lookoutmetrics_create_metric_set: Creates a dataset
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

View source: R/lookoutmetrics_operations.R

lookoutmetrics_create_metric_set

R Documentation

Creates a dataset

Description

Creates a dataset.

See https://www.paws-r-sdk.com/docs/lookoutmetrics_create_metric_set/ for full documentation.

Usage

lookoutmetrics_create_metric_set(
  AnomalyDetectorArn,
  MetricSetName,
  MetricSetDescription = NULL,
  MetricList,
  Offset = NULL,
  TimestampColumn = NULL,
  DimensionList = NULL,
  MetricSetFrequency = NULL,
  MetricSource,
  Timezone = NULL,
  Tags = NULL,
  DimensionFilterList = NULL
)

Arguments

`AnomalyDetectorArn`	[required] The ARN of the anomaly detector that will use the dataset.
`MetricSetName`	[required] The name of the dataset.
`MetricSetDescription`	A description of the dataset you are creating.
`MetricList`	[required] A list of metrics that the dataset will contain.
`Offset`	After an interval ends, the amount of seconds that the detector waits before importing data. Offset is only supported for S3, Redshift, Athena and datasources.
`TimestampColumn`	Contains information about the column used for tracking time in your source data.
`DimensionList`	A list of the fields you want to treat as dimensions.
`MetricSetFrequency`	The frequency with which the source data will be analyzed for anomalies.
`MetricSource`	[required] Contains information about how the source data should be interpreted.
`Timezone`	The time zone in which your source data was recorded.
`Tags`	A list of tags to apply to the dataset.
`DimensionFilterList`	A list of filters that specify which data is kept for anomaly detection.