> In this example, let's say that we somehow had enough storage to keep the data we want to query in 1986. The next part would be to marshall on the order of 1

> In this example, let's say that we somehow had enough storage to keep the data we want to query in 1986. The next part would be to marshall on the order of 1 CPU-year worth of resources and have the query complete in minutes. As with > the storage problem, this would have also been absurd in [1986], so we've run into a second piece of non-essential complexity so large that it would stop a person from 1986 from thinking of this problem at all.* If you are given a bucket to drain a lake, the enormity of task at hand is not "accidental complexity". OP is asserting that doing x one time or a billion times is still x, with an inherent complexity of using a bucket to (dip, draw, transfer, drain). This is true -only- if we willfully insist on ignoring that our 'conceptual model' (a reservoire, a bucket, and a worker) is intimately bound with available technology and is a leaky abstraction. The actual conceptual [model] (move liquid from one reservoire to another) says very little about "inherent complexity". (Can you point it out?) It seems it is more accurate to note that the complexity of materializing abstractions tends to increase with scale of operations. Our goal then, as a discipline, should be to insure this relationship approaches linear [or better] to the extent possible. Continuing the example, the actual task (drain a lake) could materialize as an army of workers, each with a bucket, all converging on a sink to drain their bucket. Is managing the workers really an "accidental" complexity? What above then implies is that the notion of "essential complexity" is a faulty paradigm if considered to be a static measure indepdendent of du jour technology. The essential complexity of a task is held to be inherently related to the magnitude of task, and thus inherently addressable by, and related to, advancements in technology. And finally, since nearly all of the modern software systems are merely a scaled up ("web scale") version of earlier, "less complex", systems, it seems reasonable to question the industry's singular obsession with languages as the remedy to what is inherently a problem of scaling well understood tasks.