[jira] [Commented] (FLINK-26406) Significant differences of Fault Tolerance between English and Chinese version
[ https://issues.apache.org/jira/browse/FLINK-26406?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17501688#comment-17501688 ] tonny commented on FLINK-26406: --- There are four documents as follows: [English document of version 1.11|https://nightlies.apache.org/flink/flink-docs-release-1.11/learn-flink/fault_tolerance.html] [Chinese document of version 1.11|https://nightlies.apache.org/flink/flink-docs-release-1.11/zh/learn-flink/fault_tolerance.html] [English document of version 1.14|https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/learn-flink/fault_tolerance/] [Chinese document of version 1.14|https://nightlies.apache.org/flink/flink-docs-release-1.14/zh/docs/learn-flink/fault_tolerance/] By comparing these documents, it could be found the Chinese document of version 1.14 is as the same as the version 1.11 which should have been translated from English document of version 1.11. Because the changes from version 1.11 to version 1.14, the document should be re-translated from the English version of version 1.14. The Chinese version should be marked as out-of-date before the new one comes. And I'm glad to translate the new one. > Significant differences of Fault Tolerance between English and Chinese version > -- > > Key: FLINK-26406 > URL: https://issues.apache.org/jira/browse/FLINK-26406 > Project: Flink > Issue Type: Bug > Components: chinese-translation, Documentation >Affects Versions: 1.14.3 >Reporter: tonny >Priority: Major > > There are significant differences of Fault Tolerance between English and > Chinese version. And obviously, the Chinese version has been translated from > an old version documents. For example, it lists three available > implementations of state backends, all of which are masked as *Deprecated* in > Flink ver. 1.14. -- This message was sent by Atlassian Jira (v8.20.1#820001)
[GitHub] [flink] gaoyunhaii commented on pull request #18805: [FLINK-26173][streaming] Recover GlobalCommittables with Sink V1 GlobalCommittable serializer
gaoyunhaii commented on pull request #18805: URL: https://github.com/apache/flink/pull/18805#issuecomment-1059720777 Hi Fabian~ thanks for the clarification! For the `filterRecoveredCommittables`, it should be initiated by some data lake systems like iceberg, if there are global committables from more than one checkpoint not committed before failover, then it should be able to merge them into one global committable on restoring, thus the restoring process could be accelerated [1]. For the `combine`, sorry I overlooked the issue and the current implementation, currently it is indeed called before committed. The issue is said that the committables should be combined on `snapshotState`, and the resulted global committables should be persisted, thus if there are failovers and re-commit, the `combine` does need to be executed again. If we want to call `filterRecoveredCommittables` for each snapshot, we might need to add a parameter `isRestored` to the `CommittableManager#commit`. If we want to also keep the same behavior for the `combine` method, we might need to do some more modification to the `CommittableManager` or not reuse the current implementation. However, currently the sink implementation in the `iceberg`, `hudi` and `flink-table-store` are indeed using the customized operators / legacy sink API instead of the sink API v1. In addition, the two issues should mainly affect he performance instead of the correctness. At last, users are still be able to add their own global committer implementation with topology API. Thus I think it is still useful to solve the two issues, but if we do not have capacity we might postpone solving the two issues. If so, perhaps we could create a new jira issue for state compatibility with the sink v1 and attach this PR to that issue, and dowgrade the FLINK-26173 and leaves it open? Since we have not fully fix the issues listed in the FLINK-26173~ [1] https://lists.apache.org/thread/3tqgnhclbr8ptb69b2ro74535dtbd608 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] gaoyunhaii edited a comment on pull request #18805: [FLINK-26173][streaming] Recover GlobalCommittables with Sink V1 GlobalCommittable serializer
gaoyunhaii edited a comment on pull request #18805: URL: https://github.com/apache/flink/pull/18805#issuecomment-1059720777 Hi Fabian~ thanks for the clarification! For the `filterRecoveredCommittables`, it should be initiated by some data lake systems like iceberg, if there are global committables from more than one checkpoint not committed before failover, then it should be able to merge them into one global committable on restoring, thus the restoring process could be accelerated [1]. For the `combine`, sorry I overlooked the issue and the current implementation, currently it is indeed called before committed. The issue is said that the committables should be combined on `snapshotState`, and the resulted global committables should be persisted, thus if there are failovers and re-commit, the `combine` does need to be executed again. If we want to call `filterRecoveredCommittables` for each snapshot, we might need to add a parameter `isRestored` to the `CommittableManager#commit`. If we want to also keep the same behavior for the `combine` method, we might need to do some more modification to the `CommittableManager` or not reuse the current implementation. However, currently the sink implementation in the `iceberg`, `hudi` and `flink-table-store` are indeed using the customized operators / legacy sink API instead of the sink API v1. In addition, the two issues should mainly affect he performance instead of the correctness. At last, users are still be able to add their own global committer implementation with topology API. Thus I think it is still useful to solve the two issues, but if we do not have capacity it would be also ok we postpone solving them. If so, perhaps we could create a new jira issue for state compatibility with the sink v1 and attach this PR to that issue, and dowgrade the FLINK-26173 and leaves it open? Since we have not fully fix the issues listed in the FLINK-26173~ [1] https://lists.apache.org/thread/3tqgnhclbr8ptb69b2ro74535dtbd608 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] flinkbot edited a comment on pull request #17933: [FLINK-24948][jdbc] Fix bug that special character in column names breaks JDBC statement parsing
flinkbot edited a comment on pull request #17933: URL: https://github.com/apache/flink/pull/17933#issuecomment-980508183 ## CI report: * 7d987dc1ebefcd9e92ce6d85ceec313de745e227 Azure: [FAILURE](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32560) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink-statefun] FilKarnicki commented on pull request #306: [FLINK-25866][statefun] Support additional TLS configuration
FilKarnicki commented on pull request #306: URL: https://github.com/apache/flink-statefun/pull/306#issuecomment-1059726797 hi @igalshilman I believe I addressed your concerns. Please let me know if there's anything else. Thanks! Fil -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[jira] [Created] (FLINK-26495) Dynamic table options does not work for view
Jane Chan created FLINK-26495:
-
Summary: Dynamic table options does not work for view
Key: FLINK-26495
URL: https://issues.apache.org/jira/browse/FLINK-26495
Project: Flink
Issue Type: Improvement
Components: Table SQL / API
Affects Versions: 1.15.0
Reporter: Jane Chan
The dynamic table options (aka. table hints) syntax
{code:java}
table_identifier /*+ OPTIONS(key=val [, key=val]*) */ {code}
does not work for the view without any exception thrown or suggestions to
users. It is not user-friendly and misleading. We should either throw a
meaningful exception or support this feature for view.
