Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3550#discussion_r107024971
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala
---
@@ -317,4 +317,92 @@ class SqlITCase extends StreamingWithStateTestBase {
result.addSink(new StreamITCase.StringSink)
env.execute()
}
+
+
+ @Test
+ def testAvgSumAggregatationPartition(): Unit = {
+
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ env.setParallelism(1)
+ StreamITCase.testResults = mutable.MutableList()
+
+ val sqlQuery = "SELECT a, AVG(c) OVER (PARTITION BY a ORDER BY
procTime()" +
+ "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) AS
avgC," +
+ "SUM(c) OVER (PARTITION BY a ORDER BY procTime()" +
+ "RANGE BETWEEN INTERVAL '10' SECOND PRECEDING AND CURRENT ROW) as
sumC FROM MyTable"
+
+ val t = StreamTestData.get5TupleDataStream(env)
+ .assignTimestampsAndWatermarks(new ProcTimeTimestamp())
+ .toTable(tEnv).as('a, 'b, 'c, 'd, 'e)
+
+ tEnv.registerTable("MyTable", t)
+
+ val result = tEnv.sql(sqlQuery).toDataStream[Row]
+ result.addSink(new StreamITCase.StringSink)
+ env.execute()
+
+ val expected = mutable.MutableList(
--- End diff --
Processing time is hard to validate. This test does check the feature
correctly. We should have a look at the processing time tests in the DataStream
API and check if there are some tools or best practices that we can use.
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