status, and so on.

Members
DataDelayOffsetInMinutes
Type: long (int|float)

A period of time (in minutes) by which inference on the data is delayed after the data starts. For instance, if an offset delay time of five minutes was selected, 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.

DataUploadFrequency
Type: string

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.

InferenceSchedulerArn
Type: string

The Amazon Resource Name (ARN) of the inference scheduler.

InferenceSchedulerName
Type: string

The name of the inference scheduler.

LatestInferenceResult
Type: string

Indicates whether the latest execution for the inference scheduler was Anomalous (anomalous events found) or Normal (no anomalous events found).

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model used by the inference scheduler.

ModelName
Type: string

The name of the machine learning model used for the inference scheduler.

Status
Type: string

Indicates the status of the inference scheduler.

IngestedFilesSummary

Description

Gives statistics about how many files have been ingested, and which files have not been ingested, for a particular ingestion job.

Members
DiscardedFiles
Type: Array of S3Object structures

Indicates the number of files that were discarded. A file could be discarded because its format is invalid (for example, a jpg or pdf) or not readable.

IngestedNumberOfFiles
Required: Yes
Type: int

Indicates the number of files that were successfully ingested.

TotalNumberOfFiles
Required: Yes
Type: int

Indicates the total number of files that were submitted for ingestion.

IngestionInputConfiguration

Description

Specifies configuration information for the input data for the data ingestion job, including input data S3 location.

Members
S3InputConfiguration
Required: Yes
Type: IngestionS3InputConfiguration structure

The location information for the S3 bucket used for input data for the data ingestion.

IngestionS3InputConfiguration

Description

Specifies S3 configuration information for the input data for the data ingestion job.

Members
Bucket
Required: Yes
Type: string

The name of the S3 bucket used for the input data for the data ingestion.

KeyPattern
Type: string

The pattern for matching the Amazon S3 files that will be used for ingestion. If the schema was created previously without any KeyPattern, then the default KeyPattern {prefix}/{component_name}/* is used to download files from Amazon S3 according to the schema. This field is required when ingestion is being done for the first time.

Valid Values: {prefix}/{component_name}_* | {prefix}/{component_name}/* | {prefix}/{component_name}[DELIMITER]* (Allowed delimiters : space, dot, underscore, hyphen)

Prefix
Type: string

The prefix for the S3 location being used for the input data for the data ingestion.

InsufficientSensorData

Description

Entity that comprises aggregated information on sensors having insufficient data.

Members
MissingCompleteSensorData
Required: Yes
Type: MissingCompleteSensorData structure

Parameter that describes the total number of sensors that have data completely missing for it.

SensorsWithShortDateRange
Required: Yes
Type: SensorsWithShortDateRange structure

Parameter that describes the total number of sensors that have a short date range of less than 14 days of data overall.

InternalServerException

Description

Processing of the request has failed because of an unknown error, exception or failure.

Members
Message
Required: Yes
Type: string

InvalidSensorData

Description

Entity that comprises aggregated information on sensors having insufficient data.

Members
AffectedSensorCount
Required: Yes
Type: int

Indicates the number of sensors that have at least some invalid values.

TotalNumberOfInvalidValues
Required: Yes
Type: int

Indicates the total number of invalid values across all the sensors.

LabelGroupSummary

Description

Contains information about the label group.

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label group was created.

LabelGroupArn
Type: string

The Amazon Resource Name (ARN) of the label group.

LabelGroupName
Type: string

The name of the label group.

UpdatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label group was updated.

LabelSummary

Description

Information about the label.

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the label was created.

EndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The timestamp indicating the end of the label.

Equipment
Type: string

Indicates that a label pertains to a particular piece of equipment.

FaultCode
Type: string

Indicates the type of anomaly associated with the label.

Data in this field will be retained for service usage. Follow best practices for the security of your data.

LabelGroupArn
Type: string

The Amazon Resource Name (ARN) of the label group.

LabelGroupName
Type: string

The name of the label group.

LabelId
Type: string

The ID of the label.

Rating
Type: string

Indicates whether a labeled event represents an anomaly.

StartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

The timestamp indicating the start of the label.

LabelsInputConfiguration

Description

Contains the configuration information for the S3 location being used to hold label data.

Members
LabelGroupName
Type: string

The name of the label group to be used for label data.

S3InputConfiguration
Type: LabelsS3InputConfiguration structure

Contains location information for the S3 location being used for label data.

