--- layout: doc_page title: "DataSketches Quantiles Sketch module" --- # DataSketches Quantiles Sketch module This module provides Apache Druid (incubating) aggregators based on numeric quantiles DoublesSketch from [datasketches](https://datasketches.github.io/) 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, cummulative distribution function (CDF), and quantiles (median, min, max, 95th percentile and such). See [Quantiles Sketch Overview](https://datasketches.github.io/docs/Quantiles/QuantilesOverview.html). There are three major modes of operation: 1. Ingesting sketches built outside of Druid (say, with Pig or Hive) 2. Building sketches from raw data during ingestion 3. Building sketches from raw data at query time To use this aggregator, make sure you [include](../../operations/including-extensions.html) the extension in your config file: ``` druid.extensions.loadList=["druid-datasketches"] ``` ### Aggregator The result of the aggregation is a DoublesSketch that is the union of all sketches either built from raw data or read from the segments. ```json { "type" : "quantilesDoublesSketch", "name" : , "fieldName" : , "k": } ``` |property|description|required?| |--------|-----------|---------| |type|This String should always be "quantilesDoublesSketch"|yes| |name|A String for the output (result) name of the calculation.|yes| |fieldName|A String for the name of the input field (can contain sketches or raw numeric values).|yes| |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 the [Quantiles Accuracy](https://datasketches.github.io/docs/Quantiles/QuantilesAccuracy.html) for details. |no, defaults to 128| ### Post Aggregators #### Quantile This returns an approximation to the value that would be preceded by a given fraction of a hypothetical sorted version of the input stream. ```json { "type" : "quantilesDoublesSketchToQuantile", "name": , "field" : , "fraction" : } ``` #### Quantiles This returns an array of quantiles corresponding to a given array of fractions ```json { "type" : "quantilesDoublesSketchToQuantiles", "name": , "field" : , "fractions" : } ``` #### Histogram This returns an approximation to the histogram given an array of split points that define the histogram bins. An array of m unique, monotonically increasing split points divide the real number line into m+1 consecutive disjoint intervals. The definition of an interval is inclusive of the left split point and exclusive of the right split point. ```json { "type" : "quantilesDoublesSketchToHistogram", "name": , "field" : , "splitPoints" : } ``` #### Rank This returns an approximation to the rank of a given value that is the fraction of the distribution less than that value. ```json { "type" : "quantilesDoublesSketchToRank", "name": , "field" : , "value" : } ``` #### CDF 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 m unique, monotonically increasing split points divide the real number line into m+1 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. ```json { "type" : "quantilesDoublesSketchToCDF", "name": , "field" : , "splitPoints" : } ``` #### Sketch Summary This returns a summary of the sketch that can be used for debugging. This is the result of calling toString() method. ```json { "type" : "quantilesDoublesSketchToString", "name": , "field" : } ```