docs(submitqueue): [DO NOT REVIEW][DO NOT LAND] Tango conflict research - #763
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… distribution Redo the Tango conflict-analysis research against the observed per-request affected-target histogram instead of fixed N/2N/5N workloads, and answer where each signature design stops working as in-flight batches grow. - Benchmark: draw each batch's size from the Hive histogram (one batch = one request), build closure-shaped affected sets on the full go-code graph, and give TangoSnapshot real direct dependencies. Run B = 100..10,000 and extend to 100,000 with a per-target Monte Carlo scale model that reports the first B exceeding illustrative latency/heap budgets, under object-store and KV point-read profiles. - Base drift: simulate signatures computed once against the newest base. Show that affected-set overlap misses conflicts, that new-edge destinations (the production SubmitQueue rule) reduce but do not remove misses, and that inheriting structural dependencies' signatures removes them at a cost in false conflicts. - Report: rewrite the RFC around the cold-controller worst case with TangoSnapshot as the baseline, a design vocabulary, units in every table header and an interpretation under each result table; document the ID dictionary's role in conflict relaxation and prior art; drop superseded sections, artifacts, the posting-index and cold-scan modes, and the root-level summary file. - Fix per-batch decode timing truncation to whole microseconds. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
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Summary
DRAFT RESEARCH ONLY — DO NOT REVIEW; DO NOT LAND. Leave this PR in draft. Do not request reviewers, mark it ready for review, or enable automatic merging. This branch contains a Go evaluator and a documented Tango/SubmitQueue conflict-analysis proposal; it does not deploy an analyzer.
Report:
doc/rfc/submitqueue/tango-conflict-analysis.md. The earlier HTML report (https://personal.uberinternal.com/sergeyb/submitqueue-tango-conflict-analysis/index.html) reflects the superseded fixed-N workload and has not been updated.Why?
A Tango-backed conflict analyzer stores a target signature per batch and compares each new batch against every in-flight batch. This research estimates, for a cold controller that must fetch and decode all
Bsignatures, at what number of in-flight batches each signature design stops working because of size, materialization time or latency. go-code runs fewer than 100 in-flight batches today; the goal is to pick a design that scales.What?
goqueue from Hive (58,876 requests; median 42, mean 2,527, max 2.88M). One batch is modeled as one request.Bexceeding example latency and heap budgets, under object-store and KV point-read profiles.B. NameKey holds to low thousands. ID64 is limited by round trips rather than bytes, so the choice of store matters more than the encoding.Test Plan
go test ./tool/tangograph-evaland./tool/bazel test //tool/tangograph-eval/....make check-gazelle && make check-tidy.Revert Plan
Close this draft PR without merging. If it is ever merged contrary to this instruction, revert the research commits; they add only documentation and a standalone evaluator, not service behavior.
Issue Links
None — exploratory research requested directly; no tracking issue was provided.
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