Some users may have some deployment systems in place already for which exporting the developed models to users' desired forms could be good enough.
For linear regression and logistic regression, MLlib supports model exporting to Predictive Model Markup Language (PMML).
For more information about exporting to PMML from MLlib, visit https://spark.apache.org/docs/latest/mllib-pmml-model-export.html.
For the R notebook, it can be run on another environment directly. Also, with the R package PMML, R models can be exported.
For more information on the R package PMML, go to http://journal.r-project.org/archive/2009-1/RJournal_2009-1_Guazzelli+et+al.pdf.
It is also possible to deploy the models for decision making directly on Apache Spark and make the results easily available to users.
Two commonly used methods of deploying results are (1) dashboard and (2) rule-based decision making. Which one to select depends on who we will supply our result to.
Here, we will discuss them only briefly as...