Lets say you have three numbers, a, b, c, and you want to add them together to get the total. Then later, "c" changes, and you'd like to re-compute the total. One option would be to re-run the full sum, a + b + c, which would be fine. However, that repeats the "a + b" calculation.
Would it be possible to improve the efficiency of the total calculation by re-using the pre-computed "a + b" if only "c" changes?
Differential dataflow is one way to do that, but only really applies if you have lots of data with complex calculations. For analytics, maybe the "a + b" calculation would cover your last 5 years of operations, and then when a new day's worth of data comes in, you just compute the changes to the totals, rather than re-computing the analytics for all those years, all without manually having to write distinct "total" and "update" code.
Would it be possible to improve the efficiency of the total calculation by re-using the pre-computed "a + b" if only "c" changes?
Differential dataflow is one way to do that, but only really applies if you have lots of data with complex calculations. For analytics, maybe the "a + b" calculation would cover your last 5 years of operations, and then when a new day's worth of data comes in, you just compute the changes to the totals, rather than re-computing the analytics for all those years, all without manually having to write distinct "total" and "update" code.