Prediction - script API
Functions for predicting data available in StackState
This page describes StackState version 4.2.
The StackState 4.2 version range is End of Life (EOL) and no longer supported. We encourage customers still running the 4.2 version range to upgrade to a more recent release.
Function: predictMetrics
predictMetricsPredict metrics for any metric query coming from any data source.
Args:
predictorName- the prediction preset to use:- fft - Fast Fourier Transformation. Used for seasonal metrics with a repeatable pattern that has a cycle.
- linear - used for metrics that have a linear trend.
- hmn - Harmonic Mean Normal. Used in difficult cases when metrics are not clearly seasonal or linear.
query- the metrics to use for the prediction. A telemetry query that returns metrics, created using theTelemetry.query()function followed by.compileQuery().
Builder methods:
predictionPoints(points: Int)- the number of points to the horizon.includeHistory(start?: Instant, end?: Instant)- call this builder method to include the result of thequeryin the return value. Optionally a start and end can be added to limit the included history using the instant format. When not specifying the start and end the whole history will be included.
Return type:
AsyncScriptResult[PredictionResponse]A
PredictionResponse, which contains the following fields:Fields:
PredictionResponse.request- the request made to the prediction API of typePredictionRequest.PredictionResponse.history- optional, the history used for prediction of typeMetricTelemetry. Empty if.includeHistory()was not used.PredictionResponse.prediction- the predicted metrics.
The
PredictionRequest type has the following fields:PredictionRequest.query- the query provided topredictMetrics.PredictionRequest.predictor- the name and configuration of the predictor.PredictionRequest.horizon- the prediction horizon.PredictionRequest.predictionPointCount- the number of predicted points.PredictionRequest.historyResponse- options of the history response.
The
MetricTelemetry has the following fields:MetricTelemetry.result.data- the two dimensional array with values and time stamps.
Examples:
Predict 8 points of disk utilization for
myHost for the next four hours based on the last four weeks of data:1
Prediction.predictMetrics("linear", "4h",
2
Telemetry.query("MyDatasource", 'host="myHost" and name="diskutil"')
3
.metricField("value")
4
.start("-4w")
5
.compileQuery()
6
).includeHistory().predictionPoints(8)
Copied!
Last modified 7mo ago
Copy link
Contents
Function: predictMetrics