Just one thing: It might be better to post these as separate questions because they are quite different.
Another thing: I am pretty new to this so don't treat my answers as being 100% correct but hopefully they might be helpful.
1. Usually logistic regression has a binary outcome like yes/no or hit/miss. It looks like you are talking about multinomial logistic regression where there are multiple outcomes or classes to predict e.g. low/medium/high.
I just got that from http://en.wikipedia.org/wiki/Multinomial_logit
I don't know much more about it.
2. I can't see the picture, but I imagine that normally you would do a classification of your data and then do another classification off of the data as another branch. RapidMinre then has nodes that help you assess the performance of each classification. It is probably worth going through the available videos to get an idea of the flow of a job in RapidMiner.
For text mining, I found the videos at http://vancouverdata.blogspot.ie/2010/11/text-analytics-with-rapidminer-loading.html
3. I don't know much about this yet. I kind of presume there are nodes and things in RapidMiner that help in the exporting of your code. RM produces java code under the hood so I imagine it is more straightforward to export to a java application. But I don't have experience of this yet.