[
https://issues.apache.org/jira/browse/FLINK-5658?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15882461#comment-15882461
]
ASF GitHub Bot commented on FLINK-5658:
---------------------------------------
Github user sunjincheng121 commented on a diff in the pull request:
https://github.com/apache/flink/pull/3386#discussion_r102922045
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/stream/sql/SqlITCase.scala
---
@@ -171,4 +175,98 @@ class SqlITCase extends
StreamingMultipleProgramsTestBase {
val expected = mutable.MutableList("Hello", "Hello world")
assertEquals(expected.sorted, StreamITCase.testResults.sorted)
}
+
+ /** test sliding event-time unbounded window with partition by **/
+ @Test
+ def testSlideEventTimeUnboundWindowWithGroup(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
+ StreamITCase.testResults = mutable.MutableList()
+
+ val sqlQuery = "SELECT a, b, SUM(a) over (partition by b order by
rowtime() range between " +
+ "unbounded preceding and current row) from T1"
+
+ val t1 = StreamTestData.getSmall3TupleDataStream(env)
+ .assignTimestampsAndWatermarks(new
AssignerWithPeriodicWatermarks[(Int, Long, String)] {
+
+ def getCurrentWatermark: Watermark = new
Watermark(System.currentTimeMillis)
+
+ def extractTimestamp(element: (Int, Long, String),
previousElementTimestamp: Long): Long =
+ 1400000
+ }).toTable(tEnv).as('a, 'b, 'c)
+ tEnv.registerTable("T1", t1)
+
+ val result = tEnv.sql(sqlQuery).toDataStream[Row]
+ result.addSink(new StreamITCase.StringSink)
+ env.execute()
+
+ val expected1 = mutable.MutableList(
+ "1,1,1", "2,2,2", "3,2,5")
+ val expected2 = mutable.MutableList(
+ "1,1,1", "2,2,5", "3,2,3")
+ assertTrue(expected1.equals(StreamITCase.testResults.sorted) ||
+ expected2.equals(StreamITCase.testResults.sorted))
+ }
+
+ /** test sliding event-time unbounded window without partitiion by **/
+ @Test
+ def testSlideEventTimeUnboundWindowWithoutGroup(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
+ StreamITCase.testResults = mutable.MutableList()
+
+ val sqlQuery = "SELECT SUM(a) " +
+ "over (order by rowtime() range between unbounded preceding and
current row) from T1"
+
+ val t1 = StreamTestData.getSmall3TupleDataStream(env)
+ .assignTimestampsAndWatermarks(new
AssignerWithPeriodicWatermarks[(Int, Long, String)] {
+
+ def getCurrentWatermark: Watermark = new
Watermark(System.currentTimeMillis)
+
+ def extractTimestamp(element: (Int, Long, String),
previousElementTimestamp: Long): Long =
+ 1400000
+ }).toTable(tEnv).as('a, 'b, 'c)
+ tEnv.registerTable("T1", t1)
+
+ val result = tEnv.sql(sqlQuery).toDataStream[Row]
+ result.addSink(new StreamITCase.StringSink)
+ env.execute()
+
+ assertEquals(Some("6"), StreamITCase.testResults.sorted.get(2))
+ }
+
+ /** test sliding event-time unbounded window with later record **/
+ @Test
+ def testSlideEventTimeUnboundWindowWithLater(): Unit = {
+ val env = StreamExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+ env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
+ env.setParallelism(1)
--- End diff --
When you remove this configuration, run many times will get different
results, such as:
I have added a time column for the convenience of observation `SUM(a) -> d,
SUM(a) `:
The first time:
```
1400005,2
1400010,6
```
The second time
```
1400000,1
1400010,5
```
The third time
```
1300000,3
1400005,5
1400010,9
```
Do you have that happen?If so, please check and fix the bug?
> Add event time OVER RANGE BETWEEN UNBOUNDED PRECEDING aggregation to SQL
> ------------------------------------------------------------------------
>
> Key: FLINK-5658
> URL: https://issues.apache.org/jira/browse/FLINK-5658
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Reporter: Fabian Hueske
> Assignee: Yuhong Hong
>
> The goal of this issue is to add support for OVER RANGE aggregations on event
> 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 rowTime() RANGE BETWEEN UNBOUNDED
> PRECEDING AND CURRENT ROW) AS sumB,
> MIN(b) OVER (PARTITION BY c ORDER BY rowTime() 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 PARTITION BY clause is optional (no partitioning results in single
> threaded execution).
> - The ORDER BY clause may only have rowTime() as parameter. rowTime() is a
> parameterless scalar function that just indicates processing time mode.
> - bounded PRECEDING is not supported (see FLINK-5655)
> - 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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