We are trying to create a customized transformer for a ML pipeline and
also want to persist the trained pipeline and retrieve it for
production. To enable persistency, we will have to implement read/write
functions. However, this is not feasible in Scala since the read/write
methods are private members of the MLModel class. This problem was
described in a JIRA ticket https://issues.apache.org/jira/browse/SPARK-17048
Although the ticket suggested some workaround, but only in Java. I was
wondering if anyone has tried in Scala? The scala work-around suggested
in the ticket didn't work for us. Does anyone know if this issue has
been resolved in 3.0.1 or the upcoming 3.1? Any suggestion is highly
appreciated.
-- ND
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