AngersZhuuuu commented on a change in pull request #31296:
URL: https://github.com/apache/spark/pull/31296#discussion_r564348823
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File path: sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
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@@ -2007,6 +2007,54 @@ class DatasetSuite extends QueryTest
checkAnswer(withUDF, Row(Row(1), null, null) :: Row(Row(1), null, null) ::
Nil)
}
+
+ test("SPARK-34205: Pipe Dataset") {
+ assume(TestUtils.testCommandAvailable("cat"))
+
+ val nums = spark.range(4)
+ val piped = nums.pipe("cat", (l, printFunc) => printFunc(l.toString)).toDF
Review comment:
> Unlike Window function, it seems to me that we cannot have a query
like "SELECT a, TRANSFORM(...), c FROM ..." or in DSL format like:
>
> ```scala
> df.select($"a", $"b", transform(...) ...)
> ```
>
> But for Window function we can do:
>
> ```scala
> df.select($"a", $"b", lead("key", 1).over(window) ...)
> ```
>
> That being said, in the end it is also `Dataset.transform`, instead of an
expression DSL.
I have thought this problem too, first I want to add transform as a DSL
function, in this way, we need to make an equivalent ScriptTransformation
expression first. We can think that this is just a new expression, or a new
function.
Also add a `Dataset.scriptTransform` could be fine since we can support more
flexible usage case and larger scope. Also important, it has a standard to
follow and it‘s consistent with SQL.
We don’t necessarily need to write as
```
df.select($"a", $"b", transform(xx))
```
we can write it as
```
df.scriptTransform(input, script, output...)
```
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