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[GitHub] [flink] flinkbot edited a comment on pull request #18928: [FLINK-25545][flink-clients][JUnit5 Migration] Module: flink-clients.
flinkbot edited a comment on pull request #18928: URL: https://github.com/apache/flink/pull/18928#issuecomment-1054170977 ## CI report: * 69a7198491e223208b865892c41a422fd86df5ed Azure: [SUCCESS](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32561) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] flinkbot edited a comment on pull request #18978: [FLINK-25549][flink-dstl] [JUnit5 Migration] Module: flink-dstl
flinkbot edited a comment on pull request #18978: URL: https://github.com/apache/flink/pull/18978#issuecomment-1059111709 ## CI report: * d55c277b2822bf631c2cb22483c646ff2104d322 Azure: [SUCCESS](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32562) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] RocMarshal opened a new pull request #18983: [FLINK-25543][flink-yarn] [JUnit5 Migration] Module: flink-yarn
RocMarshal opened a new pull request #18983: URL: https://github.com/apache/flink/pull/18983 ## What is the purpose of the change *[JUnit5 Migration] Module: flink-yarn* ## Brief change log [JUnit5 Migration] Module: flink-yarn ## Verifying this change This change is already covered by existing tests, such as *(please describe tests)*. ## Does this pull request potentially affect one of the following parts: - Dependencies (does it add or upgrade a dependency): (yes / **no**) - The public API, i.e., is any changed class annotated with `@Public(Evolving)`: (yes / **no**) - The serializers: (yes / **no** / don't know) - The runtime per-record code paths (performance sensitive): (yes / no / don't know) - Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (yes / **no** / don't know) - The S3 file system connector: (yes / **no** / don't know) ## Documentation - Does this pull request introduce a new feature? (yes / **no**) - If yes, how is the feature documented? (**not applicable** / docs / JavaDocs / not documented) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[jira] [Updated] (FLINK-22265) Abnormal document display
[ https://issues.apache.org/jira/browse/FLINK-22265?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-22265: --- Labels: auto-deprioritized-minor pull-request-available (was: pull-request-available stale-minor) Priority: Not a Priority (was: Minor) This issue was labeled "stale-minor" 7 days ago and has not received any updates so it is being deprioritized. If this ticket is actually Minor, please raise the priority and ask a committer to assign you the issue or revive the public discussion. > Abnormal document display > - > > Key: FLINK-22265 > URL: https://issues.apache.org/jira/browse/FLINK-22265 > Project: Flink > Issue Type: Improvement > Components: API / Core >Reporter: BoYi Zhang >Priority: Not a Priority > Labels: auto-deprioritized-minor, pull-request-available > Attachments: image-2021-04-14-11-00-24-999.png, > image-2021-04-14-11-01-47-226.png > > > > As shown in the figure, the document displays an exception : > > !image-2021-04-14-11-00-24-999.png! > > After repair : > > !image-2021-04-14-11-01-47-226.png! > > > > > > -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Updated] (FLINK-23167) Port Kinesis Table API e2e tests to release-1.12 branch
[ https://issues.apache.org/jira/browse/FLINK-23167?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Flink Jira Bot updated FLINK-23167: --- Labels: auto-deprioritized-major kinesis stale-minor (was: auto-deprioritized-major kinesis) I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help the community manage its development. I see this issues has been marked as Minor but is unassigned and neither itself nor its Sub-Tasks have been updated for 180 days. I have gone ahead and marked it "stale-minor". If this ticket is still Minor, please either assign yourself or give an update. Afterwards, please remove the label or in 7 days the issue will be deprioritized. > Port Kinesis Table API e2e tests to release-1.12 branch > --- > > Key: FLINK-23167 > URL: https://issues.apache.org/jira/browse/FLINK-23167 > Project: Flink > Issue Type: Improvement > Components: Connectors / Kinesis >Affects Versions: 1.12.6 >Reporter: Emre Kartoglu >Priority: Minor > Labels: auto-deprioritized-major, kinesis, stale-minor > Original Estimate: 24h > Remaining Estimate: 24h > > https://issues.apache.org/jira/browse/FLINK-20042 added e2e tests for the > Kinesis Table API. This was only done for versions >=1.13 however. > We need to port these tests to the release-1.12 branch as version 1.12 > supports the same functionality that needs the same (or a similar) test. -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Updated] (FLINK-25543) [JUnit5 Migration] Module: flink-yarn
