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https://issues.apache.org/jira/browse/FLINK-26301?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17497548#comment-17497548
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Jing Ge edited comment on FLINK-26301 at 2/24/22, 6:58 PM:
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>> The reason of choosing PublicEvolving is that the API will not change.
> Personally, I am not that confident.
It make sense to mark AvroParquetReaders as Experimental. The class
AvroParquetRecordFormat is used via the PublicEvolving interface StreamFormat.
Why should we use Experimental in this case?
was (Author: jingge):
>> The reason of choosing PublicEvolving is that the API will not change.
> Personally, I am not that confident.
The class is used via the PublicEvolving interface StreamFormat. Why should we
use Experimental in this case?
> Test AvroParquet format
> -----------------------
>
> Key: FLINK-26301
> URL: https://issues.apache.org/jira/browse/FLINK-26301
> Project: Flink
> Issue Type: Improvement
> Components: Formats (JSON, Avro, Parquet, ORC, SequenceFile)
> Reporter: Jing Ge
> Assignee: Dawid Wysakowicz
> Priority: Blocker
> Labels: release-testing
> Fix For: 1.15.0
>
>
> The following scenarios are worthwhile to test
> * Start a simple job with None/At-least-once/exactly-once delivery guarantee
> read Avro Generic/sSpecific/Reflect records and write them to an arbitrary
> sink.
> * Start the above job with bounded/unbounded data.
> * Start the above job with streaming/batch execution mode.
>
> This format works with FileSource[2] and can only be used with DataStream.
> Normal parquet files can be used as test files. Schema introduced at [1]
> could be used.
>
> [1]Reference:
> [1][https://nightlies.apache.org/flink/flink-docs-master/docs/connectors/datastream/formats/parquet/]
> [2]
> [https://nightlies.apache.org/flink/flink-docs-master/docs/connectors/datastream/filesystem/]
>
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