HyukjinKwon commented on a change in pull request #31296:
URL: https://github.com/apache/spark/pull/31296#discussion_r564138543
##########
File path: sql/core/src/test/scala/org/apache/spark/sql/DatasetSuite.scala
##########
@@ -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:
@viirya, what do you think about we expose an `transform` equivalent
expression exposed as DSL? e.g.)
```scala
scala> val data = Seq((123, "first"), (4567, "second")).toDF("num", "word")
data: org.apache.spark.sql.DataFrame = [num: int, word: string]
scala> data.createOrReplaceTempView("t1")
scala> sql("select transform(*) using 'cat' from t1").show()
+----+------+
| key| value|
+----+------+
| 123| first|
|4567|second|
+----+------+
```
```scala
scala> data.repartition(1).createOrReplaceTempView("t1")
scala> sql("select transform(*) using 'wc -l' as (echo) from t1").show()
+--------+
| echo|
+--------+
| 2|
+--------+
```
Spark lately added the native support of script transformation, and I think
it could do what you want.
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