startree-percentage-rule-query-dx

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The aggregation function to apply on the aggregationColumn. Example: AVG.

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The dataset to query.

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Timezone used to group by time. In TZ-identifier(opens in a new tab) format.

For instance, UTC or US/Pacific.

UTC

AUTO

Required if timeColumn is not AUTO. Learn more(opens in a new tab)

The time for your data to be considered complete and ready for anomaly detection. In ISO-8601 format. Example: PT2H. Learn more(opens in a new tab)

P0D

100000001

Offset in ISO-8601 format. Example: P7D means “use the value of the last week as a baseline”.

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Percentage threshold. If the percentage change is above this threshold, detect an anomaly.

In ratio. Eg 0.1 means 10 percent. Learn more(opens in a new tab).

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Whether to detect an anomaly if it’s a drop, a spike or any of the two.

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"].

[]

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]

[]

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]}

{}

Used to ignore anomalies that don’t meet the thresholdFilter min and max. Example: set thresholdFilterMin = 10 to ignore anomalies when the metric is smaller than 10. Can help ignore anomalies happening in low data regimes. Filter threshold minimum. If -1, no minimum threshold is applied.

-1

Used to ignore anomalies that don’t meet the thresholdFilter min and max. Example: set thresholdFilterMin = 10 to ignore anomalies when the metric is smaller than 10. Can help ignore anomalies happening in low data regimes. Filter threshold maximum. If -1, no maximum threshold is applied.

-1

Used to ignore anomalies that happen during events. Sql filter to apply on the events. Learn more

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

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’]

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

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

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

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

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.

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.

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(opens in a new tab).

[]

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.

[]

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(opens in a new tab).

[]

A Sql filter for RCA events. Only events that match the filter will be shown in the RCA related events tab. Learn more(opens in a new tab).

This is a SQL query that will run on the data source and build enumeration items from that queryExample: “SELECT DISTINCT country, device from pageviews LIMIT 100”. In this case, the enumerator will generate one enumeration item for each country/device combination.

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List of keys to use to identify the enumeration.

The format is the following:

[

“queryFilters”

]

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’]