Concept

Query distribution — where it appears

The pattern of where a system's queries start and end, as distinct from the structure they run over. A preparation fitted to it — landmarks chosen from a log of past queries — beats one fitted to the map only while the traffic stays where the log saw it.

Named by 2 essays across one field — each of them below, with the objects they name alongside it.

125102050100200100observed queries the selection sawcells expanded, meanon fresh querieson the sample it was chosen fromthe cornersfarthest-first8 maps × 150 fresh queriesflat lines read no queries

What the queries know that the map does not

A greedy rule that chooses landmark cells by rerunning a sample of past queries needs two hundred of them to draw level with a rule that reads only the map — and what it finally chooses, on map after map, is the four corners. Give the queries a destination instead of scattering them, and twenty are enough to beat the corners by 29% on eight maps out of eight. A query log is worth reading exactly to the extent that it is not uniform.

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0.50011.5020102030cells the destination moved from the one the landmarks were fitted tocells expanded, fitted placement ÷ cornersthe corners0/87/4811/4825/4832/4834/4841/4842/48digits: cases worsethan the corners8 maps, 6 directions a distancebelow one the fit is still worth having

A placement after the traffic moved

Four landmarks fitted to twenty queries that all end at one cell expand two thirds of the corners' cells there. Move the destination ten cells and the advantage is gone; move it thirty and the fitted placement expands nearly twice the corners' cells. Choosing again costs 317,000 cells of search — the saving of 8,600 queries — so on streams whose destination drifts, a policy that refits on a counter never beats fitting once and keeping the result, and past a drift of about ten cells nothing fitted beats the corners.

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Named alongside it

The objects these essays reach for when they reach for this one.

Break-evenHeuristic searchLandmarkOverfittingParameter choicePreprocessingSamplingShortest pathGreedy algorithmHonest limitMeasurement designPotential function

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