[ https://issues.apache.org/jira/browse/FLINK-25543?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] ASF GitHub Bot updated FLINK-25543: --- Labels: pull-request-available (was: ) > [JUnit5 Migration] Module: flink-yarn > - > > Key: FLINK-25543 > URL: https://issues.apache.org/jira/browse/FLINK-25543 > Project: Flink > Issue Type: Sub-task > Components: Tests >Reporter: Hang Ruan >Priority: Minor > Labels: pull-request-available > -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Updated] (FLINK-21936) Rescale pointwise connections for unaligned checkpoints
[
https://issues.apache.org/jira/browse/FLINK-21936?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Flink Jira Bot updated FLINK-21936:
---
Labels: auto-deprioritized-major auto-deprioritized-minor (was:
auto-deprioritized-major stale-minor)
Priority: Not a Priority (was: Minor)
This issue was labeled "stale-minor" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Minor, please
raise the priority and ask a committer to assign you the issue or revive the
public discussion.
> Rescale pointwise connections for unaligned checkpoints
> ---
>
> Key: FLINK-21936
> URL: https://issues.apache.org/jira/browse/FLINK-21936
> Project: Flink
> Issue Type: Improvement
> Components: Runtime / Checkpointing
>Affects Versions: 1.13.0
>Reporter: Arvid Heise
>Priority: Not a Priority
> Labels: auto-deprioritized-major, auto-deprioritized-minor
>
> We currently do not have any hard guarantees on pointwise connection
> regarding data consistency. However, since data was structured implicitly in
> the same way as any preceding source or keyby, some users relied on this
> behavior to divide compute-intensive tasks into smaller chunks while relying
> on ordering guarantees.
> As long as the parallelism does not change, unaligned checkpoints (UC)
> retains these properties. With the implementation of rescaling of UC
> (FLINK-19801), that has changed. For most exchanges, there is a meaningful
> way to reassign state from one channel to another (even in random order). For
> some exchanges, the mapping is ambiguous and requires post-filtering.
> However, for point-wise connections, it's impossible while retaining these
> properties.
> Consider, {{source -> keyby -> task1 -> forward -> task2}}. Now if we want to
> rescale from parallelism p = 1 to p = 2, suddenly the records inside the
> keyby channels need to be divided into two channels according to the
> keygroups. That is easily possible by using the keygroup ranges of the
> operators and a way to determine the key(group) of the record (independent of
> the actual approach). For the forward channel, we completely lack the key
> context. No record in the forward channel has any keygroup assigned; it's
> also not possible to calculate it as there is no guarantee that the key is
> still present.
> The root cause for this limitation is the conceptual mismatch between what we
> provide and what some users assume we provide (or we assume that the users
> assume). For example, it's impossible to use (keyed) state in task2 right
> now, because there is no key context, but we still want to guarantee
> orderness in respect to that key context.
> For 1.13, the easiest solution is to disable channel state in pointwise
> connections. For any non-trivial application with at least one shuffle, the
> number of pointwise channels (linear to p) is quickly dwarfed by all-to-all
> connections (quadratic to p). I'd add some alternative ideas to the
> discussion.
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[jira] [Updated] (FLINK-25499) Column 'window_start' is ambiguous
[
https://issues.apache.org/jira/browse/FLINK-25499?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Flink Jira Bot updated FLINK-25499:
---
Labels: ambiguous stale-major window_start (was: ambiguous window_start)
I am the [Flink Jira Bot|https://github.com/apache/flink-jira-bot/] and I help
the community manage its development. I see this issues has been marked as
Major but is unassigned and neither itself nor its Sub-Tasks have been updated
for 60 days. I have gone ahead and added a "stale-major" to the issue". If this
ticket is a Major, please either assign yourself or give an update. Afterwards,
please remove the label or in 7 days the issue will be deprioritized.
