> Right. But that seems fraught with difficulty. I suspect that the
> costs that the planner attributes to each plan often aren't very
> reliable in any absolute sense, even when everything is working very
> well by every available metric. Even a very noisy cost model with
> somewhat inaccurate selectivity estimates will often pick the cheapest
> plan, or close enough.
Sure, the absolute cost of a complex plan will always be inaccurate at best.
My point is that we can be very confident in the cardinalities of base tables. As the paper states in "3.1. Estimates
forBase Tables":
"The median q-error is close to the optimal value of 1 for all systems,
indicating that the majority of all selections are estimated correctly."
Thanks to the statistics will practically never be off by an order of magnitude when estimating base table
cardinalities.
The paper also clearly shows (and that certainly coincides with my experience) that those cardinality underestimations
growexponentially as they propagate up the join tree.
Given the research I'd stipulate that at any given level of the join tree, the current depth is a reasonable indicator
ofunderestimation. Taking that into account (even if only to mitigate nested loops on higher levels) is IMV a
principledapproach, and not necesseraly a hack.
Obviously having something like error bars as proposed by Tom would be even better and perhaps more general, but that
ison a whole different level in terms of complexity and I certainly have no idea how we would easily get there.
