[GitHub] leerho commented on issue #7160: Error bounds / probabilities / skewness as first-class Druid query results

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leerho commented on issue #7160: Error bounds / probabilities / skewness as first-class Druid query results
URL: https://github.com/apache/incubator-druid/issues/7160#issuecomment-468436251
 
 
   I strongly support the concept that any aggregation that returns approximate results also return a means for the user to establish the likely bounds on the error along with the corresponding confidence interval. 
   
   Please note that all of the sketches in the DataSketches library provide both a-priori and a-posteriori error estimation methods. 
   
   Also, please do not confuse the built-in `Druid Approximate Histogram`  with the DataSketches Quantiles sketch which can also produce an approximate histogram.  The built-in Druid Approximate Histogram is very data sensitive and cannot provide any error guarantees.  It also does not qualify as a "sketch" largely because of these issues, it is a purely empirical algorithm.   Please see this [comparative study](https://datasketches.github.io/docs/Quantiles/DruidApproxHistogramStudy.html).
   
   

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