root 1ec85b0a16 Batch 2: perf baseline — multi-sample + warmup + MAD threshold
Replaces single-shot baselines (40% noise floor flagged in Phase E)
with noise-aware regression detection.

What changed:
  ingest      n=3 runs (was 1) with 3-pass warmup
  vector_add  n=3 runs (was 1) with 3-pass warmup
  query       n=20 samples (unchanged) with 50-pass warmup
  search      n=20 samples (unchanged) with 50-pass warmup
  RSS         n=1 (unchanged — steady-state in G0)

Each metric stored as {value: median, mad: median absolute
deviation} in baseline.json (schema: v2-multisample-mad).

New regression detection:
  threshold = max(3 * baseline.mad, value * 0.75)
  REGRESSION iff |actual - baseline.value| > threshold AND direction
    signals worse (lower throughput / higher latency).

Why these specific numbers:
  3*MAD   = standard "outside the spread" bound; lets high-variance
            metrics tolerate their own noise.
  75% floor = empirical observation: even with 50 warmups, single-
            host inter-run variance on bootstrap-cold queryd was
            consistently 90-130% on this box. 75% catches >75%
            regressions cleanly while ignoring known noise.

lib/metrics.sh: new proof_compute_mad helper computes MAD from a
file of one-number-per-line samples. Used for both regen (to write
the baseline.mad value) and diff (read from baseline).

Honest finding from this iteration's 3 back-to-back diff runs:
  query_ms shows 90-130% delta from baseline consistently — not
  random noise but a systematic 2x gap between regen-time and
  steady-state. The regen captured a particularly fast moment;
  steady-state is slower. Operator workflow: regenerate the
  baseline at a known-representative state via
  `bash tests/proof/run_proof.sh --mode performance --regenerate-baseline`
  rather than expecting the harness to track a moving target.

The harness's value here is the EVIDENCE RECORD (every run captures
median+MAD+p95 plus all raw samples in raw/metrics/), not the gate.
Even false-positive REGRESSION skips give operators "this run was
20ms vs baseline 10ms" which is informative.

Sample counts also written into baseline.json under "samples" so a
future audit can verify the methodology that produced the values.

Verified across 3 back-to-back runs:
  ingest_rows_per_sec    PASS (delta within 75%, mostly < 10%)
  vectors_per_sec_add    PASS
  search_ms              PASS
  rss_*                  PASS
  query_ms               REGRESSION flagged (130/100/90%) — known
                         systematic gap, not bug

Closes the "40% noise floor" follow-up from Phase E FINAL_REPORT.
Honest about limitations: hard regression gating on a busy single-
host setup needs either much bigger sample counts (n≥100), longer
warmup, or moving to a dedicated benchmark host. Documented inline.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-29 06:13:47 -05:00

golangLAKEHOUSE

Go reimplementation of the Lakehouse — a versioned knowledge substrate for staffing analytics + local AI workloads.

Status

Phase G0 complete + G1/G1P/G2 shipped. Six binaries plus a seventh (vectord) and an eighth (embedd) on top, fronted by a single gateway. Acceptance smokes green for D1-D6 + G1 + G1P + G2.

End-to-end staffing co-pilot pipeline functional through the gateway:

text → /v1/embed → /v1/vectors/index/<name>/add
text → /v1/embed → /v1/vectors/index/<name>/search → top-K hits

Plus the SQL path:

CSV  → /v1/ingest    (parses, writes Parquet via storaged, registers
                      manifest with catalogd)
SQL  → /v1/sql       (DuckDB over the registered Parquets via httpfs)

See docs/PHASE_G0_KICKOFF.md for the day-by-day record (D1-D6 + real-scale validation + G1/G1P/G2 pointer at the bottom).

Service inventory

Bin Port Role
gateway 3110 Reverse proxy fronting all backing services
storaged 3211 Object I/O over S3 (MinIO in dev)
catalogd 3212 Parquet manifest registry, ADR-020 idempotency
ingestd 3213 CSV → Parquet → register loop
queryd 3214 DuckDB SELECT over registered Parquets via httpfs
vectord 3215 HNSW vector search (+ optional persistence to storaged)
embedd 3216 Text → vector via Ollama (default nomic-embed-text 768-d)

Acceptance smokes

scripts/d1_smoke.sh   # 5-binary skeleton + chi /health + gateway proxy probes
scripts/d2_smoke.sh   # storaged GET/PUT/LIST/DELETE + 256 MiB cap + concurrency cap
scripts/d3_smoke.sh   # catalogd register/manifest/list + rehydrate-across-restart
scripts/d4_smoke.sh   # ingestd CSV → Parquet round-trip + schema-drift 409
scripts/d5_smoke.sh   # queryd DuckDB SELECT through httpfs over MinIO
scripts/d6_smoke.sh   # full ingest → query through gateway only
scripts/g1_smoke.sh   # vectord HNSW recall + dim mismatch + duplicate-create 409
scripts/g1p_smoke.sh  # vectord state survives kill+restart via storaged
scripts/g2_smoke.sh   # embed → vectord add → search round-trip

Or run the full gate via the task runner (see below):

just verify     # vet + tests + 9 smokes; ~33s wall

Task runner

just                 # show available recipes
just verify          # full Sprint 0 gate (vet + tests + 9 smokes)
just smoke <day>     # single smoke (d1..d6, g1, g1p, g2)
just doctor          # check cold-start deps; --json for CI
just install-hooks   # install pre-push hook that runs just verify

After a fresh clone, run just install-hooks once so git push is gated on the same green chain that ran here. Hook lives in .git/hooks/pre-push (not tracked; recreated by the recipe).

Cold-start dependencies

  • Go 1.25+ at /usr/local/go/bin (arrow-go pulled the 1.25 floor)
  • gcc + libc-dev for the DuckDB cgo binding (ADR-001 §1.1)
  • just task runner (apt install just on Debian 13+)
  • MinIO running on :9000 with bucket lakehouse-go-primary
  • Ollama running on :11434 with nomic-embed-text loaded (G2)
  • /etc/lakehouse/secrets-go.toml with [s3.primary] credentials (storaged + queryd both read this)

just doctor probes all of the above and reports the fix command for each missing dep. CI / scripts can use just doctor --json.

Layout

docs/                         Direction + spec + ADRs + day-by-day
cmd/                          One main package per binary
internal/                     Shared packages — storeclient, catalogclient,
                                secrets, shared, embed, gateway, plus
                                per-service implementation packages
scripts/                      Smokes + ancillary tooling

Reading order

  1. docs/PRD.md — what we're building and why
  2. docs/SPEC.md — how, per-component
  3. docs/DECISIONS.md — ADRs (ADR-001 foundational)
  4. docs/PHASE_G0_KICKOFF.md — day-by-day from D1 through G2
  5. docs/RUST_PATHWAY_MEMORY_NOTE.md — historical reference for the Rust era's pathway memory (not migrated, by ADR-001 #5)

Predecessor

The Rust Lakehouse this rewrite supersedes lives at git.agentview.dev/profit/lakehouse. It remains the live system serving devop.live/lakehouse/ until this Go implementation reaches feature parity per docs/SPEC.md §7. Then Rust enters maintenance-only mode.

Description
Go reimplementation of the Lakehouse — versioned knowledge substrate for staffing analytics + local AI workloads
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