Interesting! One more reason to use sparklyr. Do you know of any R Markdown report/GitHub repository containing a Data Science analysis performed with sparklyr? Preferably on open data (otherwise I won't be able to reproduce it).
However, when it comes to spark_apply function, the better option is not Sparklyr or SparkR, it should be spark-shell or pyspark which is more robust for your program and better error tracing.
I'd like to show my Python-purist coworkers that R can be successfully deployed in production for actual Big Data (TB-scale) projects, so it's probably better not to use a Python module for that 
Thanks! But I can't read Chinese
personally, I'm already convinced that sparklyr > sparkr. However, if you translate your blog post to English, I'll be happy to tweet about it. It sounds like an interesting resource.