htlee
37ae1bfa48
scheduler.py features write 확장: - pair_tier (STRONG/PROBABLE/SUSPECT) - pair_type, pair_reject_reason - similarity, confidence - registered_fishery_code → SUSPECT tier 까지 raw_pair 로 보존하여 통계 집계 가능 diagnostic-snapshot.sh (5분 주기): - 4-4.1 pair_trawl tier 분포 + avg_sync_min - 4-4.2 reject 사유 journal 로그 tail - 4-4.3 G-02 금어기 상세 (observed_at, fishery_code) - 4-4.4 G-03 미등록 어구 상세 (detected/registered/allowed) - 7.5-2b match_method 분포 (EXACT vs FUZZY) - 7.5-2c fishery_code × match_method 교차 hourly-analysis-snapshot.sh (1시간 주기): - P3.5 match_method 분포 + avg_confidence - P3.6 fishery_code × match_method 교차 - D3.6 pair_tier 분포 + avg_sync_min + avg_sep_nm - D3.7 G-02/G-03 건수 + gear_judgment 분포 - D3.8 reject 사유 1시간 journal 집계
465 lines
18 KiB
Bash
465 lines
18 KiB
Bash
#!/bin/bash
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# prediction 알고리즘 진단 스냅샷 수집기 (5분 주기, 수동 종료까지 연속 실행)
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#
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# 용도: DAR-03 G코드 + 쌍끌이 + 어구 위반 포함 알고리즘 동작 검증
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# 실행: nohup bash /home/apps/kcg-ai-prediction/scripts/diagnostic-snapshot.sh &
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# 종료: kill $(cat /home/apps/kcg-ai-prediction/data/diag/diag.pid)
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# 출력: /home/apps/kcg-ai-prediction/data/diag/YYYYMMDD-HHMM.txt
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set -u
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OUTDIR=/home/apps/kcg-ai-prediction/data/diag
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mkdir -p "$OUTDIR"
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echo $$ > "$OUTDIR/diag.pid"
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export PGPASSWORD=Kcg2026ai
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PSQL="psql -U kcg-app -d kcgaidb -h 211.208.115.83 -P pager=off -x"
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PSQL_TABLE="psql -U kcg-app -d kcgaidb -h 211.208.115.83 -P pager=off"
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INTERVAL_SEC=300 # 5분
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while true; do
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STAMP=$(date '+%Y%m%d-%H%M')
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OUT="$OUTDIR/$STAMP.txt"
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{
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echo "###################################################################"
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echo "# PREDICTION DIAGNOSTIC SNAPSHOT (DAR-03 enhanced)"
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echo "# generated: $(date '+%Y-%m-%d %H:%M:%S %Z')"
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echo "# host: $(hostname)"
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echo "# interval: ${INTERVAL_SEC}s"
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echo "###################################################################"
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#===================================================================
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# PART 1: 종합 지표
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 1: 종합 지표 (last 5min)"
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echo "================================================================="
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$PSQL_TABLE << 'SQL'
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SELECT count(*) total,
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count(*) FILTER (WHERE vessel_type != 'UNKNOWN') pipeline,
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count(*) FILTER (WHERE vessel_type = 'UNKNOWN') lightweight,
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count(*) FILTER (WHERE is_dark) dark,
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count(*) FILTER (WHERE transship_suspect) transship,
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count(*) FILTER (WHERE gear_judgment IS NOT NULL AND gear_judgment != '') gear_violation,
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count(*) FILTER (WHERE risk_level='CRITICAL') crit,
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count(*) FILTER (WHERE risk_level='HIGH') high,
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round(avg(risk_score)::numeric, 1) avg_risk,
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max(risk_score) max_risk,
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round(count(*) FILTER (WHERE is_dark)::numeric / NULLIF(count(*), 0) * 100, 1) AS dark_pct
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes';
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SQL
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#===================================================================
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# PART 2: 다크베셀 심층 진단
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 2: DARK VESSEL 심층 진단"
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echo "================================================================="
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echo ""
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echo "--- 2-1. dark_suspicion_score 히스토그램 ---"
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$PSQL_TABLE << 'SQL'
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SELECT CASE
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WHEN (features->>'dark_suspicion_score')::int >= 90 THEN 'a_90-100 (CRITICAL_HIGH)'
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WHEN (features->>'dark_suspicion_score')::int >= 70 THEN 'b_70-89 (CRITICAL)'