LabelsS3InputConfiguration

Description

The location information (prefix and bucket name) for the s3 location being used for label data.

Members
Bucket
Required: Yes
Type: string

The name of the S3 bucket holding the label data.

Prefix
Type: string

The prefix for the S3 bucket used for the label data.

LargeTimestampGaps

Description

Entity that comprises information on large gaps between consecutive timestamps in data.

Members
MaxTimestampGapInDays
Type: int

Indicates the size of the largest timestamp gap, in days.

NumberOfLargeTimestampGaps
Type: int

Indicates the number of large timestamp gaps, if there are any.

Status
Required: Yes
Type: string

Indicates whether there is a potential data issue related to large gaps in timestamps.

MissingCompleteSensorData

Description

Entity that comprises information on sensors that have sensor data completely missing.

Members
AffectedSensorCount
Required: Yes
Type: int

Indicates the number of sensors that have data missing completely.

MissingSensorData

Description

Entity that comprises aggregated information on sensors having missing data.

Members
AffectedSensorCount
Required: Yes
Type: int

Indicates the number of sensors that have atleast some data missing.

TotalNumberOfMissingValues
Required: Yes
Type: int

Indicates the total number of missing values across all the sensors.

ModelDiagnosticsOutputConfiguration

Description

Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.

Members
KmsKeyId
Type: string

The Amazon Web Services Key Management Service (KMS) key identifier to encrypt the pointwise model diagnostics files.

S3OutputConfiguration
Required: Yes
Type: ModelDiagnosticsS3OutputConfiguration structure

The Amazon S3 location for the pointwise model diagnostics.

ModelDiagnosticsS3OutputConfiguration

Description

The Amazon S3 location for the pointwise model diagnostics for an Amazon Lookout for Equipment model.

Members
Bucket
Required: Yes
Type: string

The name of the Amazon S3 bucket where the pointwise model diagnostics are located. You must be the owner of the Amazon S3 bucket.

Prefix
Type: string

The Amazon S3 prefix for the location of the pointwise model diagnostics. The prefix specifies the folder and evaluation result file name. (bucket).

When you call CreateModel or UpdateModel, specify the path within the bucket that you want Lookout for Equipment to save the model to. During training, Lookout for Equipment creates the model evaluation model as a compressed JSON file with the name model_diagnostics_results.json.gz.

When you call DescribeModel or DescribeModelVersion, prefix contains the file path and filename of the model evaluation file.

ModelSummary

Description

Provides information about the specified machine learning model, including dataset and model names and ARNs, as well as status.

Members
ActiveModelVersion
Type: long (int|float)

The model version that the inference scheduler uses to run an inference execution.

ActiveModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution.

CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time at which the specific model was created.

DatasetArn
Type: string

The Amazon Resource Name (ARN) of the dataset used to create the model.

DatasetName
Type: string

The name of the dataset being used for the machine learning model.

LatestScheduledRetrainingModelVersion
Type: long (int|float)

Indicates the most recent model version that was generated by retraining.

LatestScheduledRetrainingStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the start time of the most recent scheduled retraining run.

LatestScheduledRetrainingStatus
Type: string

Indicates the status of the most recent scheduled retraining run.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the machine learning model.

ModelDiagnosticsOutputConfiguration

Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.

ModelName
Type: string

The name of the machine learning model.

ModelQuality
Type: string

Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

For information about using labels with your models, see Understanding labeling.

For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

NextScheduledRetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.

RetrainingSchedulerStatus
Type: string

Indicates the status of the retraining scheduler.

Status
Type: string

Indicates the status of the machine learning model.

ModelVersionSummary

Description

Contains information about the specific model version.

Members
CreatedAt
Type: timestamp (string|DateTime or anything parsable by strtotime)

The time when this model version was created.

ModelArn
Type: string

The Amazon Resource Name (ARN) of the model that this model version is a version of.

ModelName
Type: string

The name of the model that this model version is a version of.

ModelQuality
Type: string

Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

If the model is unlabeled, the model quality can't be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

ModelVersion
Type: long (int|float)

The version of the model.

ModelVersionArn
Type: string

The Amazon Resource Name (ARN) of the model version.

SourceType
Type: string

Indicates how this model version was generated.

Status
Type: string

The current status of the model version.

MonotonicValues

Description

Entity that comprises information on monotonic values in the data.

Members
Monotonicity
Type: string

Indicates the monotonicity of values. Can be INCREASING, DECREASING, or STATIC.

