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https://issues.apache.org/jira/browse/FLINK-1758?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14502885#comment-14502885
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ASF GitHub Bot commented on FLINK-1758:
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Github user andralungu commented on the pull request:
https://github.com/apache/flink/pull/576#issuecomment-94461019
Hi @vasia ,
The inline comments have been addressed, I still have the big comment to
look at :)
One thing(or two ^^) that could be discussed:
- the inconsistency between the iterateOn* and the reduce* method names
comes from the fact that the two methods have different behaviour: reduce takes
the elements two by two and aggregates them while iterateOn uses an iterator to
go through the edges. Hence the different names.
Imagine something like this:
Tuple2<K, Edge<K, EV>> iterateOnEdges(Tuple2<K, Edge<K, EV>> firstEdge,
Tuple2<K, Edge<K, EV>> secondEdge);
when you're not iterating on anything(or vice-versa reduceOnEdges(Iterable
edges)).
- I know ReduceEdgesFunction is not a pretty name, but I don't have another
one, ReduceFunction is already taken :P. When you think of a better name, tell
me and I can do the refactoring.
> Extend Gelly's neighborhood methods
> -----------------------------------
>
> Key: FLINK-1758
> URL: https://issues.apache.org/jira/browse/FLINK-1758
> Project: Flink
> Issue Type: Improvement
> Components: Gelly
> Affects Versions: 0.9
> Reporter: Vasia Kalavri
> Assignee: Andra Lungu
>
> Currently, the neighborhood methods only allow returning a single value per
> vertex. In many cases, it is desirable to return several or no value per
> vertex. This is the case in clustering coefficient computation,
> vertex-centric jaccard, algorithms where a vertex computes a value per edge
> or when a vertex computes a value only for some of its neighbors.
> This issue proposes to
> - change the current reduceOnEdges/reduceOnNeighbors methods to use
> combinable reduce operations where possible
> - provide groupReduce-versions, which will use a Collector and allow
> returning none or more values per vertex.
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