[GitHub] [spark] HyukjinKwon commented on a change in pull request #29835: [SPARK-32306][SQL][DOCS] Clarify the result of `percentile_approx()`

[GitBox <gi...@apache.org>]

HyukjinKwon commented on a change in pull request #29835:
URL: https://github.com/apache/spark/pull/29835#discussion_r492613049



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File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/aggregate/ApproximatePercentile.scala
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@@ -49,11 +49,13 @@ import org.apache.spark.sql.types._
  */
 @ExpressionDescription(
   usage = """
-    _FUNC_(col, percentage [, accuracy]) - Returns the approximate percentile value of numeric
-      column `col` at the given percentage. The value of percentage must be between 0.0
-      and 1.0. The `accuracy` parameter (default: 10000) is a positive numeric literal which
-      controls approximation accuracy at the cost of memory. Higher value of `accuracy` yields
-      better accuracy, `1.0/accuracy` is the relative error of the approximation.
+    _FUNC_(col, percentage [, accuracy]) - Returns the approximate `percentile` of the numeric
+      column `col` which is the smallest value in the ordered `col` values (sorted from least to
+      greatest) such that no more than `percentage` of `col` values is less than the value
+      or equal to that value. The value of percentage must be between 0.0 and 1.0. The `accuracy`
+      parameter (default: 10000) is a positive numeric literal which controls approximation accuracy
+      at the cost of memory. Higher value of `accuracy` yields better accuracy, `1.0/accuracy` is
+      the relative error of the approximation.

Review comment:
       Shall we update Scala, Python and R functions too?




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