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https://issues.apache.org/jira/browse/FLINK-5803?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15888643#comment-15888643
]
ASF GitHub Bot commented on FLINK-5803:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/3397#discussion_r103512951
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala
---
@@ -171,4 +183,82 @@ class SqlITCase extends
StreamingMultipleProgramsTestBase {
val expected = mutable.MutableList("Hello", "Hello world")
assertEquals(expected.sorted, StreamITCase.testResults.sorted)
}
+
+ @Test
+ def testUnboundPartitionedProcessingWindowWithRange(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ StreamITCase.testResults = mutable.MutableList()
+
+ // for sum aggregation ensure that every time the order of each
element is consistent
+ env.setParallelism(1)
+
+ val t1 = env.fromCollection(data).toTable(tEnv).as('a, 'b, 'c)
+
+ tEnv.registerTable("T1", t1)
+
+ val sqlQuery = "SELECT ProcTime()," +
+ "c, " +
+ "count(a) OVER (PARTITION BY c ORDER BY ProcTime() RANGE UNBOUNDED
preceding) as cnt1, " +
+ "sum(a) OVER (PARTITION BY c ORDER BY ProcTime() RANGE UNBOUNDED
preceding) as cnt2 " +
+ "from T1"
+
+ val result = tEnv.sql(sqlQuery).toDataStream[Row]
+ result.addSink(new StreamITCase.StringSink)
+ env.execute()
+
+ val expected = mutable.MutableList(
+ "Hello World,1,7", "Hello World,2,15", "Hello World,3,35",
+ "Hello,1,1", "Hello,2,3", "Hello,3,6", "Hello,4,10", "Hello,5,15",
"Hello,6,21")
+ assertEquals(expected.sorted, StreamITCase.testResults.sorted)
+ }
+
+ @Test
+ def testUnboundPartitionedProcessingWindowWithRow(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ StreamITCase.testResults = mutable.MutableList()
+
+ val t1 = env.fromCollection(data).toTable(tEnv).as('a, 'b, 'c)
+
+ tEnv.registerTable("T1", t1)
+
+ val sqlQuery = "SELECT " +
--- End diff --
This query should not work because `ORDER BY` is missing which is required
for RANGE and ROWS because the result is not completely defined otherwise.
> Add [partitioned] processing time OVER RANGE BETWEEN UNBOUNDED PRECEDING
> aggregation to SQL
> -------------------------------------------------------------------------------------------
>
> Key: FLINK-5803
> URL: https://issues.apache.org/jira/browse/FLINK-5803
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> The goal of this issue is to add support for OVER RANGE aggregations on
> processing time streams to the SQL interface.
> Queries similar to the following should be supported:
> {code}
> SELECT
> a,
> SUM(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY procTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS minB
> FROM myStream
> {code}
> The following restrictions should initially apply:
> - All OVER clauses in the same SELECT clause must be exactly the same.
> - The ORDER BY clause may only have procTime() as parameter. procTime() is a
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5654)
> - FOLLOWING is not supported.
> The restrictions will be resolved in follow up issues. If we find that some
> of the restrictions are trivial to address, we can add the functionality in
> this issue as well.
> This issue includes:
> - Design of the DataStream operator to compute OVER ROW aggregates
> - Translation from Calcite's RelNode representation (LogicalProject with
> RexOver expression).
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