Iterative macros are very powerful tools in your arsenal when properly understood. The True/False setup is a common limitation artificially imposed upon Iterative macros. You can build an iterative macro in that way, but they can do much more).
In the broadest sense, an iterative macro is defined by 3 things:
- Iteration Input
- Iteration Output
- The Workflow in-between
They work by first running the workflow (#3) for your starting data (what you connect to the input anchor/(s) of the macro) just like a standard macro, and then everything that is output to the Iteration Output (#2) gets sent back through the Iteration Input (#1) to start the process over again. This is done until the Iteration Output receives no data (i.e. 0 records) or your macro reaches the maximum number of iterations (that you've defined). Finally, output from each iteration are Union-ed together to provide the dataset in each of your defined output anchors
That's it. You can generate other outputs based on your requirements, but as long as those 3 things are implemented, your macro will work. The tricky part is coming up with the most efficient way to step through your data in an iterative way so that you achieve the empty Iteration Output before the workflow iteration maximum while also tagging relevant information for your other outputs (like the Group # in your case). This allows the following structures to be implemented:
- True/False logic you mentioned
- Map Traversal (basically a Breadth First Search algorithms): This is what I used for your particular use case. Your Iteration Input/Output are a single "time step" and every iteration references a secondary "Map" input, which is static (i.e. does not change) and contains all information about how records are interconnected to determine what the next value should be.
- On/Off logic: similar to True/False except instead of referencing each record individually, you perform a secondary operation and either send all records to Iteration Output or no records to Iteration Output depending on the outcome of the secondary operation (The times I have used this model, usually reference a Join Tool Output, Count Records, Append to main dataset, Filter all records if [Count] > 0 (Just remember to remove the [Count] column via Select Tool right before the Iteration Output)
- etc.
There are many other forms and use cases for the iterative macro, and often the planning stage takes more effort than the building of the workflow. In your case the iterative macro is initialized with all Task ID's that have no associated prior tasks (adding Group and Item fields for tracking purposes). Additionally, the "map" table with all Task associations is passed in for static referencing (I filtered out the starting tasks, but did not need to).
Our Iteration Input thus contains a list of unrelated independent task ID's, and our "iteration" goal is to gather the next associated task ID's, which can be found by joining to the "map" table. Everything that doesn't join in a single iteration is irrelevant in that iteration (because it was either already handled or will be later on). The only exception would be a task record with a bad reference (a record with a prior Task ID that does not exist in the dataset).
Hope this helps and Happy Solving!
