title: Loading a pyspark ML model in a non-Spark environment
body: <p>I am interested in deploying a machine learning model in python, so predictions can be made through requests to a server.</p>
  
  <p>I will create a Cloudera cluster and take advantage of Spark to develop the models, by using the library <em>pyspark</em>. I would like to know how the model can be saved in order to employ it on the server. </p>
  
  <p>I have seen that the different algorithms have the .save functions (like it is answered in this post <a href="https://stackoverflow.com/questions/34270427/how-to-save-and-load-mllib-model-in-apache-spark">How to save and load MLLib model in Apache Spark</a>), but as the server will be in a different machine without Spark and not in the Cloudera cluster, I don't know if it is possible to use their .load and .predict  functions.</p>
  
  <p>Can it be made by using the <em>pyspark</em> library functions for prediction without Spark underneath? Or would I have to do any transformations in order to save the model and use it elsewhere? </p>