[jira] [Commented] (FLINK-7939) DataStream of atomic type cannot be converted to Table with time attributes

["ASF GitHub Bot (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-7939?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16223723#comment-16223723 ] 

ASF GitHub Bot commented on FLINK-7939:
---------------------------------------

GitHub user fhueske opened a pull request:

    https://github.com/apache/flink/pull/4917

    [FLINK-7939] [table] Fix Table conversion of DataStream of AtomicType.

    ## What is the purpose of the change
    
    Fix the conversion of a `DataStream` of an `AtomicType` to a `Table` with time attributes.
    
    ## Brief change log
    
    * Fix index computation for table fields from `AtomicType`
    * Fix field type computation for tables from `AtomicType`
    
    ## Verifying this change
    
    Added tests to
    * `StreamTableEnvironmentTest`
    * `TimeAttributesITCase`
    
    ## 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: **no**
      - The runtime per-record code paths (performance sensitive): **no**
      - Anything that affects deployment or recovery: JobManager (and its components), Checkpointing, Yarn/Mesos, ZooKeeper: **no**
    
    ## Documentation
    
    Fix doesn't need documentation.


You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/fhueske/flink tableAtomicStream

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/flink/pull/4917.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #4917
    
----
commit 437eeba6c0d78143a53654517bb4ace47b9bf53a
Author: Fabian Hueske <fh...@apache.org>
Date:   2017-10-28T20:13:23Z

    [FLINK-7939] [table] Fix Table conversion of DataStream of AtomicType.

----


> DataStream of atomic type cannot be converted to Table with time attributes
> ---------------------------------------------------------------------------
>
>                 Key: FLINK-7939
>                 URL: https://issues.apache.org/jira/browse/FLINK-7939
>             Project: Flink
>          Issue Type: Bug
>          Components: Table API & SQL
>    Affects Versions: 1.4.0, 1.3.3
>            Reporter: Fabian Hueske
>            Assignee: Fabian Hueske
>             Fix For: 1.4.0, 1.3.3
>
>
> A DataStream of an atomic type, such as {{DataStream<String>}} or {{DataStream<Long>}} cannot be converted into a {{Table}} with a time attribute.
> {code}
> DataStream<String> stream = ...
> Table table = tEnv.fromDataStream(stream, "string, rowtime.rowtime")
> {code}
> yields
> {code}
> Exception in thread "main" org.apache.flink.table.api.TableException: Field reference expression requested.
>     at org.apache.flink.table.api.TableEnvironment$$anonfun$1.apply(TableEnvironment.scala:630)
>     at org.apache.flink.table.api.TableEnvironment$$anonfun$1.apply(TableEnvironment.scala:624)
>     at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
>     at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
>     at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
>     at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:186)
>     at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
>     at scala.collection.mutable.ArrayOps$ofRef.flatMap(ArrayOps.scala:186)
>     at org.apache.flink.table.api.TableEnvironment.getFieldInfo(TableEnvironment.scala:624)
>     at org.apache.flink.table.api.StreamTableEnvironment.registerDataStreamInternal(StreamTableEnvironment.scala:398)
>     at org.apache.flink.table.api.scala.StreamTableEnvironment.fromDataStream(StreamTableEnvironment.scala:85)
> {code}
> As a workaround the atomic type can be wrapped in {{Tuple1}}, i.e., convert a {{DataStream<String>}} into a {{DataStream<Tuple1<String>>}}.



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