startree-drift-discrete-dx - StarTree Docs

Description

Detect an anomaly if the distribution drift metric of a continuous variable is above a maximum threshold. Use the enumerationItems property to configure the different dimensions to explore.

Flowchart

Parameters

DATA

name	description	default value
aggregationColumn	The column to aggregate. Can be a derived metric.	-
dataSource	The Pinot datasource to use.	-
dataset	The dataset to query.	-
monitoringGranularity	The period of aggregation of the timeseries. In ISO-8601 format. Example: `PT1H`.	-
timezone	Timezone used to group by time. In TZ-identifier format. For instance, `UTC` or `US/Pacific`.	UTC
timeColumn	TimeColumn used to group by time. If set to AUTO (the default value), the Pinot primary time column is used.	AUTO
timeColumnFormat	Required if timeColumn is not AUTO. Learn more.
completenessDelay	The time for your data to be considered complete and ready for anomaly detection. In ISO-8601 format. Example: `PT2H`. Learn more.	P0D
queryFilters	Filters to apply when fetching data. Prefix with `AND`. Example: `AND country='US'`	$
queryLimit	Maximum number of timeseries point to fetch.	100000001

DETECTION

name	description	default value
lookback	Historical time period to use to train the model. In ISO-8601 format. Example: `P21D`.	P21D
baselineOffsets	A list of baseline offsets in ISO-8601 format to use when computing the distribution drift. Eg `[P7D, P14D, P21D]` will compute the drift between the current distribution and the distribution 1 week, 2 weeks, and 3 weeks ago. The final score is the median of the drifts.	-
distance	The distribution drift distance to use.	-
max	If the current value is above this threshold, detect an anomaly.	-
min	If the current value is below this threshold, detect an anomaly.	0

FILTER

Time of week

name	description	default value
daysOfWeek	Used to ignore anomalies that happen at specific time periods. A list of days. Anomalies happening on these days are ignored if timeOfWeekIgnore is true. Example: `["MONDAY", "SUNDAY"]`.	[]
hoursOfDay	Used to ignore anomalies that happen at specific time periods. A list of hours. Anomalies happening on these hours are ignored. Example: `[0,1,2,23]`	[]
dayHoursOfWeek	Used to ignore anomalies that happen at specific time periods. A mapping of `{DAY: [hours]}`. Anomalies happening on these timeframes are ignored if timeOfWeekIgnore is true. Example: `{"FRIDAY": [22, 23], "SATURDAY": [0, 1, 2]}`

Guardrail metric

name	description	default value
guardrailMetricMin	Used to ignore anomalies that don’t meet the guardrail threshold. Minimum threshold of the guardrail metric. If `-1`, no minimum threshold is applied.	-1
guardrailMetricMax	Used to ignore anomalies that don’t meet the guardrail threshold. Maximum threshold of guardrailMetric. If `-1`, no maximum threshold is applied.	-1
guardrailMetric	Used to ignore anomalies that don’t meet the guardrail threshold. Metric to use as a threshold guardrail. Example: `COUNT(*)` and set `guardrailMetricMin = 100` to ignore anomalies detected when there is less than 100 observations in the period.	COUNT(*)

Special events

name	description	default value
eventFilterSqlFilter	Used to ignore anomalies that happen during events. Sql filter to apply on the events. Learn more
eventFilterLookaround	Used to ignore anomalies that happen during events. Offset to apply on startTime and endTime to look around the timeframe. In ISO-8601 format. Example: `P1D`.	P2D
eventFilterTypes	Used to ignore anomalies that happen during events. List of event types to fetch by. Example: `["HOLIDAY", "DEPLOYMENT"]`. `[]` fetches all events. Use `["__NO_EVENTS"]` to disable.	[‘__NO_EVENTS’]
eventFilterBeforeEventMargin	Used to ignore anomalies that happen during events. A period in ISO-8601 format that corresponds to a period that is also impacted by the event. Example: if beforeEventMargin is `P1D`, if event happens on `[Dec 24 0:00, Dec 25 0:00[`, the label will be applied to anomalies happening on `[Dec 23 0:00 and Dec 25 0:00[`	P0D
eventFilterAfterEventMargin	Used to ignore anomalies that happen during events. Same as eventFilterBeforeEventMargin at the end of the event.	P0D

POSTPROCESS

Data mutability

name	description	default value
mutabilityPeriod	Use if your data is mutable. ThirdEye will maintain the detection results up to date on the mutable period. For instance, if your last 10 days of data is mutable, set `P10D`. At each cron detection job, the detection results for the last 10 days will be updated.	P0D
reNotifyPercentageThreshold	For detection replay when data is mutable. If the percentage difference between an existing anomaly and a new anomaly on the same time frame is above this threshold, renotify. Combined with `reNotifyAbsoluteThreshold`. Both thresholds must pass to be re-notified. If zero, always renotify. If null or negative, never re-notifies.	-1
reNotifyAbsoluteThreshold	For detection replay when data is mutable. If the absolute difference between an existing anomaly and a new anomaly on the same time frame is above this threshold, renotify. Combined with `reNotifyPercentageThreshold`. Both thresholds must pass to be re-notified. If zero, always renotify. If null or negative, never re-notifies.	-1

Anomaly merger

name	description	default value
mergeMaxGap	Maximum gap between 2 anomalies for anomalies to be merged. In ISO-8601 format. Example: `PT2H`. The default behavior is to merge consecutive anomalies only. To disable anomaly merging entirely, set this value to `P0D`.
mergeMaxDuration	Maximum duration of an anomaly merger. At merge time, if an anomaly merger would get bigger than this limit, the anomalies are not merged. In ISO-8601 format. Example: `P7D`.

RCA

name	description	default value
rcaAggregationFunction	The aggregation function to use for RCA. If the detection metric name is known to ThirdEye, this parameter is optional.
rcaIncludedDimensions	List of the dimensions (columns in the dataset) to use in RCA drill-downs. If not set or empty, all dimensions of the table are used. Learn more.	[]
rcaExcludedDimensions	List of dimensions (columns in the dataset) to ignore in RCA drill-downs. If not set or empty, all dimensions of the table are used. rcaExcludedDimensions and rcaIncludedDimensions cannot be used at the same time.	[]
rcaEventTypes	A list of type to filter on for RCA. Only events that match such types will be shown in the RCA related events tab. Learn more.	[]
rcaEventSqlFilter	A Sql filter for RCA events. Only events that match the filter will be shown in the RCA related events tab. Learn more.

DIMENSION_EXPLORATION

name	description	default value
enumerationItems	Array of enumerations. The detection pipeline will run for each enumeration. The format is the following: `json[<br></br> {<br></br> "name": "US country",<br></br> "description": "slice for US only",<br></br> "params": {<br></br> "queryFilters": " AND country='US'"<br></br> }<br></br> }<br></br>,... # other enumerations<br></br>,]<br></br>` To make a property configurable for each enumeration, ensure it is set to the special value: `[DOLLAR]{myProperty}` - replace [DOLLAR] by the dollar character). In the example above the `queryFilter` property must be set to `[DOLLAR]{queryFilters}`.	-
enumerationItemIdKeys	List of keys to use to identify the enumeration. The format is the following: `json[<br></br> "queryFilters"<br></br>]<br></br>` The keys must be present in the `params` object of each enumeration. The keys will be used to generate the dimension exploration id. The id will be used to identify the enumeration in the detection pipeline.	[‘queryFilters’]

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