I'm trying to understand how all the "big data" components play together in a real world use case, e.g. hadoop, monogodb/nosql, storm, kafka, ... I know that this is quite a wide range of tools used for different types, but I'd like to get to know more about their interaction in applications, e.g. thinking machine learning for an app, webapp, online shop.
I have vistors/session, transaction data etc and store that; but if I want to make recommendations on the fly, I can't run slow map/reduce jobs for that on some big database of logs I have. Where can I learn more about the infrastructure aspects? I think I can use most of the tools on their own, but plugging them into each other seems to be an art of its own.
Are there any public examples/use cases etc available? I understand that the individual pipelines strongly depend on the use case and the user, but just examples will probably be very useful to me.