Status
Required: Yes
Type: string

Indicates whether there is a potential data issue related to having monotonic values.

MultipleOperatingModes

Description

Entity that comprises information on operating modes in data.

Members
Status
Required: Yes
Type: string

Indicates whether there is a potential data issue related to having multiple operating modes.

ResourceNotFoundException

Description

The resource requested could not be found. Verify the resource ID and retry your request.

Members
Message
Required: Yes
Type: string

RetrainingSchedulerSummary

Description

Provides information about the specified retraining scheduler, including model name, status, start date, frequency, and lookback window.

Members
LookbackWindow
Type: string

The number of past days of data used for retraining.

ModelArn
Type: string

The ARN of the model that the retraining scheduler is attached to.

ModelName
Type: string

The name of the model that the retraining scheduler is attached to.

RetrainingFrequency
Type: string

The frequency at which the model retraining is set. This follows the ISO 8601 guidelines.

RetrainingStartDate
Type: timestamp (string|DateTime or anything parsable by strtotime)

The start date for the retraining scheduler. Lookout for Equipment truncates the time you provide to the nearest UTC day.

Status
Type: string

The status of the retraining scheduler.

S3Object

Description

Contains information about an S3 bucket.

Members
Bucket
Required: Yes
Type: string

The name of the specific S3 bucket.

Key
Required: Yes
Type: string

The Amazon Web Services Key Management Service (KMS key) key being used to encrypt the S3 object. Without this key, data in the bucket is not accessible.

SensorStatisticsSummary

Description

Summary of ingestion statistics like whether data exists, number of missing values, number of invalid values and so on related to the particular sensor.

Members
CategoricalValues
Type: CategoricalValues structure

Parameter that describes potential risk about whether data associated with the sensor is categorical.

ComponentName
Type: string

Name of the component to which the particular sensor belongs for which the statistics belong to.

DataEndTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference to indicate the end of valid data associated with the sensor that the statistics belong to.

DataExists
Type: boolean

Parameter that indicates whether data exists for the sensor that the statistics belong to.

DataStartTime
Type: timestamp (string|DateTime or anything parsable by strtotime)

Indicates the time reference to indicate the beginning of valid data associated with the sensor that the statistics belong to.

DuplicateTimestamps
Type: CountPercent structure

Parameter that describes the total number of duplicate timestamp records associated with the sensor that the statistics belong to.

InvalidDateEntries
Type: CountPercent structure

Parameter that describes the total number of invalid date entries associated with the sensor that the statistics belong to.

InvalidValues
Type: CountPercent structure

Parameter that describes the total number of, and percentage of, values that are invalid for the sensor that the statistics belong to.

LargeTimestampGaps
Type: LargeTimestampGaps structure

Parameter that describes potential risk about whether data associated with the sensor contains one or more large gaps between consecutive timestamps.

MissingValues
Type: CountPercent structure

Parameter that describes the total number of, and percentage of, values that are missing for the sensor that the statistics belong to.

MonotonicValues
Type: MonotonicValues structure

Parameter that describes potential risk about whether data associated with the sensor is mostly monotonic.

MultipleOperatingModes
Type: MultipleOperatingModes structure

Parameter that describes potential risk about whether data associated with the sensor has more than one operating mode.

SensorName
Type: string

Name of the sensor that the statistics belong to.

SensorsWithShortDateRange

Description

Entity that comprises information on sensors that have shorter date range.

Members
AffectedSensorCount
Required: Yes
Type: int

Indicates the number of sensors that have less than 14 days of data.

ServiceQuotaExceededException

Description

Resource limitations have been exceeded.

Members
Message
Required: Yes
Type: string

Tag

Description

A tag is a key-value pair that can be added to a resource as metadata.

Members
Key
Required: Yes
Type: string

The key for the specified tag.

Value
Required: Yes
Type: string

The value for the specified tag.

ThrottlingException

Description

The request was denied due to request throttling.

Members
Message
Required: Yes
Type: string

UnsupportedTimestamps

Description

Entity that comprises information abount unsupported timestamps in the dataset.

Members
TotalNumberOfUnsupportedTimestamps
Required: Yes
Type: int

Indicates the total number of unsupported timestamps across the ingested data.

ValidationException

Description

The input fails to satisfy constraints specified by Amazon Lookout for Equipment or a related Amazon Web Services service that's being utilized.

Members
Message
Required: Yes
Type: string