April 2017
Beginner to intermediate
420 pages
9h 58m
English
Let's assume you have the bank_DL.csv file saved in your working directory. Remember, getwd() will provide you with the path to it. So, let's load the library and create an object with the file path to the data:
> library(h2o) > path <- "C:/.../bank_DL.csv"
We can now connect to H2O and start an instance on the cluster. Specifying nthreads = -1 requests our instance use all CPUs on the cluster:
> localH2O = h2o.init(nthreads = -1)
The H2O function, h2o.uploadFile(), allows you to upload/import your file to the H2O cloud. The following functions are also available for uploads:
It is quite simple to upload the file and a per cent indicator tracks the status:
> bank <- ...Read now
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