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WHEN (features->>'dark_suspicion_score')::int >= 50 THEN 'c_50-69 (HIGH)'
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WHEN (features->>'dark_suspicion_score')::int >= 30 THEN 'd_30-49 (WATCH)'
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WHEN (features->>'dark_suspicion_score')::int >= 1 THEN 'e_1-29 (NONE_SCORED)'
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ELSE 'f_0 (NOT_DARK)'
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END bucket,
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count(*) cnt,
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round(avg(gap_duration_min)::numeric, 0) avg_gap_min,
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round(avg(risk_score)::numeric, 1) avg_risk
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND is_dark = true
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GROUP BY bucket ORDER BY bucket;
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SQL
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echo ""
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echo "--- 2-2. dark_patterns 발동 빈도 ---"
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$PSQL_TABLE << 'SQL'
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SELECT pattern,
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count(*) cnt,
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round(count(*)::numeric / NULLIF((SELECT count(*) FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes' AND is_dark), 0) * 100, 1) AS pct
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FROM kcg.vessel_analysis_results,
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LATERAL jsonb_array_elements_text(features->'dark_patterns') AS pattern
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WHERE analyzed_at > now() - interval '5 minutes'
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AND is_dark = true
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GROUP BY pattern ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 2-3. P9/P10/P11 + coverage 요약 ---"
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$PSQL_TABLE << 'SQL'
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WITH dark AS (
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SELECT features FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes' AND is_dark = true
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)
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SELECT count(*) total_dark,
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count(*) FILTER (WHERE features->>'dark_patterns' LIKE '%fishing_vessel_dark%'
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OR features->>'dark_patterns' LIKE '%cargo_natural_gap%') p9,
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count(*) FILTER (WHERE features->>'dark_patterns' LIKE '%underway_deliberate_off%'
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OR features->>'dark_patterns' LIKE '%anchored_natural_gap%') p10,
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count(*) FILTER (WHERE features->>'dark_patterns' LIKE '%heading_cog_mismatch%') p11,
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count(*) FILTER (WHERE features->>'dark_patterns' LIKE '%out_of_coverage%') coverage
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FROM dark;
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SQL
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echo ""
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echo "--- 2-4. CRITICAL dark 상위 10건 ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, gap_duration_min, zone_code, activity_state,
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(features->>'dark_suspicion_score')::int AS score,
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features->>'dark_tier' AS tier,
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features->>'dark_patterns' AS patterns,
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risk_score, risk_level
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'dark_tier' = 'CRITICAL'
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ORDER BY (features->>'dark_suspicion_score')::int DESC
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LIMIT 10;
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SQL
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#===================================================================
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# PART 3: 환적 탐지
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 3: TRANSSHIPMENT 진단"
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echo "================================================================="
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$PSQL_TABLE << 'SQL'
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SELECT count(*) suspects,
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count(*) FILTER (WHERE (features->>'transship_score')::numeric >= 70) critical,
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count(*) FILTER (WHERE (features->>'transship_score')::numeric >= 50
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AND (features->>'transship_score')::numeric < 70) high,
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round(avg((features->>'transship_score')::numeric)::numeric, 1) avg_score,
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round(avg(transship_duration_min)::numeric, 0) avg_dur
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes' AND transship_suspect = true;
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SQL
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echo ""
