sure, I certainly see the appeal of the absolute values approach – like I said, it's a design tradeoff.
however, one point of DRF is that we can sensibly consider "fractions" of multidimensional resource vectors since the "fraction" is defined as the fraction of the cluster consumed by the most dominant resource. having single-dimensional fractions like this is nice because we can then a) weight them, and b) calculate max-min fairness as in the one-dimensional case (eg, memory) case.
consider the history and geology departments you introduced above. let's say our policy is that each queue gets equal weight (since the the departments went in on the purchase of the cluster 50/50), and that each queue should be guaranteed a minimum of 1/4 of the cluster (so that a queue fresh with jobs ramps-up to 1/4 of the cluster quickly).
in your proposal, since the departments have different shaped demands (one for high-memory, the other for high-cpu), we would configure their minimum share vectors based on these different shaped demands. this would work fine as long as the departments continued to submit resource requests which had these same, pre-configured shapes.
however, if we establish the minimums using fractions, then the departments can easily change between different shaped jobs, and still have the minimums work out for them sensibly. does this make sense?
let's be concrete:
10 nodes with 8 CPUs and 64 GB of RAM
if history usually submits jobs for (1 CPU, 16 GB) and geology for (2 CPU, 8 GB). with your proposal, we might define history's minimum allocation to be (10 CPU, 160 GB) (1/4 of the dominant resource) and geology to be (20 CPU, 80 GB) (again, 1/4 of dominant resource). if either department changed the shape of their requests, they wouldn't get full use of their minimum.
so, what if we listed the minimums as simply 1/4 * cluster size, but not considering DRF? ie, giving (20 CPU and 160 GB) as the minimum allocation to each? well, if the departments continued to submit the different shaped jobs (1 CPU, 16 GB) and (2 CPU, 8 GB), the design described would continue to see the queues as being below their "minimum allocation", even after the bottleneck resource fully consumed its amount of the minimum allocation. in the extreme case, I highly suspect a job could get more than its DRF-based fair share, simply by having one of its non-dominant resources remain below the amount listed in its minimum share. (can you see this? if not, I'll work out an example)
the beauty of the fractions approach, in my mind, is that it will apply no matter which resource is the bottleneck resource.
hope this example is clear. sorry I haven't had time to look at your code – this is just based on my reading of your design doc. perhaps all is well and good in the code itself.