> Column 'window_start' is ambiguous
> --
>
> Key: FLINK-25499
> URL: https://issues.apache.org/jira/browse/FLINK-25499
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / API
>Affects Versions: 1.14.2
> Environment: Flink 1.14.0
>Reporter: Shandy
>Priority: Major
> Labels: ambiguous, stale-major, window_start
>
> *For docs: [Window
> Aggregation|https://nightlies.apache.org/flink/flink-docs-release-1.14/docs/dev/table/sql/queries/window-agg/#cascading-window-aggregation]*
> *use sql-client create view such as:*
> =
> CREATE TEMPORARY VIEW IF NOT EXISTS telemetry_r_yangchen_standard_t
> AS
> (
> SELECT a.window_start,a.window_end,a.window_time as
> rowTime,last_value(a.tenantId) as tenantId
> FROM TABLE(TUMBLE(TABLE telemetry_r_yangchen_normal,
> DESCRIPTOR(receiveTimeTS), INTERVAL '10' MINUTES)) as a
> group by a.window_start, a.window_end,a.window_time
> );
> SELECT b.window_start, b.window_end,b.window_time as rowTime,sum(b.tenantId)
> as tenantId
> FROM TABLE(TUMBLE(TABLE telemetry_r_yangchen_standard_t,
> DESCRIPTOR(rowTime), INTERVAL '60' MINUTES)) as b
> group by b.window_start, b.window_end,b.window_time;
> =
> *above select occurs error message:*
> {color:#ff}*[ERROR] Could not execute SQL statement. Reason:
> org.apache.calcite.sql.validate.SqlValidatorException: Column 'window_start'
> is ambiguous
> *{color}
> *if modify create sql like this :*
>
> CREATE TEMPORARY VIEW IF NOT EXISTS telemetry_r_yangchen_standard_t
> AS
> (
> SELECT {color:#de350b}-a.windw_start,-{color}a.window_end,a.window_time
> as rowTime,last_value(a.tenantId) as tenantId
> FROM TABLE(TUMBLE(TABLE telemetry_r_yangchen_normal,
> DESCRIPTOR(receiveTimeTS), INTERVAL '10' MINUTES)) as a
> group by a.window_start, a.window_end,a.window_time
> );
> *or*
> CREATE TEMPORARY VIEW IF NOT EXISTS telemetry_r_yangchen_standard_t
> AS
> (
> SELECT {color:#de350b}cast(a.window_start as timestamp) as
> windowStart,cast(a.window_end as timestamp) as windowEnd,{color}a.window_time
> as rowTime,last_value(a.tenantId) as tenantId
> FROM TABLE(TUMBLE(TABLE telemetry_r_yangchen_normal,
> DESCRIPTOR(receiveTimeTS), INTERVAL '10' MINUTES)) as a
> group by a.window_start, a.window_end,a.window_time
> );
>
> *then, above select-sql can be executed ok!*
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[jira] [Updated] (FLINK-26041) AbstractTaskManagerProcessFailureRecoveryTest.testTaskManagerProcessFailure hang on azure
[
https://issues.apache.org/jira/browse/FLINK-26041?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Flink Jira Bot updated FLINK-26041:
---
Labels: auto-deprioritized-critical test-stability (was: stale-critical
test-stability)
Priority: Major (was: Critical)
This issue was labeled "stale-critical" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Critical,
please raise the priority and ask a committer to assign you the issue or revive
the public discussion.
> AbstractTaskManagerProcessFailureRecoveryTest.testTaskManagerProcessFailure
> hang on azure
> -
>
> Key: FLINK-26041
> URL: https://issues.apache.org/jira/browse/FLINK-26041
> Project: Flink
> Issue Type: Bug
> Components: Runtime / Coordination
>Affects Versions: 1.15.0
>Reporter: Yun Gao
>Priority: Major
> Labels: auto-deprioritized-critical, test-stability
>
> {code:java}
> Feb 08 13:04:58 "main" #1 prio=5 os_prio=0 tid=0x7fdcf000b800 nid=0x47bd
> waiting on condition [0x7fdcf697b000]
> Feb 08 13:04:58java.lang.Thread.State: WAITING (parking)
> Feb 08 13:04:58 at sun.misc.Unsafe.park(Native Method)
> Feb 08 13:04:58 - parking to wait for <0x8f644330> (a
> java.util.concurrent.CompletableFuture$Signaller)
> Feb 08 13:04:58 at
> java.util.concurrent.locks.LockSupport.park(LockSupport.java:175)
> Feb 08 13:04:58 at
> java.util.concurrent.CompletableFuture$Signaller.block(CompletableFuture.java:1707)
> Feb 08 13:04:58 at
> java.util.concurrent.ForkJoinPool.managedBlock(ForkJoinPool.java:3323)
> Feb 08 13:04:58 at
> java.util.concurrent.CompletableFuture.waitingGet(CompletableFuture.java:1742)
> Feb 08 13:04:58 at
> java.util.concurrent.CompletableFuture.get(CompletableFuture.java:1908)
> Feb 08 13:04:58 at
> org.apache.flink.util.AutoCloseableAsync.close(AutoCloseableAsync.java:36)
> Feb 08 13:04:58 at
> org.apache.flink.test.recovery.AbstractTaskManagerProcessFailureRecoveryTest.testTaskManagerProcessFailure(AbstractTaskManagerProcessFailureRecoveryTest.java:209)
> Feb 08 13:04:58 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native
> Method)
> Feb 08 13:04:58 at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
> Feb 08 13:04:58 at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> Feb 08 13:04:58 at java.lang.reflect.Method.invoke(Method.java:498)
> Feb 08 13:04:58 at
> org.junit.runners.model.FrameworkMethod$1.runReflectiveCall(FrameworkMethod.java:59)
> Feb 08 13:04:58 at
> org.junit.internal.runners.model.ReflectiveCallable.run(ReflectiveCallable.java:12)
> Feb 08 13:04:58 at
> org.junit.runners.model.FrameworkMethod.invokeExplosively(FrameworkMethod.java:56)
> Feb 08 13:04:58 at
> org.junit.internal.runners.statements.InvokeMethod.evaluate(InvokeMethod.java:17)
> Feb 08 13:04:58 at
> org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:54)
> Feb 08 13:04:58 at
> org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:54)
> Feb 08 13:04:58 at
> org.junit.rules.ExternalResource$1.evaluate(ExternalResource.java:54)
> Feb 08 13:04:58 at
