dfiter

Documentation

Overview

Package dfiter efficiently creates dataframes used in regression detection.

Index

• Variables
• type DataFrameIterator
  • func NewDataFrameIterator(ctx context.Context, progress progress.Progress, ...) (DataFrameIterator, error)

Variables

var ErrInsufficientData = errors.New("insufficient data")

ErrInsufficientData is returned by the DataFrameIterator if all the queries compeleted successfully, but there wasn't enough data to continue.

Types

type DataFrameIterator

type DataFrameIterator interface {
	Next() bool
	Value(ctx context.Context) (*dataframe.DataFrame, error)
}

DataFrameIterator is an iterator that produces DataFrames.

for it.Next() {
  df, err := it.Value(ctx)
  // Do something with df.
}

func NewDataFrameIterator

func NewDataFrameIterator(
	ctx context.Context,
	progress progress.Progress,
	dfBuilder dataframe.DataFrameBuilder,
	perfGit perfgit.Git,
	regressionStateCallback types.ProgressCallback,
	queryAsString string,
	domain types.Domain,
	alert *alerts.Alert,
	anomalyConfig config.AnomalyConfig,
) (DataFrameIterator, error)

NewDataFrameIterator returns a DataFrameIterator that produces a set of dataframes for the given query, domain, and alert.

If domain.Offset is non-zero then we want the iterator to return a single dataframe of alert.Radius around the specified commit. Otherwise it returns a series of dataframes of size 2*alert.Radius+1 sliced from a single dataframe of size domain.N.