As mentioned in the answer to this question, "SVM training can be arbitrary long" depending on the parameters selected.
If I remember correctly from my ML class, running time is roughly proportional to the square of the number training examples, so for 800k
examples you probably do not want to wait.
Also, as an anecdote, I once ran e1071
in R
for more than two days on a smaller data set than yours. It eventually completed, but the training took too long for my needs.
Keep in mind that most ML algorithms, including SVM, will usually not achieve the desired result out of the box. Therefore, when you are thinking about how fast you need it to run, keep in mind that you will have to pay the running time every time you tweak a tuning parameter. Of course you can reduce this running time by sampling down to a smaller training set, with the understanding that you will be learning from less data.