> org.apache.flink.util.TestNameProvider$1.evaluate(TestNameProvider.java:45)
> Feb 08 13:04:58 at
> org.junit.rules.TestWatcher$1.evaluate(TestWatcher.java:61)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner$3.evaluate(ParentRunner.java:306)
> Feb 08 13:04:58 at
> org.junit.runners.BlockJUnit4ClassRunner$1.evaluate(BlockJUnit4ClassRunner.java:100)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner.runLeaf(ParentRunner.java:366)
> Feb 08 13:04:58 at
> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:103)
> Feb 08 13:04:58 at
> org.junit.runners.BlockJUnit4ClassRunner.runChild(BlockJUnit4ClassRunner.java:63)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner$4.run(ParentRunner.java:331)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner$1.schedule(ParentRunner.java:79)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner.runChildren(ParentRunner.java:329)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner.access$100(ParentRunner.java:66)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner$2.evaluate(ParentRunner.java:293)
> Feb 08 13:04:58 at
> org.junit.runners.ParentRunner.run(ParentRunner.java:413)
> Feb 08 13:04:58 at org.junit.runners.Suite.runChild(Suite.java:128)
> Feb 08 13:04:58 at org.junit.runners.Suite.runChild(Suite.java:27)
> {code}
> https://dev.azure.com/apache-flink/apache-flink/_bui
[GitHub] [flink] flinkbot commented on pull request #18983: [FLINK-25543][flink-yarn] [JUnit5 Migration] Module: flink-yarn
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[jira] [Created] (FLINK-26496) [JUnit5 Migration] Module: flink-yarn-test
RocMarshal created FLINK-26496: -- Summary: [JUnit5 Migration] Module: flink-yarn-test Key: FLINK-26496 URL: https://issues.apache.org/jira/browse/FLINK-26496 Project: Flink Issue Type: Improvement Components: Deployment / YARN, Tests Reporter: RocMarshal -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Commented] (FLINK-26496) [JUnit5 Migration] Module: flink-yarn-test
[ https://issues.apache.org/jira/browse/FLINK-26496?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17501708#comment-17501708 ] RocMarshal commented on FLINK-26496: Could someone please assign this ticket to me ? Thx:) > [JUnit5 Migration] Module: flink-yarn-test > -- > > Key: FLINK-26496 > URL: https://issues.apache.org/jira/browse/FLINK-26496 > Project: Flink > Issue Type: Improvement > Components: Deployment / YARN, Tests >Reporter: RocMarshal >Priority: Minor > -- This message was sent by Atlassian Jira (v8.20.1#820001)
[GitHub] [flink] smattheis opened a new pull request #18984: [hotfix][docs] Fix HTML formatting in ops/metrics.md
smattheis opened a new pull request #18984: URL: https://github.com/apache/flink/pull/18984 ## What is the purpose of the change Fix HTML in ops/metrics.md ## Brief change log Fix 'Note' paragraph and adapt to style to other 'Note' paragraphs of the rest of the document. ## Verifying this change Not applicable. ## Does this pull request potentially affect one of the following parts: Only docs affected ## Documentation - Does this pull request introduce a new feature? (yes / **no**) - If yes, how is the feature documented? (**not applicable** / docs / JavaDocs / not documented) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
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[GitHub] [flink] tonny1983 opened a new pull request #18985: [FLINK-26428][docs-zh] Significant differences of Fault Tolerance between English and Chinese version
tonny1983 opened a new pull request #18985: URL: https://github.com/apache/flink/pull/18985 ## What is the purpose of the change Update the `Fault Tolerance` chapter of Chinese version based on the current version ## Brief change log File location: docs/content.zh/docs/learn-flink/fault_tolerance.md ## Verifying this change a pure documentation translation ## Does this pull request potentially affect one of the following parts: - Dependencies (does it add or upgrade a dependency): no - The public API, i.e., is any changed class annotated with `@Public(Evolving)`: no - The serializers: (yes / no / don't know) - The runtime per-record code paths (performance sensitive): no - Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: no - The S3 file system connector: no ## Documentation - Does this pull request introduce a new feature? no - If yes, how is the feature documented? (not applicable / docs / JavaDocs / not documented) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
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[jira] [Created] (FLINK-26497) Cast Exception when use split agg with multiple filters
Jingsong Lee created FLINK-26497: Summary: Cast Exception when use split agg with multiple filters Key: FLINK-26497 URL: https://issues.apache.org/jira/browse/FLINK-26497 Project: Flink Issue Type: Bug Components: Table SQL / Planner Reporter: Jingsong Lee Fix For: 1.14.4 table.optimizer.distinct-agg.split.enabled is true. count(distinct c) filter (...), count(distinct c) filter (...), count(distinct c) filter (...) Filtering conditions excess 8. java.lang.RuntimeException: [J cannot be cast to [Ljava.lang.Object; (BTW, it seems that we don't have test case to cover this situation. -- This message was sent by Atlassian Jira (v8.20.1#820001)
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[GitHub] [flink] wuchong commented on pull request #18655: [FLINK-25799] [docs] Translate table/filesystem.md page into Chinese.
