as said in here there are some overlap between UIMA and spark in distribution infrastructures. I was planning to use UIMA with spark. (now i am moving to UIMAFit) Can any one tell me what are the problems we really face when we develop uima with spark. And what are the possible encounters. (Sorry I haven't done any research on this.)
The main problem is accessing objects because UIMA tries to re instantiate objects when running their analyse engines. if the objects has local references then there will be a problem with accessing from a remote spark cluster. some RDD functions might not work within UIMA context. however if you don't use a separate remote cluster then there won't be a problem. (I am talking about uima-fit 2.2)