  Distributed data processing systems have advanced through models that expose
more and more opportunities for concurrency within a computation. The
scheduling of these increasingly sophisticated models has become the bottleneck
for improved throughput and reduced latency.
  We present a new coordination primitive for dataflow systems, the timestamp
token, which minimizes the volume of information shared between the computation
and host system, without surrendering precision about concurrency. Several
projects have now used timestamp tokens, and were able to explore computational
idioms that could not be expressed easily, if at all, in other platforms.
Importantly, these projects did not need to design and implement whole systems
to support their research.
