Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/21183#discussion_r187217859
--- Diff: mllib/src/main/scala/org/apache/spark/ml/clustering/LDA.scala ---
@@ -622,11 +623,11 @@ object LocalLDAModel extends
MLReadable[LocalLDAModel] {
val vectorConverted = MLUtils.convertVectorColumnsToML(data,
"docConcentration")
val matrixConverted =
MLUtils.convertMatrixColumnsToML(vectorConverted, "topicsMatrix")
val Row(vocabSize: Int, topicsMatrix: Matrix, docConcentration:
Vector,
- topicConcentration: Double, gammaShape: Double) =
+ topicConcentration: Double, gammaShape: Double, seed: Long) =
--- End diff --
This will break backwards compatibility of ML persistence (when users try
to load LDAModels saved using past versions of Spark). Could you please test
this manually by saving a LocalLDAModel using Spark 2.3 and loading it with a
build of your PR? You can fix this by checking for the Spark version (in the
`metadata`) and loading the seed for Spark >= 2.4.
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