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https://issues.apache.org/jira/browse/FLINK-37067?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17916582#comment-17916582
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xuhuang edited comment on FLINK-37067 at 1/24/25 7:38 AM:
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In Flink 2.0, we have introduce DataStream API V2. To verify this feature, you
should test four scenarios:
1. Write a stateful DataStream program, such as WordCount. Use ProcessFunction
to receive and process data, and use State to store the state. You can refer to
the documentation:
# [context and state
processing|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/context_and_state_processing/]
2. Write a window aggregation job using the event time extension and verify it.
You can refer to the documentation:
# Event Time
## [Event Timer
Service|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/time-processing/event_timer_service/]
## Examples listed in [FLIP-499: Support Event Time in DataStream
V2|https://cwiki.apache.org/confluence/x/pQz0Ew]
# Window
##
[Windows|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/builtin-funcs/windows/]
## Examples listed in [FLIP-501: Support Window in DataStream
V2|https://cwiki.apache.org/confluence/x/z4kgF]
3. Write a Join job using the BuiltinFuncs#join and verify it. You can refer to
the documentation:
#
[Joins|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/builtin-funcs/joining/]
# Examples listed in [FLIP-500: Support Join in DataStream
V2|https://cwiki.apache.org/confluence/x/ywz0Ew]
4. Write a job define and using the Watermark and verify it. You can refer to
the documentation:
#
[Watermark|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/watermark/]
# Examples listed in [FLIP-467: Introduce Generalized
Watermarks|https://cwiki.apache.org/confluence/x/oA6TEg]
was (Author: JIRAUSER300304):
In Flink 2.0, we have introduce DataStream API V2. To verify this feature, you
should test four scenarios:
1. Write a stateful DataStream program, such as WordCount. Use ProcessFunction
to receive and process data, and use State to store the state. You can refer to
the documentation:
# [context and state
processing|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/context_and_state_processing/]
2. Write a window aggregation job using the event time extension and verify it.
You can refer to the documentation:
# Event Time
##
[event_timer_service|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/time-processing/event_timer_service/]
## Examples listed in [FLIP-499: Support Event Time in DataStream
V2|https://cwiki.apache.org/confluence/x/pQz0Ew]
# Window
##
[Windows|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/builtin-funcs/windows/]
## Examples listed in [FLIP-501: Support Window in DataStream
V2|https://cwiki.apache.org/confluence/x/z4kgF]
3. Write a Join job using the BuiltinFuncs#join and verify it. You can refer to
the documentation:
#
[Joins|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/builtin-funcs/joining/]
# Examples listed in [FLIP-500: Support Join in DataStream
V2|https://cwiki.apache.org/confluence/x/ywz0Ew]
4. Write a job define and using the Watermark and verify it. You can refer to
the documentation:
#
[Watermark|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/watermark/]
# Examples listed in [FLIP-467: Introduce Generalized
Watermarks|https://cwiki.apache.org/confluence/x/oA6TEg]
> Cross-team verification for “Introduce DataStream API V2”
> ---------------------------------------------------------
>
> Key: FLINK-37067
> URL: https://issues.apache.org/jira/browse/FLINK-37067
> Project: Flink
> Issue Type: Sub-task
> Reporter: Xintong Song
> Priority: Blocker
> Fix For: 2.0.0
>
>
> In Flink 2.0, we have introduce DataStream API V2. To verify this feature,
> you should test four scenarios:
> 1. Write a stateful DataStream program, such as WordCount. Use
> ProcessFunction to receive and process data, and use State to store the
> state. You can refer to the documentation:
> # docs/content/docs/dev/datastream-v2/context_and_state_processing.md
> 2. Write a window aggregation job using the event time extension and verify
> it. You can refer to the documentation:
> # Event Time
> ## docs/content/docs/dev/datastream-v2/time-processing/event_timer_service.md
> ## Examples listed in [FLIP-499: Support Event Time in DataStream
> V2|https://cwiki.apache.org/confluence/x/pQz0Ew]
> # Window
> ## docs/content.zh/docs/dev/datastream-v2/builtin-funcs/windows.md
> ## Examples listed in [FLIP-501: Support Window in DataStream
> V2|https://cwiki.apache.org/confluence/x/z4kgF]
> 3. Write a Join job using the BuiltinFuncs#join and verify it. You can refer
> to the documentation:
> # docs/content/docs/dev/datastream-v2/builtin-funcs/joining.md
> # Examples listed in [FLIP-500: Support Join in DataStream
> V2|https://cwiki.apache.org/confluence/x/ywz0Ew]
> 4. Write a job define and using the Watermark and verify it. You can refer to
> the documentation:
> # docs/content.zh/docs/dev/datastream-v2/watermark.md
> # Examples listed in [FLIP-467: Introduce Generalized
> Watermarks|https://cwiki.apache.org/confluence/x/oA6TEg]
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