I am new to opencpu. My specialty is java. I use R for very specific
analyses.
*PROBLEM*
My understanding is that each API call to opencpu opens a new R session.
My function will classify the data input using the predict method of a
linear discriminant analysis (lda from MASS package).
The initial linear discriminant analysis on 100000+ cases and 150+ factor
levels takes time (over 30 seconds). This function returns a list.
The subsequent prediction function is quick and returns a simple vector.
*APPROACH*
I run one opencpu function to run the initial lda. This only needs to run
once.
I want my second function to ONLY run the predict function. This is
possible if the lda is held as a global variable.
My understanding is that global variables are not possible in opencpu. So I
will have to cache the lda on the file system.
In sum, I need to run the lda just once and hold the analysis (a list)
either in memory or on the file system. I then retrieve the lda analysis
when predict is called.
*QUESTION*
Which approach is best, and how to implement?
1. I could use an opencpu function that creates and returns the lda. Then
when I call a prediction, I could retrieve the lda object (a list) from the
file system. But how do I retrieve the list from the file system. How
does opencpu even know where it is?
2. I could use r.cache package. I haven't used this package before but the
docs suggest it is a solution. Will this work?
Any advice would be deeply appreciated.
best
jake
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