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https://issues.apache.org/jira/browse/FLINK-37067?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17930180#comment-17930180
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Yutong Han commented on FLINK-37067:
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Hi [~yyhx]
I should be able to wrap thing up by this week.
* And I few things for [context and state
processing|https://nightlies.apache.org/flink/flink-docs-release-2.0/docs/dev/datastream-v2/context_and_state_processing/]
** I am creating a WordCount with stateful function implement
OneInputStreamProcessFunction. And trying to run the Flink application locally
with flink-2.0-preview1 binary download from
[here|https://www.apache.org/dyn/closer.lua/flink/flink-2.0-preview1/flink-2.0-preview1-bin-scala_2.12.tgz]
The flink version I am using is _2.0-SNAPSHOT_ But getting
_java.lang.NoSuchMethodError
'org.apache.flink.datastream.api.stream.NonKeyedPartitionStream$ProcessConfigurableAndNonKeyedPartitionStream
org.apache.flink.datastream.api.ExecutionEnvironment.fromSource(org.apache.flink.api.connector.dsv2.Source,
java.lang.String)'_ I think it may because the flink-2.0-preview1 binary
release doesn't contain the latest changes. Please help to advise on this,
thanks.
** Nit: The example in the doc _ListState<Long> state = stateOptional.get();_
probably avoid Optional.get without a isPresent check.
> 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
> Assignee: Yutong Han
> 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:
> # [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]\
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