Github user stefanobortoli commented on a diff in the pull request:
https://github.com/apache/flink/pull/3574#discussion_r108626444
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/WindowAggregateTest.scala
---
@@ -350,4 +350,59 @@ class WindowAggregateTest extends TableTestBase {
streamUtil.verifySql(sql, expected)
}
+ @Test
+ def testBoundedNonPartitionedProcessingWindowWithRow() = {
+ val sql = "SELECT " +
+ "c, " +
+ "count(a) OVER (ORDER BY procTime() ROWS BETWEEN 2 preceding AND " +
+ "CURRENT ROW) as cnt1 " +
+ "from MyTable"
+
+ val expected =
+ unaryNode(
+ "DataStreamCalc",
+ unaryNode(
+ "DataStreamOverAggregate",
+ unaryNode(
+ "DataStreamCalc",
+ streamTableNode(0),
+ term("select", "a", "c", "PROCTIME() AS $2")
+ ),
+ term("orderBy", "PROCTIME"),
+ term("rows", "BETWEEN 2 PRECEDING AND CURRENT ROW"),
+ term("select", "a", "c", "PROCTIME", "COUNT(a) AS w0$o0")
+ ),
+ term("select", "c", "w0$o0 AS $1")
+ )
+ streamUtil.verifySql(sql, expected)
+ }
+
+ @Test
+ def testBoundedPartitionedProcessingWindowWithRow() = {
+ val sql = "SELECT " +
+ "c, " +
+ "count(a) OVER (PARTITION BY c ORDER BY procTime() ROWS BETWEEN 2
preceding AND " +
--- End diff --
I have tested 4 situations that Fabian thought to be sufficient for our
purpose. 3 or 4 does not change besides my work to manually assemble the test.
:-) of course unless the aggregations are not reliable and summing 3 numbers or
4 numbers could have an impact. :-D
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