Github user holdenk commented on a diff in the pull request:
https://github.com/apache/spark/pull/9003#discussion_r42697800
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/DataFrameAggregateSuite.scala ---
@@ -221,4 +221,40 @@ class DataFrameAggregateSuite extends QueryTest with
SharedSQLContext {
emptyTableData.agg(sumDistinct('a)),
Row(null))
}
+
+ test("moments") {
+ checkAnswer(
+ testData2.agg(skewness('a)),
+ Row(0.0))
+
+ checkAnswer(
--- End diff --
So there are a few options for how to go about this. In spark-testing-base
(which I'd like to eventually merge some of the functionality of) I made a
modified version of checkAnswer which also takes tolerance and does tolerance
based matching for floating point data (see
https://github.com/holdenk/spark-testing-base/blob/master/src/main/scala/com/holdenkarau/spark/testing/DataFrameSuiteBase.scala
& approxEqualDataFrames + approxEquals for comparing the rows). The other
option would be, since for these tests its just a single value, just collect
the result back, extract the value and do a regular assertion with tolerance.
I think collecting the result and just checking the single value is
probably the best plan for this PR and eventually maybe looking at a more
general version of check answer.
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