This module provides Apache Druid aggregators based on numeric quantiles DoublesSketch from [Apache DataSketches](https://datasketches.apache.org/) library. Quantiles sketch is a mergeable streaming algorithm to estimate the distribution of values, and approximately answer queries about the rank of a value, probability mass function of the distribution (PMF) or histogram, cumulative distribution function (CDF), and quantiles (median, min, max, 95th percentile and such). See [Quantiles Sketch Overview](https://datasketches.apache.org/docs/Quantiles/QuantilesOverview).
|k|Parameter that determines the accuracy and size of the sketch. Higher k means higher accuracy but more space to store sketches. Must be a power of 2 from 2 to 32768. See [accuracy information](https://datasketches.apache.org/docs/Quantiles/OrigQuantilesSketch) in the DataSketches documentation for details.|no, defaults to 128|
|maxStreamLength|This parameter is a temporary solution to avoid a [known issue](https://github.com/apache/druid/issues/11544). It may be removed in a future release after the bug is fixed. This parameter defines the maximum number of items to store in each sketch. If a sketch reaches the limit, the query can throw `IllegalStateException`. To workaround this issue, increase the maximum stream length. See [accuracy information](https://datasketches.apache.org/docs/Quantiles/OrigQuantilesSketch) in the DataSketches documentation for how many bytes are required per stream length.|no, defaults to 1000000000|
This returns an approximation to the histogram given an array of split points that define the histogram bins or a number of bins (not both). An array of <i>m</i> unique, monotonically increasing split points divide the real number line into <i>m+1</i> consecutive disjoint intervals. The definition of an interval is inclusive of the left split point and exclusive of the right split point. If the number of bins is specified instead of split points, the interval between the minimum and maximum values is divided into the given number of equally-spaced bins.
This returns an approximation to the Cumulative Distribution Function given an array of split points that define the edges of the bins. An array of <i>m</i> unique, monotonically increasing split points divide the real number line into <i>m+1</i> consecutive disjoint intervals. The definition of an interval is inclusive of the left split point and exclusive of the right split point. The resulting array of fractions can be viewed as ranks of each split point with one additional rank that is always 1.
