TypeResample🔗
Constructor🔗
Methods🔗
build🔗
Builds the object.
datasource🔗
The datasource
downsampler🔗
The downsample function
Possible enum values:
"sum"
"mean"
"min"
"max"
"count"
"last"
"median"
def downsampler(downsampler: typing.Literal["sum", "mean", "min", "max", "count", "last", "median"]) -> typing.Self
expression🔗
The math expression
hide🔗
true if query is disabled (ie should not be returned to the dashboard)
NOTE: this does not always imply that the query should not be executed since
the results from a hidden query may be used as the input to other queries (SSE etc)
interval_ms🔗
Interval is the suggested duration between time points in a time series query.
NOTE: the values for intervalMs is not saved in the query model. It is typically calculated
from the interval required to fill a pixels in the visualization
max_data_points🔗
MaxDataPoints is the maximum number of data points that should be returned from a time series query.
NOTE: the values for maxDataPoints is not saved in the query model. It is typically calculated
from the number of pixels visible in a visualization
query_type🔗
QueryType is an optional identifier for the type of query.
It can be used to distinguish different types of queries.
ref_id🔗
RefID is the unique identifier of the query, set by the frontend call.
result_assertions🔗
Optionally define expected query result behavior
def result_assertions(result_assertions: cogbuilder.Builder[expr.ExprTypeResampleResultAssertions]) -> typing.Self
time_range🔗
TimeRange represents the query range
NOTE: unlike generic /ds/query, we can now send explicit time values in each query
NOTE: the values for timeRange are not saved in a dashboard, they are constructed on the fly
upsampler🔗
The upsample function
Possible enum values:
"pad"
Use the last seen value"backfilling"
backfill"fillna"
Do not fill values (nill)
window🔗
The time duration