e4b430f69c
For continuous optimization we need to attribute slow/failed decodes to the right cause. query_logs.timings jsonb is now a structured decode-meta blob, not just stage timings: - wmi: first 3 chars of VIN (per-brand aggregation) - result_kind: vehicle / pcat_candidates / emex_candidates / unknown / aborted - cache_source: db_hit / redis_positive / redis_negative / lock_wait / miss - candidate_pick: pcat / emex / none (when user picks from candidate modal) - pcat_car_count, emex_candidate_count (cardinality, drives candidate-modal rate) - pl24_circuit_open, pl24_skipped (CB state at request time) - vin_api_used, vin_api timing (NHTSA fallback frequency) Migration 0003 adds a query_log_insights VIEW that flattens these keys into typed columns, so ad-hoc SQL doesn't need json operators. New meta keys appear automatically as NULL; the VIEW stays stable. docs/analytics-queries.sql has 8 starter queries: cache hit ratio, per-source latency, slowest WMIs, stage breakdowns, CB/abort frequency, candidate-modal rate, top failing VINs, dedup effectiveness. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
34 lines
647 B
JSON
34 lines
647 B
JSON
{
|
|
"version": "7",
|
|
"dialect": "postgresql",
|
|
"entries": [
|
|
{
|
|
"idx": 0,
|
|
"version": "7",
|
|
"when": 1778535325959,
|
|
"tag": "0000_brief_guardian",
|
|
"breakpoints": true
|
|
},
|
|
{
|
|
"idx": 1,
|
|
"version": "7",
|
|
"when": 1747039600000,
|
|
"tag": "0001_charming_quicksand",
|
|
"breakpoints": true
|
|
},
|
|
{
|
|
"idx": 2,
|
|
"version": "7",
|
|
"when": 1778584574615,
|
|
"tag": "0002_boring_the_stranger",
|
|
"breakpoints": true
|
|
},
|
|
{
|
|
"idx": 3,
|
|
"version": "7",
|
|
"when": 1778587000000,
|
|
"tag": "0003_query_log_insights",
|
|
"breakpoints": true
|
|
}
|
|
]
|
|
} |