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echo "--- 3-1. 환적 의심 개별 건 ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, transship_pair_mmsi pair, transship_duration_min dur,
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(features->>'transship_score')::numeric score,
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features->>'transship_tier' tier, zone_code
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes' AND transship_suspect = true
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ORDER BY (features->>'transship_score')::numeric DESC;
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SQL
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#===================================================================
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# PART 4: G코드 어구 위반 진단 (DAR-03 신규)
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 4: G코드 어구 위반 진단 (DAR-03)"
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echo "================================================================="
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echo ""
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echo "--- 4-1. gear_judgment 분포 ---"
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$PSQL_TABLE << 'SQL'
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SELECT coalesce(NULLIF(gear_judgment, ''), '(none)') AS judgment,
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count(*) cnt,
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round(avg(risk_score)::numeric, 1) avg_risk
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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GROUP BY judgment ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 4-2. G코드별 발동 빈도 ---"
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$PSQL_TABLE << 'SQL'
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SELECT gcode,
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count(*) cnt,
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round(avg(risk_score)::numeric, 1) avg_risk
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FROM kcg.vessel_analysis_results,
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LATERAL jsonb_array_elements_text(features->'g_codes') AS gcode
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WHERE analyzed_at > now() - interval '5 minutes'
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GROUP BY gcode ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 4-3. G-01 수역-어구 위반 상세 (상위 20건) ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, zone_code, vessel_type, risk_score, gear_judgment,
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(features->>'gear_violation_score')::int AS gv_score,
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(features->'gear_violation_evidence'->'G-01'->>'allowed')::text AS allowed
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'g_codes' LIKE '%G-01%'
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ORDER BY risk_score DESC LIMIT 20;
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SQL
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echo ""
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echo "--- 4-4. G-06 쌍끌이 공조 탐지 (tier 포함) ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, zone_code, vessel_type, risk_score,
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features->>'pair_tier' tier,
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(features->'gear_violation_evidence'->'G-06'->>'sync_duration_min') sync_min,
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(features->'gear_violation_evidence'->'G-06'->>'mean_separation_nm') sep_nm,
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(features->'gear_violation_evidence'->'G-06'->>'pair_mmsi') pair_mmsi,
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features->>'pair_trawl_detected' pt
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND (features->>'pair_trawl_detected' = 'true' OR features->>'g_codes' LIKE '%G-06%')
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ORDER BY risk_score DESC LIMIT 20;
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SQL
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echo ""
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echo "--- 4-4.1 pair_trawl tier 분포 (DAR-03 신호 강도별) ---"
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$PSQL_TABLE << 'SQL'
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SELECT coalesce(features->>'pair_tier', '(none)') tier,
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count(*) cnt,
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round(avg((features->>'similarity')::numeric)::numeric, 3) avg_sim,
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round(avg((features->'gear_violation_evidence'->'G-06'->>'sync_duration_min')::numeric)::numeric, 1) avg_sync_min
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'pair_trawl_detected' = 'true'
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GROUP BY tier ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 4-4.2 pair detection reject 사유 (최근 5분 로그) ---"
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ssh redis-211 "sudo journalctl -u kcg-ai-prediction --no-pager --since '5 minutes ago' | grep -oE 'pair detection:[^$]+reject=\{[^}]+\}' | tail -5" 2>/dev/null || true
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echo ""
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echo "--- 4-4.3 G-02 금어기 조업 탐지 ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, zone_code, vessel_type, risk_score,
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features->>'g_codes' g_codes,
