I'm developing a back-end application for a search system. The search system copies files to a temporary directory and gives them random names. Then it passes the temporary files' names to my application. My application must process each file within a limited period of time, otherwise it is shut down – that's a watchdog-like security measure. Processing files is likely to take long so I need to design the application capable of handling this scenario. If my application gets shut down next time the search system wants to index the same file it will likely give it a different temporary name.
The obvious solution is to provide an intermediate layer between the search system and the backend. It will queue the request to the backend and wait for the result to arrive. If the request times out in the intermediate layer – no problem, the backend will continue working, only the intermediate layer is restarted and it can retrieve the result from the backend when the request is later repeated by the search system.
The problem is how to identify the files. Their names change randomly. I intend to use a hash function like MD5 to hash the file contents. I'm well aware of the birthday paradox and used an estimation from the linked article to compute the probability. If I assume I have no more than 100 000 files the probability of two files having the same MD5 (128 bit) is about 1,47×10-29.
Should I care of such collision probability or just assume that equal hash values mean equal file contents?