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docs(gfql): SNB section renders the SF0.1 GFQL arms re-measured with index-resolved seeds
Vendors pyg-bench published/docs-numbers.json at main 5cf81ae (byte-identical): the SF0.1 indexed GFQL cells come from the #2038 head with the pre-landing disclosure, SF1 stays the release measurement. The SNB prose states the native op-list arm, where the resident indexes now engage, the hop rows they do not change, and the open issues behind the remaining gaps. Release-notes Performance paragraph names the native seed resolution and the sentinel's native op-list points. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_014RhboAkmjP5eXbCCkX1BMt
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* GFQL: the wavefront seed-rediscovery rule moved out of `hop.py` into `graphistry/compute/gfql/seed_rediscovery.py` (pandas/cuDF) and `graphistry/compute/gfql/lazy/engine/polars/seed_rediscovery.py` (polars); `undirected_rediscovered_seed_ids` (an internal helper) is gone.
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### Performance
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* GFQL latency: this release closes a set of point-lookup regressions found while re-measuring the LDBC SNB Interactive shapes, and adds the gates that stop them coming back. Regressions fixed: every Cypher string query on a wide pandas node table re-scanned the object columns to key the compile cache (#2029); an undirected multi-hop paid a per-edge Python loop in the seed-rediscovery rule (#2023) and a whole-frame dedup of the doubled edge frame on pandas and cuDF; the LDBC IS1 form (a seeded hop returning properties of both aliases) and the seeded single-node lookup ran the full chain with no index consulted. Gates added: `test_gfql_latency_contract.py` (fast path served plus a bounded ratio to plain frame ops for the basic shapes on pandas, polars and cuDF), `test_hop_scaling_pin.py` (undirected 2-hop cost bounded relative to two plain joins), and, in the private benchmark repository, a point-latency sentinel on the real SF0.1 fixture with absolute sub-10 ms thresholds that runs on every release candidate before the documentation numbers are re-vendored, plus an exporter gate that fails any unexplained slowdown or new loss in the published cells.
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* GFQL latency: this release closes a set of point-lookup regressions found while re-measuring the LDBC SNB Interactive shapes, and adds the gates that stop them coming back. Regressions fixed: every Cypher string query on a wide pandas node table re-scanned the object columns to key the compile cache (#2029); an undirected multi-hop paid a per-edge Python loop in the seed-rediscovery rule (#2023) and a whole-frame dedup of the doubled edge frame on pandas and cuDF; the LDBC IS1 form (a seeded hop returning properties of both aliases) and the seeded single-node lookup ran the full chain with no index consulted; native op-list chains scanned the node table for a seed given on a non-binding property even with a node-property index resident, declined named patterns that the chain fast path could serve, and on polars never consulted the resident seed indexes at all (#2027, #2033; now served through the resident node-id, adjacency and node-property indexes on pandas, cuDF and polars, with the engagement visible in `gfql_explain`). Gates added: `test_gfql_latency_contract.py` (fast path served plus a bounded ratio to plain frame ops for the basic shapes on pandas, polars and cuDF), `test_hop_scaling_pin.py` (undirected 2-hop cost bounded relative to two plain joins), and, in the private benchmark repository, a point-latency sentinel on the real SF0.1 fixture with absolute sub-10 ms thresholds that runs on every release candidate before the documentation numbers are re-vendored, plus an exporter gate that fails any unexplained slowdown or new loss in the published cells. The sentinel also times native op-list twins of the same shapes with untimed receipts of the route that served them and value parity with the full path, so a fast path that stops engaging is reported rather than hidden behind a still-correct answer.
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### Docs
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