Nice to read if you ever wondered why our Histogram is so different and what is that MixMaxCounter we talk about: http://kamon.io/core/metrics/instruments/ …
@giltene @kamonteam yep. I'm coming from a machine learning context, where being able to eg find that "DC offset" on the fly is more useful.
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@avibryant@kamonteam In this case it's trivial at the start: E.g. take the average of the first 100 results in the stream before feeding. -
@giltene@kamonteam bit trickier in a distributed context; each node will have a slightly different average, then you have to reconcile. -
@avibryant@kamonteam Reconciling isn't hard. Each node can produce their own histogram, and they are additive later. -
@giltene@kamonteam right, but if they each have a different offset it gets harder. -
@giltene@kamonteam this isn't an academic question - I'm thinking in particular about using it in MapReduce, where the nodes have no comm. -
@avibryant@kamonteam What would you consider an acceptable footprint for an "accurate" histogram, BTW? -
@avibryant@kamonteam E.g would 0.5MB be acceptable for 0.01% accuracy across 12 [decimal] orders of magnitude? How about 5MB for 0.001%? -
@giltene@kamonteam those footprints are definitely acceptable. - 3 more replies
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