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From "Alex DeCastro (JIRA)" <j...@apache.org>
Subject [jira] [Created] (FLINK-5936) Can't pass keyed vectors to KNN join algorithm
Date Tue, 28 Feb 2017 12:16:45 GMT
Alex DeCastro created FLINK-5936:

             Summary: Can't pass keyed vectors to KNN join algorithm  
                 Key: FLINK-5936
                 URL: https://issues.apache.org/jira/browse/FLINK-5936
             Project: Flink
          Issue Type: Improvement
          Components: Machine Learning Library
    Affects Versions: 1.1.3
            Reporter: Alex DeCastro

Hi there, 
I noticed that for Scala 2.10/Flink 1.1.3 there's no way to recover keys from the predict
method of KNN join even if the Vector (FlinkVector) class gets extended to allow for keys.

If I create a class say, SparseVectorsWithKeys the predict method will return SparseVectors
only. Any workarounds here?  

Would it be possible to either extend the Vector class or the ML models to consume and output
keyed vectors?  This is very important to NLP and pretty much a lot of ML pipeline debugging
-- including logging. 

Thanks a lot

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