I am trying to come up with a formula or machine learning algorithm using which I can approximately predict the weekly or monthly users.
What to keep in mind is that I already have counts for the unique visitors per day for the week/months that I would like to make a near accurate prediction. Here, simply summing the daily unique users would not work, as they can be unique on one day but not on two days as they can have a session lasting over 2 days.
This method is to serve as an alternative to running a Spark job on the whole week/month data in order to save time and resources - Is this possible?
I have looked at Time Series and Linear Regression, but need more clarification on the possible approaches and also on any work-arounds?