wuchong commented on pull request #18655: URL: https://github.com/apache/flink/pull/18655#issuecomment-1059773436 Thanks @RocMarshal and @MrWhiteSike ! I will merge it. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] wuchong merged pull request #18655: [FLINK-25799] [docs] Translate table/filesystem.md page into Chinese.
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[jira] [Closed] (FLINK-25799) Translate table/filesystem.md page into Chinese.
[ https://issues.apache.org/jira/browse/FLINK-25799?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Jark Wu closed FLINK-25799. --- Fix Version/s: 1.15.0 Resolution: Fixed Fixed in master: 8f88e8f5963ab25a3ed1eb35134dbde045c14afe > Translate table/filesystem.md page into Chinese. > > > Key: FLINK-25799 > URL: https://issues.apache.org/jira/browse/FLINK-25799 > Project: Flink > Issue Type: Sub-task > Components: Documentation >Reporter: RocMarshal >Assignee: baisike >Priority: Minor > Labels: chinese-translation, pull-request-available > Fix For: 1.15.0 > > > docs/content.zh/docs/connectors/table/filesystem.md -- This message was sent by Atlassian Jira (v8.20.1#820001)
[GitHub] [flink] RocMarshal commented on pull request #18986: [FLINK-26496][flink-yarn-test] [JUnit5 Migration] Module: flink-yarn-test
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[jira] [Updated] (FLINK-26496) [JUnit5 Migration] Module: flink-yarn-test
[ https://issues.apache.org/jira/browse/FLINK-26496?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] ASF GitHub Bot updated FLINK-26496: --- Labels: pull-request-available (was: ) > [JUnit5 Migration] Module: flink-yarn-test > -- > > Key: FLINK-26496 > URL: https://issues.apache.org/jira/browse/FLINK-26496 > Project: Flink > Issue Type: Improvement > Components: Deployment / YARN, Tests >Reporter: RocMarshal >Priority: Minor > Labels: pull-request-available > -- This message was sent by Atlassian Jira (v8.20.1#820001)
[GitHub] [flink] RocMarshal opened a new pull request #18986: [FLINK-26496][flink-yarn-test] [JUnit5 Migration] Module: flink-yarn-test
RocMarshal opened a new pull request #18986: URL: https://github.com/apache/flink/pull/18986 ## What is the purpose of the change [JUnit5 Migration] Module: flink-yarn-test ## Brief change log [JUnit5 Migration] Module: flink-yarn-test ## Verifying this change This change is already covered by existing tests ## Does this pull request potentially affect one of the following parts: - Dependencies (does it add or upgrade a dependency): (yes / **no**) - The public API, i.e., is any changed class annotated with `@Public(Evolving)`: (yes / **no**) - The serializers: (yes / **no** / don't know) - The runtime per-record code paths (performance sensitive): (yes / **no** / don't know) - Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Kubernetes/Yarn, ZooKeeper: (yes / **no** / don't know) - The S3 file system connector: (yes / **no** / don't know) ## Documentation - Does this pull request introduce a new feature? (yes / **no**) - If yes, how is the feature documented? (**not applicable** / docs / JavaDocs / not documented) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
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[jira] [Created] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
hehuiyuan created FLINK-26498:
-
Summary: The window result may not have been emitted when use
window emit feature and use lateTrigger.
Key: FLINK-26498
URL: https://issues.apache.org/jira/browse/FLINK-26498
Project: Flink
Issue Type: Improvement
Components: Table SQL / Planner
Reporter: hehuiyuan
Attachments: image-2022-03-05-23-53-37-086.png,
image-2022-03-05-23-53-44-196.png, image-2022-03-06-00-03-11-670.png
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for
>[0:00:00 1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
`hehuiyuan1,22,woman,2022-03-05 00:59:20.100` is lost， the lateTrigger is not
trigger and the window[0:00:00 ,1:00:00] is cleaned when the data
`hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
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[jira] [Updated] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
hehuiyuan updated FLINK-26498:
--
Description:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
`hehuiyuan1,22,woman,2022-03-05 00:59:20.100` is lost， the lateTrigger is not
trigger and the window[0:00:00 ,1:00:00] is cleaned when the data
`hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
was:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for
>[0:00:00 1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T0
[jira] [Commented] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17501763#comment-17501763
]
hehuiyuan commented on FLINK-26498:
---
Hi [~jark] ， have time to look at this problem.
> The window result may not have been emitted when use window emit feature and
> use lateTrigger.
