Imagine that I am training a Spark MLlib model as follows:
val traingData = loadTrainingData(...)val logisticRegression = new
LogisticRegression()
traingData.cacheval logisticRegressionModel =
logisticRegression.fit(trainingData)
Does the call traingData.cache improve performances at training
Is Spark planning to support *online scoring* (without any Spark
dependencies) of a PipelineModel trained offline? Not being able to do so
is a huge barrier to entry for using Spark in production at my company...
For online support, I found this https://github.com/combust/mleap
Any feedback on
