Hey Spark devs I noticed that we now have a large number of examples for ML & MLlib in the examples project - 57 for ML and 67 for MLLIB to be precise. This is bound to get larger as we add features (though I know there are some PRs to clean up duplicated examples).
What do you think about organizing them into packages to match the use case and the structure of the code base? e.g. org.apache.spark.examples.ml.recommendation org.apache.spark.examples.ml.feature and so on... Is it worth doing? The doc pages with include_example would need updating, and the run_example script input would just need to change the package slightly. Did I miss any potential issue? N
