27 lines
1 KiB
Text
27 lines
1 KiB
Text
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# Keep the aggregate quantiles of each metric passing through.
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[[aggregators.quantile]]
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## General Aggregator Arguments:
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## The period on which to flush & clear the aggregator.
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# period = "30s"
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## If true, the original metric will be dropped by the
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## aggregator and will not get sent to the output plugins.
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# drop_original = false
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## Quantiles to output in the range [0,1]
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# quantiles = [0.25, 0.5, 0.75]
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## Type of aggregation algorithm
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## Supported are:
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## "t-digest" -- approximation using centroids, can cope with large number of samples
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## "exact R7" -- exact computation also used by Excel or NumPy (Hyndman & Fan 1996 R7)
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## "exact R8" -- exact computation (Hyndman & Fan 1996 R8)
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## NOTE: Do not use "exact" algorithms with large number of samples
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## to not impair performance or memory consumption!
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# algorithm = "t-digest"
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## Compression for approximation (t-digest). The value needs to be
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## greater or equal to 1.0. Smaller values will result in more
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## performance but less accuracy.
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# compression = 100.0
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