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Create Inference Scheduler

lookoutequipment_create_inference_scheduler R Documentation

Creates a scheduled inference

Description

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.

Usage

lookoutequipment_create_inference_scheduler(ModelName,
  InferenceSchedulerName, DataDelayOffsetInMinutes, DataUploadFrequency,
  DataInputConfiguration, DataOutputConfiguration, RoleArn,
  ServerSideKmsKeyId, ClientToken, Tags)

Arguments

ModelName

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

InferenceSchedulerName

[required] The name of the inference scheduler being created.

DataDelayOffsetInMinutes

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.

DataUploadFrequency

[required] 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.

DataInputConfiguration

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

DataOutputConfiguration

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

RoleArn

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

ServerSideKmsKeyId

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

ClientToken

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

Tags

Any tags associated with the inference scheduler.

Value

A list with the following syntax: 

list(
  InferenceSchedulerArn = "string",
  InferenceSchedulerName = "string",
  Status = "PENDING"|"RUNNING"|"STOPPING"|"STOPPED",
  ModelQuality = "QUALITY_THRESHOLD_MET"|"CANNOT_DETERMINE_QUALITY"|"POOR_QUALITY_DETECTED"
)

Request syntax

svc$create_inference_scheduler(
  ModelName = "string",
  InferenceSchedulerName = "string",
  DataDelayOffsetInMinutes = 123,
  DataUploadFrequency = "PT5M"|"PT10M"|"PT15M"|"PT30M"|"PT1H",
  DataInputConfiguration = list(
    S3InputConfiguration = list(
      Bucket = "string",
      Prefix = "string"
    ),
    InputTimeZoneOffset = "string",
    InferenceInputNameConfiguration = list(
      TimestampFormat = "string",
      ComponentTimestampDelimiter = "string"
    )
  ),
  DataOutputConfiguration = list(
    S3OutputConfiguration = list(
      Bucket = "string",
      Prefix = "string"
    ),
    KmsKeyId = "string"
  ),
  RoleArn = "string",
  ServerSideKmsKeyId = "string",
  ClientToken = "string",
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)