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https://issues.apache.org/jira/browse/FLINK-1193?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14296788#comment-14296788
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ASF GitHub Bot commented on FLINK-1193:
---------------------------------------
GitHub user twalthr opened a pull request:
https://github.com/apache/flink/pull/348
[FLINK-1193][java-api][scala-api] Complete support for multidimensional
arrays
This PR introduces official support for multidimensional arrays.
It contains bug fixes for TypeExtractor and Serializer (see [FLINK-1193])
as well as adds tests for Java and Scala API.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/twalthr/flink MultidimensionalArrays
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/348.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 #348
----
commit 9b66b6a56ceeb948f1cb6b6045dd9063ad33016f
Author: twalthr <[email protected]>
Date: 2015-01-27T13:07:12Z
[FLINK-1193][java-api][scala-api] Complete support for multidimensional
arrays
----
> InvalidTypesException for Array[Array[Tuple2[Int, Double]]]
> -----------------------------------------------------------
>
> Key: FLINK-1193
> URL: https://issues.apache.org/jira/browse/FLINK-1193
> Project: Flink
> Issue Type: Bug
> Reporter: Till Rohrmann
> Assignee: Timo Walther
>
> The TypeExtractor cannot handle nested arrays with non-trivial element types.
> For example, the following code cannot be run
> {code}
> val input = env.fromCollection(List(1,2,3,4))
> val mapped = input.map{
> id => {
> val pair = (1,1.0)
> val a = Array(pair)
> val b = Array(a)
> b
> }
> }
> {code}
> The resulting type Array[Array[Tuple2[Int, Double]]] cannot be extracted. It
> would be nice, if Flink supported these types.
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