Method: projects.datasets.evaluateSlice

Evaluate an explicit slice from a loaded DataSet.

HTTP request

POST https://{endpoint}/v1/{dataset=projects/*/datasets/*}:evaluateSlice

Where {endpoint} is one of the supported service endpoints.

The URLs use gRPC Transcoding syntax.

Path parameters

Parameters
dataset

string

Required. Loaded DataSet to be queried in the format of "projects/{project}/datasets/{dataset}"

Request body

The request body contains data with the following structure:

JSON representation 
{
  "pinnedDimensions": [
    {
      object (PinnedDimension)
    }
  ],
  "detectionTime": string,
  "timeseriesParams": {
    object (TimeseriesParams)
  },
  "forecastParams": {
    object (ForecastParams)
  }
}
Fields
pinnedDimensions[]

object (PinnedDimension)

Required. Dimensions with pinned values that specify the slice for which we will fetch the time series.
detectionTime

string (Timestamp format)

Required. This is the point in time which we want to probe for anomalies.

See documentation for [QueryDataSetRequest.detectionPoint][QueryDataSetRequest.detection_point].

A timestamp in RFC3339 UTC "Zulu" format, with nanosecond resolution and up to nine fractional digits. Examples: "2014-10-02T15:01:23Z" and "2014-10-02T15:01:23.045123456Z".
timeseriesParams

object (TimeseriesParams)

Parameters controlling how we will build the time series used to predict the detectionTime value for this slice.
forecastParams

object (ForecastParams)

Parameters that control the time series forecasting models, such as the sensitivity of the anomaly detection.

Response body

If successful, the response body contains an instance of ForecastResult.

Authorization Scopes

Requires the following OAuth scope:

  • https://www.googleapis.com/auth/cloud-platform

For more information, see the Authentication Overview.