Each combinator knows how to produce the output diff from an input diff; the computation is then just a matter of stringing these combinators together.

For example, consider a map combinator. The output diff is just the input diff with a function applied to the data. More formally, for every incoming (data, time, diff) triple, an output triple (f(data), time, diff) is produced.

For a filter combinator, the output is (data, time, diff) if f(data) is true, or (data, time, 0) if f(data) is false.

A computation that wants to filter and map some data then just requires piping together these operators.

Things get interesting when you want to aggregate and join data, but Frank’s blog posts and documentation explain how you build that in a dataflow system far better than I can here.