> ---
>
> Key: FLINK-26498
> URL: https://issues.apache.org/jira/browse/FLINK-26498
> Project: Flink
> Issue Type: Improvement
> Components: Table SQL / Planner
>Reporter: hehuiyuan
>Priority: Major
> Attachments: image-2022-03-05-23-53-37-086.png,
> image-2022-03-05-23-53-44-196.png, image-2022-03-06-00-03-11-670.png
>
>
> the sql of job :
>
> {code:java}
> CREATE TABLE tableSource(
> name string,
> age int not null,
> sex string,
> dt TIMESTAMP(3),
> WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
> ) WITH (
> );
> CREATE TABLE tableSink(
> windowstart timestamp(3),
> windowend timestamp(3),
> name string,
> age int,
> cou bigint
> )
> WITH (
> );
> INSERT INTO tablesink
> SELECT
> TUMBLE_START(dt, INTERVAL '1' HOUR),
> TUMBLE_END(dt, INTERVAL '1' HOUR),
> name,
> age,
> count(sex)
> FROM tableSource
> GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
> and table config:
>
>
> {code:java}
> table.exec.emit.allow-lateness = 1 hour
> table.exec.emit.late-fire.delay = 1 min
> table.exec.emit.early-fire.delay = 1min{code}
> The data:
>
>
> {code:java}
> >hehuiyuan1,22,woman,2022-03-05 00:30:22.000
> >hehuiyuan1,22,woman,2022-03-05 00:40:22.000
> //pause ,wait for the window trigger for earlyTrigger 1 min
> >hehuiyuan1,22,woman,2022-03-05 00:50:22.000
> >hehuiyuan1,22,woman,2022-03-05 00:56:22.000
> //pause ,wait for the window trigger for earlyTrigger 1 min
> >hehuiyuan1,22,woman,2022-03-05 01:00:00.000
> //pause ,wait for the window trigger for earlyTrigger 1 min
> >hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
> //pause ,wait for the window trigger for earlyTrigger 1 min
> >hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
> >hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for
> >[0:00:00 1:00:00]
> >hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
> The result:
> {code:java}
> > +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> > -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> > +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> > +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> > -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> > +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
>
>
> > +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
>
> `hehuiyuan1,22,woman,2022-03-05 00:59:20.100` is lost， the lateTrigger is not
> trigger and the window[0:00:00 ,1:00:00] is cleaned when the data
> `hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated watermark.
>
> The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
> The trigger is AfterEndOfWindowEarlyAndLate .
> So WindowOpearator may need to emit reuslt when the window cleanupTimer call
> onEventTime.
> I think the correct result is as follows:
>
>
> {code:java}
> > +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> > -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> > +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> > +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> > -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> > +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> > -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> > +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> > +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
>
--
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[jira] [Assigned] (FLINK-26406) Significant differences of Fault Tolerance between English and Chinese version
[ https://issues.apache.org/jira/browse/FLINK-26406?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Yun Tang reassigned FLINK-26406: Assignee: tonny > Significant differences of Fault Tolerance between English and Chinese version > -- > > Key: FLINK-26406 > URL: https://issues.apache.org/jira/browse/FLINK-26406 > Project: Flink > Issue Type: Bug > Components: chinese-translation, Documentation >Affects Versions: 1.14.3 >Reporter: tonny >Assignee: tonny >Priority: Major > > There are significant differences of Fault Tolerance between English and > Chinese version. And obviously, the Chinese version has been translated from > an old version documents. For example, it lists three available > implementations of state backends, all of which are masked as *Deprecated* in > Flink ver. 1.14. -- This message was sent by Atlassian Jira (v8.20.1#820001)
[jira] [Commented] (FLINK-26406) Significant differences of Fault Tolerance between English and Chinese version
[ https://issues.apache.org/jira/browse/FLINK-26406?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17501764#comment-17501764 ] Yun Tang commented on FLINK-26406: -- I see, these parts belong to the learn-flink module. Already assigned to you, please go ahead. > Significant differences of Fault Tolerance between English and Chinese version > -- > > Key: FLINK-26406 > URL: https://issues.apache.org/jira/browse/FLINK-26406 > Project: Flink > Issue Type: Bug > Components: chinese-translation, Documentation >Affects Versions: 1.14.3 >Reporter: tonny >Assignee: tonny >Priority: Major > > There are significant differences of Fault Tolerance between English and > Chinese version. And obviously, the Chinese version has been translated from > an old version documents. For example, it lists three available > implementations of state backends, all of which are masked as *Deprecated* in > Flink ver. 1.14. -- This message was sent by Atlassian Jira (v8.20.1#820001)
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[jira] [Updated] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
hehuiyuan updated FLINK-26498:
--
Description:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
`hehuiyuan1,22,woman,2022-03-05 00:59:20.100` is lost， the lateTrigger is not
trigger and the window[0:00:00 ,1:00:00] is cleaned when the data
`hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
was:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00
[jira] [Updated] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
hehuiyuan updated FLINK-26498:
--
Description:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
`hehuiyuan1,22,woman,2022-03-05 00:59:20.100` is lost， the lateTrigger is not
trigger and the window[0:00:00 ,1:00:00] is cleaned when the data
`hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
was:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-
[jira] [Updated] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
hehuiyuan updated FLINK-26498:
--
Description:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
`hehuiyuan1,22,woman,2022-03-05 00:59:20.100` window result is lost， the
lateTrigger is not trigger and the window[0:00:00 ,1:00:00] is cleaned when the
data `hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived that updated
watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
was:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:0
[jira] [Updated] (FLINK-26498) The window result may not have been emitted when use window emit feature and use lateTrigger.
