Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/8314#discussion_r44066760
--- Diff: R/pkg/inst/tests/test_sparkSQL.R ---
@@ -1458,8 +1458,8 @@ test_that("sampleBy() on a DataFrame", {
fractions <- list("0" = 0.1, "1" = 0.2)
sample <- sampleBy(df, "key", fractions, 0)
result <- collect(orderBy(count(groupBy(sample, "key")), "key"))
- expect_identical(as.list(result[1, ]), list(key = "0", count = 2))
- expect_identical(as.list(result[2, ]), list(key = "1", count = 10))
+ expect_identical(as.list(result[1, ]), list(key = "0", count = 3))
+ expect_identical(as.list(result[2, ]), list(key = "1", count = 7))
--- End diff --
this one really confused me ... I thought I could figure out what the right
values should be by running the equivalent thing in scala, but I got totally
different answers.
```scala
case class Data(val key: String)
val data = (0 to 99).map{x => Data((x % 3).toString)}
val dataDF = sqlContext.createDataFrame(data)
scala> dataDF.stat.sampleBy("key", Map("0" -> 0.1, "1" -> 0.2),
0).groupBy("key").count().show()
+---+-----+
|key|count|
+---+-----+
| 0| 5|
| 1| 5|
+---+-----+
```
but whatever, these vals work :/
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