siying commented on code in PR #41578:
URL: https://github.com/apache/spark/pull/41578#discussion_r1230077414
##########
sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamSuite.scala:
##########
@@ -684,6 +685,26 @@ class StreamSuite extends StreamTest {
assert(query.exception.isEmpty)
}
+ test("SPARK-44044: non-time-window") {
+ val inputData = MemoryStream[(Int, Int)]
+ val e = intercept[AnalysisException] {
+ val agg = inputData
+ .toDF()
+ .selectExpr("CAST(_1 AS timestamp) AS col1", "_2 AS col2")
+ .withWatermark("col1", "10 seconds")
+ .withColumn("rn_col", row_number().over(Window
+ .partitionBy("col1")
+ .orderBy(col("col2"))))
+ .select("rn_col", "col1", "col2")
+ .writeStream
+ .format("console")
+ .start()
+ }
+ assert(e.getMessage.contains(
+ "Unsupported window function found in column 'row_number() AS rn_col'"))
Review Comment:
If we add `OVER`, it looks like this:
```
Unsupported window function found in column 'row_number() OVER (PARTITION BY
col1 ORDER BY col2 ASC NULLS FIRST ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT
ROW) as column rn_col'. Structured streaming only supports time-window
aggregation using the `window` function.
```
I don't have a strong opinion on this but I didn't include it because I
personally feel that I'm a little bit overwhelmed by less relevant information.
What's your opinion on this?
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org
For additional commands, e-mail: reviews-h...@spark.apache.org
