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Design, prior art and a measurement protocol for a weighted inverted index over a mixed sparse basis and part-level routing before per-part HNSW in a ClickHouse-derived store. Each component is marked prior art or proposed. The protocol fits C(N) = aN^alpha to parts, granules and bytes touched per correct answer at a held recall. No numbers: every results cell is a placeholder read from results-data.tex until the baseline lane writes it. Co-authored-by: Hanzo Dev <[email protected]>
50 lines
2.7 KiB
TeX
50 lines
2.7 KiB
TeX
\section{Limitations}
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\label{sec:limits}
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\textbf{Nothing here is measured.} The design has not been built at the scale
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it is argued for, and the protocol in \S\ref{sec:method} has produced no
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numbers. Every statement about cost in this paper is a statement about what a
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bound permits, not about what a machine did.
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\textbf{The per-type calibration is unsolved.} A single score over a mixed
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basis needs weights $w_t$ that put an entity linker's confidence and a lexical
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impact on one scale. Learning them requires relevance judgements over the
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mixture, which the lane does not yet have; until it does, any reported
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effectiveness is the effectiveness of a hand-set combination, and should be
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read as such.
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\textbf{Bounds loosen with dimension, and that is not fixable by tuning.}
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Covering radii stop separating regions in high intrinsic dimension, so the
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exact routing rule can degenerate to a full visit; the approximate rule then
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carries the load and converts a cost problem into a recall problem. The
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protocol measures where that transition happens for a given corpus, but no
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choice of region size avoids it.
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\textbf{The routing metadata is itself a cost that grows.} The number of region
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summaries is proportional to the number of regions, so a design that scanned
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them all would be linear in the corpus with a small constant. The tree over
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part summaries is what keeps that term sublinear, and its depth, fan-out and
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maintenance cost during merges are unmeasured.
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\textbf{Merge-time maintenance is a write-side cost we do not price.} Carrying
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posting lists, block maxima and region summaries through a merge is work that
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competes with ingestion. A design that makes reads cheap and merges expensive
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can be a net loss for a table that is written more often than it is queried.
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\textbf{The claim is about a query distribution.} An exponent fitted under one
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distribution says nothing about another. The strata in \S\ref{sec:method} are
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there so a reader can see which queries the average is made of, but the
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protocol cannot certify that a deployment's queries resemble the set measured.
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\textbf{Exactness is relative to the per-part search.} The routing rule is
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exact given the region bounds, but the dense leg inside a part is an
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approximate graph search, so the system's answer is exact only with respect to
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what that search returns. Conflating the two would make a recall failure look
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like a routing success.
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\textbf{The largest sizes are not yet reachable.} A corpus of $10^9$ rows with
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dense vectors and a mixed sparse basis needs hardware the lane has not yet been
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given, the first pass stops two decades below it, and the collection it samples
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holds $3.5 \times 10^7$ rows. A fit over the sizes actually run is a fit over
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those sizes.
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