Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/13394#discussion_r65410850
--- Diff: R/pkg/R/stats.R ---
@@ -135,13 +136,13 @@ setMethod("freqItems", signature(x =
"SparkDataFrame", cols = "character"),
#' Calculates the approximate quantiles of a numerical column of a
SparkDataFrame.
#'
#' The result of this algorithm has the following deterministic bound:
-#' If the SparkDataFrame 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
SparkDataFrame 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.
+#' If the SparkDataFrame has N elements and if we request the quantile at
probability \strong{p} up
--- End diff --
@vectorijk Are you able to separate them? If you can't find a good way
easily, ping & I can try to figure it out. Thanks!
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