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(features->'gear_violation_evidence'->'G-02'->>'observed_at') observed_at,
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features->>'registered_fishery_code' fishery_code
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'g_codes' LIKE '%G-02%'
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ORDER BY risk_score DESC LIMIT 15;
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SQL
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echo ""
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echo "--- 4-4.4 G-03 미등록/허가외 어구 탐지 ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, zone_code, vessel_type, risk_score,
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features->>'g_codes' g_codes,
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(features->'gear_violation_evidence'->'G-03'->>'detected_gear') detected,
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(features->'gear_violation_evidence'->'G-03'->>'registered_fishery_code') registered,
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(features->'gear_violation_evidence'->'G-03'->>'allowed_gears') allowed
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'g_codes' LIKE '%G-03%'
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ORDER BY risk_score DESC LIMIT 15;
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SQL
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echo ""
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echo "--- 4-5. G-04 MMSI 조작 + G-05 어구 이동 ---"
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$PSQL_TABLE << 'SQL'
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SELECT mmsi, zone_code, vessel_type, risk_score,
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features->>'g_codes' g_codes,
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(features->'gear_violation_evidence'->'G-04'->>'cycling_count') g04_cycle,
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(features->'gear_violation_evidence'->'G-05'->>'drift_nm') g05_drift
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND (features->>'g_codes' LIKE '%G-04%' OR features->>'g_codes' LIKE '%G-05%')
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ORDER BY risk_score DESC LIMIT 10;
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SQL
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echo ""
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echo "--- 4-5.5 pair_type 분포 (DAR-03 base-target 탐색, 5min) ---"
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$PSQL_TABLE << 'SQL'
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SELECT coalesce(features->>'pair_type', '(none)') pair_type,
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count(*) cnt,
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round(avg((features->>'similarity')::numeric)::numeric, 3) avg_sim
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND features->>'pair_trawl_detected' = 'true'
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GROUP BY pair_type ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 4-6. GEAR_ILLEGAL 이벤트 ---"
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$PSQL_TABLE << 'SQL'
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SELECT category, level, title, count(*) cnt
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FROM kcg.prediction_events
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WHERE created_at > now() - interval '5 minutes'
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AND category IN ('GEAR_ILLEGAL', 'MMSI_TAMPERING')
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GROUP BY category, level, title ORDER BY cnt DESC;
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SQL
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echo ""
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echo "--- 4-7. violation_categories ILLEGAL_GEAR ---"
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$PSQL_TABLE << 'SQL'
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SELECT count(*) total,
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count(*) FILTER (WHERE gear_judgment = 'ZONE_VIOLATION') zone_viol,
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count(*) FILTER (WHERE gear_judgment = 'PAIR_TRAWL') pair_trawl,
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count(*) FILTER (WHERE gear_judgment = 'GEAR_MISMATCH') mismatch
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND 'ILLEGAL_GEAR' = ANY(violation_categories);
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SQL
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#===================================================================
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# PART 5: 수역 × 어구 타입 교차 (G-01 검증 핵심)
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 5: 수역 x 어구 타입 교차 (G-01 검증)"
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echo "================================================================="
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$PSQL_TABLE << 'SQL'
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SELECT zone_code, vessel_type, count(*) total,
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count(*) FILTER (WHERE features->>'g_codes' LIKE '%G-01%') g01
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FROM kcg.vessel_analysis_results
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WHERE analyzed_at > now() - interval '5 minutes'
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AND vessel_type != 'UNKNOWN' AND zone_code LIKE 'ZONE_%'
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GROUP BY zone_code, vessel_type ORDER BY zone_code, vessel_type;
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SQL