[
https://issues.apache.org/jira/browse/FLINK-26498?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
hehuiyuan updated FLINK-26498:
--
Description:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
The window result is lost when `hehuiyuan1,22,woman,2022-03-05 00:59:20.100`
arrived， the lateTrigger is not trigger and the window[0:00:00 ,1:00:00] is
cleaned when the data `hehuiyuan1,22,woman,2022-03-05 02:00:00.000` arrived
that updated watermark.
The window[0:00:00 ,1:00:00] has 6 pieces of data, but we got 5.
The trigger is AfterEndOfWindowEarlyAndLate .
So WindowOpearator may need to emit reuslt when the window cleanupTimer call
onEventTime.
I think the correct result is as follows:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I(+I[2022-03-05T01:00, 2022-03-05T02:00, hehuiyuan1, 22, 1])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 5])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 6])
> +I(+I[2022-03-05T02:00, 2022-03-05T03:00, hehuiyuan1, 22, 2]) {code}
was:
the sql of job :
{code:java}
CREATE TABLE tableSource(
name string,
age int not null,
sex string,
dt TIMESTAMP(3),
WATERMARK FOR dt AS dt - INTERVAL '0' SECOND
) WITH (
);
CREATE TABLE tableSink(
windowstart timestamp(3),
windowend timestamp(3),
name string,
age int,
cou bigint
)
WITH (
);
INSERT INTO tablesink
SELECT
TUMBLE_START(dt, INTERVAL '1' HOUR),
TUMBLE_END(dt, INTERVAL '1' HOUR),
name,
age,
count(sex)
FROM tableSource
GROUP BY TUMBLE(dt, INTERVAL '1' HOUR), name,age {code}
and table config:
{code:java}
table.exec.emit.allow-lateness = 1 hour
table.exec.emit.late-fire.delay = 1 min
table.exec.emit.early-fire.delay = 1min{code}
The data:
{code:java}
>hehuiyuan1,22,woman,2022-03-05 00:30:22.000
>hehuiyuan1,22,woman,2022-03-05 00:40:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:50:22.000
>hehuiyuan1,22,woman,2022-03-05 00:56:22.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 01:00:00.000
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.000 --latency data
//pause ,wait for the window trigger for earlyTrigger 1 min
>hehuiyuan1,22,woman,2022-03-05 00:59:20.100 --latency data
>hehuiyuan1,22,woman,2022-03-05 02:00:00.000 -- window state clean for [0:00:00
>1:00:00]
>hehuiyuan1,22,woman,2022-03-05 02:10:00.000 {code}
The result:
{code:java}
> +I(+I[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> -U(-U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 2])
> +U(+U[2022-03-05T00:00, 2022-03-05T01:00, hehuiyuan1, 22, 4])
> +I
[GitHub] [flink] flinkbot edited a comment on pull request #17933: [FLINK-24948][jdbc] Fix bug that special character in column names breaks JDBC statement parsing
flinkbot edited a comment on pull request #17933: URL: https://github.com/apache/flink/pull/17933#issuecomment-980508183 ## CI report: * 7d987dc1ebefcd9e92ce6d85ceec313de745e227 Azure: [FAILURE](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32560) * ecaf798ecefbc6fcfdbcd891d5589e7a2cdf6313 UNKNOWN Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] flinkbot edited a comment on pull request #17933: [FLINK-24948][jdbc] Fix bug that special character in column names breaks JDBC statement parsing
flinkbot edited a comment on pull request #17933: URL: https://github.com/apache/flink/pull/17933#issuecomment-980508183 ## CI report: * 7d987dc1ebefcd9e92ce6d85ceec313de745e227 Azure: [FAILURE](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32560) * ecaf798ecefbc6fcfdbcd891d5589e7a2cdf6313 Azure: [PENDING](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32573) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] flinkbot edited a comment on pull request #18986: [FLINK-26496][flink-yarn-test] [JUnit5 Migration] Module: flink-yarn-test
flinkbot edited a comment on pull request #18986: URL: https://github.com/apache/flink/pull/18986#issuecomment-1059778170 ## CI report: * 157009e24cc7b1482aa2eba02695e78d3d44f545 Azure: [FAILURE](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32572) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
[GitHub] [flink] flinkbot edited a comment on pull request #17933: [FLINK-24948][jdbc] Fix bug that special character in column names breaks JDBC statement parsing
flinkbot edited a comment on pull request #17933: URL: https://github.com/apache/flink/pull/17933#issuecomment-980508183 ## CI report: * ecaf798ecefbc6fcfdbcd891d5589e7a2cdf6313 Azure: [FAILURE](https://dev.azure.com/apache-flink/98463496-1af2-4620-8eab-a2ecc1a2e6fe/_build/results?buildId=32573) Bot commands The @flinkbot bot supports the following commands: - `@flinkbot run azure` re-run the last Azure build -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: issues-unsubscr...@flink.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
