Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/16971#discussion_r103843868
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/DataFrameStatFunctions.scala ---
@@ -89,22 +88,17 @@ final class DataFrameStatFunctions private[sql](df:
DataFrame) {
* Note that values greater than 1 are accepted but give the same
result as 1.
* @return the approximate quantiles at the given probabilities of each
column
*
- * @note Rows containing any null or NaN values will be removed before
calculation. If
- * the dataframe is empty or all rows contain null or NaN, null is
returned.
+ * @note null and NaN values will be ignored in numerical columns before
calculation. For
+ * columns only containing null or NaN values, an empty array is
returned.
*
* @since 2.2.0
*/
def approxQuantile(
cols: Array[String],
probabilities: Array[Double],
relativeError: Double): Array[Array[Double]] = {
- // TODO: Update NaN/null handling to keep consistent with the
single-column version
- try {
- StatFunctions.multipleApproxQuantiles(df.select(cols.map(col):
_*).na.drop(), cols,
- probabilities, relativeError).map(_.toArray).toArray
- } catch {
- case e: NoSuchElementException => null
- }
+ StatFunctions.multipleApproxQuantiles(df.select(cols.map(col): _*),
cols,
+ probabilities, relativeError).map(_.toArray).toArray
--- End diff --
Nit: style issue
```
StatFunctions.multipleApproxQuantiles(
df.select(cols.map(col): _*),
cols,
probabilities,
relativeError).map(_.toArray).toArray
```
---
If your project is set up for it, you can reply to this email and have your
reply appear on GitHub as well. If your project does not have this feature
enabled and wishes so, or if the feature is enabled but not working, please
contact infrastructure at [email protected] or file a JIRA ticket
with INFRA.
---
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
