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https://issues.apache.org/jira/browse/FLINK-6649?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16072697#comment-16072697
]
ASF GitHub Bot commented on FLINK-6649:
---------------------------------------
Github user fhueske commented on a diff in the pull request:
https://github.com/apache/flink/pull/4157#discussion_r125322758
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/runtime/harness/NonWindowHarnessTest.scala
---
@@ -80,18 +80,79 @@ class NonWindowHarnessTest extends HarnessTestBase {
val expectedOutput = new ConcurrentLinkedQueue[Object]()
- expectedOutput.add(new StreamRecord(CRow(Row.of(1L: JLong, 1: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(2L: JLong, 1: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(3L: JLong, 3: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(4L: JLong, 6: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(5L: JLong, 10: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(6L: JLong, 3: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(7L: JLong, 5: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(8L: JLong, 11: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(9L: JLong, 18: JInt),
true), 1))
- expectedOutput.add(new StreamRecord(CRow(Row.of(10L: JLong, 3: JInt),
true), 1))
-
- verify(expectedOutput, result, new RowResultSortComparator(6))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(1L: JLong, "aaa", 1:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(2L: JLong, "bbb", 1:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(3L: JLong, "aaa", 3:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(4L: JLong, "aaa", 6:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(5L: JLong, "aaa", 10:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(6L: JLong, "bbb", 3:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(7L: JLong, "aaa", 5:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(8L: JLong, "aaa", 11:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(9L: JLong, "aaa", 18:
JInt), true), 1))
+ expectedOutput.add(new StreamRecord(CRow(Row.of(10L: JLong, "bbb", 3:
JInt), true), 1))
+
+ verifySorted(expectedOutput, result, new RowResultSortComparator)
+
+ testHarness.close()
+ }
+
+ @Test
+ def testProcTimeNonWindowWithUpdateInterval(): Unit = {
+
+ val processFunction = new KeyedProcessOperator[String, CRow, CRow](
+ new GroupAggProcessFunctionWithUpdateInterval(
+ genSumAggFunction,
+ sumAggregationStateType,
+ sumAggregationRowType,
+ false,
+ queryConfig
+ .withIdleStateRetentionTime(Time.seconds(4), Time.seconds(5))
+ .withUnboundedAggregateUpdateInterval(Time.seconds(1))))
+
+ val testHarness =
+ createHarnessTester(
+ processFunction,
+ new TupleRowKeySelector[String](2),
+ BasicTypeInfo.STRING_TYPE_INFO)
+
+ testHarness.open()
+
+ testHarness.setProcessingTime(1)
+
+ testHarness.processElement(new StreamRecord(CRow(Row.of(1L: JLong, 1:
JInt, "aaa"), true), 1))
+ testHarness.processElement(new StreamRecord(CRow(Row.of(2L: JLong, 1:
JInt, "bbb"), true), 1))
+ testHarness.setProcessingTime(1000)
+ testHarness.processElement(new StreamRecord(CRow(Row.of(3L: JLong, 2:
JInt, "aaa"), true), 1))
+ testHarness.processElement(new StreamRecord(CRow(Row.of(4L: JLong, 3:
JInt, "aaa"), true), 1))
+
+ testHarness.setProcessingTime(1002)
+ testHarness.processElement(new StreamRecord(CRow(Row.of(5L: JLong, 4:
JInt, "aaa"), true), 1))
+ testHarness.processElement(new StreamRecord(CRow(Row.of(6L: JLong, 2:
JInt, "bbb"), true), 1))
+
+ testHarness.setProcessingTime(4003)
+ testHarness.processElement(new StreamRecord(CRow(Row.of(7L: JLong, 5:
JInt, "aaa"), true), 1))
+ testHarness.processElement(new StreamRecord(CRow(Row.of(8L: JLong, 6:
JInt, "aaa"), true), 1))
+
+ // clear all states
+ testHarness.setProcessingTime(10003)
+ testHarness.processElement(new StreamRecord(CRow(Row.of(9L: JLong, 7:
JInt, "aaa"), true), 1))
+ testHarness.processElement(new StreamRecord(CRow(Row.of(10L: JLong, 3:
JInt, "bbb"), true), 1))
+
+ testHarness.setProcessingTime(12003)
+
+ val result = testHarness.getOutput
+
+ val expectedOutput = new ConcurrentLinkedQueue[Object]()
+
+ expectedOutput.add(new StreamRecord(CRow(Row.of(1L: JLong, "aaa", 6:
JInt), true), 1001))
--- End diff --
The `ProcessingFunction` sets the timestamp of the processing time timer as
event-time to all records emitted in `onTimer()`. IMO, this is pretty bad
behavior because processing time and event time (and existing watermarks) are
not related at all. I think the best behavior would be to assign the timestamp
of the last updating record. However, this would again require to hold back
watermarks which is not trivial (and can only be done with a custom operator).
For now, I would propose to set the current watermark as timestamp such
that records are not considered as late data.
> Improve Non-window group aggregate with configurable `earlyFire`.
> -----------------------------------------------------------------
>
> Key: FLINK-6649
> URL: https://issues.apache.org/jira/browse/FLINK-6649
> Project: Flink
> Issue Type: Sub-task
> Components: Table API & SQL
> Affects Versions: 1.4.0
> Reporter: sunjincheng
> Assignee: sunjincheng
>
> Currently, Non-windowed group aggregate is earlyFiring at count(1), that is
> every row will emit a aggregate result. But some times user want config count
> number (`early firing with count[N]`) , to reduce the downstream pressure.
> This JIRA. will enable the config of e`earlyFiring` for Non-windowed group
> aggregate.
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