Github user MLnick commented on a diff in the pull request:
https://github.com/apache/spark/pull/12135#discussion_r86504547
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala ---
@@ -73,13 +73,50 @@ final class DataFrameStatFunctions private[sql](df:
DataFrame) {
}
/**
+ * Calculates the approximate quantiles of numerical columns of a
DataFrame.
+ *
+ * The result of this algorithm has the following deterministic bound:
+ * If the DataFrame has N elements and if we request the quantile at
probability `p` up to error
+ * `err`, then the algorithm will return a sample `x` from the DataFrame
so that the *exact* rank
+ * of `x` is close to (p * N).
+ * More precisely,
+ *
+ * floor((p - err) * N) <= rank(x) <= ceil((p + err) * N).
+ *
+ * This method implements a variation of the Greenwald-Khanna algorithm
(with some speed
+ * optimizations).
+ * The algorithm was first present in
[[http://dx.doi.org/10.1145/375663.375670 Space-efficient
+ * Online Computation of Quantile Summaries]] by Greenwald and Khanna.
--- End diff --
I would still prefer not to have this duplicate doc string. We can refer
here to the doc of the single-column method to ensure we reference the details
without repeating them.
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