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Till Rohrmann updated FLINK-5936: --------------------------------- Priority: Minor (was: Major) > 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 > Priority: Minor > > 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 > Alex -- This message was sent by Atlassian JIRA (v6.3.15#6346)