TPL Dataflow Starvation Fixed
Great news for all TPL Dataflow developers.
The old bug (more than a year since I reported it) was finally fixed at version 4.5.24.
now it is safe to use fallback scenario with TPL Dataflow.
for example: if you’re having 2 face recognition algorithm:
* excellent but slow
* fine and fast
and you want to use those algorithm on a video streams without getting to much
behind. You can limit the Bounded Capacity of the excellent algorithm’s block,
link the two algorithm’s blocks to a buffer block.
As long as the excellent algorithm stand the pace you will have the best recognition
but when it start to get behind, it will reach the bounded capacity and the fast algorithm
will start to process messages until the excellent algorithm will get below the bounded capacity.
the code will look something like:
I was waiting for this fix for a long time and I got fixed right on time because I really
need it now in at one of mine customers.