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#===================================================================
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# PART 6: 이벤트 + KPI
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 6: 이벤트 + KPI"
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echo "================================================================="
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$PSQL_TABLE << 'SQL'
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SELECT category, level, count(*) cnt
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FROM kcg.prediction_events
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WHERE created_at > now() - interval '5 minutes'
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GROUP BY category, level ORDER BY cnt DESC;
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SQL
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$PSQL_TABLE << 'SQL'
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SELECT kpi_key, value, trend, delta_pct, updated_at
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FROM kcg.prediction_kpi_realtime ORDER BY kpi_key;
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SQL
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#===================================================================
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# PART 7: 사이클 로그 + 에러
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 7: 사이클 로그 (최근 6분)"
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echo "================================================================="
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journalctl -u kcg-ai-prediction --since '6 minutes ago' --no-pager 2>/dev/null | \
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grep -E 'analysis cycle:|lightweight|pipeline dark:|event_generator:|pair_trawl|gear_violation|GEAR_ILLEGAL|ERROR|Traceback' | \
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tail -20
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#===================================================================
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# PART 7.5: 한중어업협정 레지스트리 매칭 (V029)
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#===================================================================
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echo ""
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echo "================================================================="
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echo "PART 7.5: FISHERY PERMIT CN REGISTRY 매칭 현황"
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echo "================================================================="
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echo ""
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echo "--- 7.5-1. fleet_vessels 매칭 현황 (현재 연도) ---"
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$PSQL_TABLE << 'SQL'
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SELECT permit_year,
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count(*) total,
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count(mmsi) with_mmsi,
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round(count(mmsi)::numeric / NULLIF(count(*),0) * 100, 1) match_pct
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FROM kcg.fleet_vessels
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WHERE permit_year IS NOT NULL
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GROUP BY permit_year ORDER BY permit_year DESC;
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SQL
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echo ""
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echo "--- 7.5-2. fishery_code 별 매칭률 (현재 연도) ---"
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$PSQL_TABLE << 'SQL'
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SELECT fishery_code, count(*) total, count(mmsi) matched,
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round(count(mmsi)::numeric / NULLIF(count(*),0) * 100, 1) pct
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FROM kcg.fleet_vessels
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WHERE permit_year = EXTRACT(YEAR FROM now())::int
|
||
GROUP BY fishery_code ORDER BY total DESC;
|
||
SQL
|
||
|
||
echo ""
|
||
echo "--- 7.5-2b. match_method 분포 (NAME_EXACT vs NAME_FUZZY) ---"
|
||
$PSQL_TABLE << 'SQL'
|
||
SELECT coalesce(match_method, '(unmatched)') method,
|
||
count(*) cnt,
|
||
round(avg(match_confidence)::numeric, 3) avg_conf
|
||
FROM kcg.fleet_vessels
|
||
WHERE permit_year = EXTRACT(YEAR FROM now())::int
|
||
GROUP BY method ORDER BY cnt DESC;
|
||
SQL
|
||
|
||
echo ""
|
||
echo "--- 7.5-2c. fishery_code × match_method 교차 ---"
|
||
$PSQL_TABLE << 'SQL'
|
||
SELECT fishery_code,
|
||
count(*) FILTER (WHERE match_method = 'NAME_EXACT') exact,
|
||
count(*) FILTER (WHERE match_method = 'NAME_FUZZY') fuzzy,
|
||
count(*) FILTER (WHERE mmsi IS NULL) unmatched,
|
||
count(*) total
|
||
FROM kcg.fleet_vessels
|
||
WHERE permit_year = EXTRACT(YEAR FROM now())::int
|
||
GROUP BY fishery_code ORDER BY total DESC;
|
||
SQL
|
||
|
||
echo ""
|
||
echo "--- 7.5-3. vessel_analysis_results.gear_code 분포 (last 5min) ---"
|
||
$PSQL_TABLE << 'SQL'
|
||
SELECT coalesce(gear_code, '(null)') gear_code,
|
||
count(*) cnt,
|
||
round(avg(risk_score)::numeric, 1) avg_risk
|
||
FROM kcg.vessel_analysis_results
|
||
WHERE analyzed_at > now() - interval '5 minutes'
|
||
GROUP BY gear_code ORDER BY cnt DESC LIMIT 15;
|
||
SQL
|
||
|
||
echo ""
|
||
echo "--- 7.5-4. 최근 매칭된 선박 (top 10 by last_seen_at) ---"
|
||
$PSQL_TABLE << 'SQL'
|
||
SELECT permit_no, fishery_code, name_cn, mmsi, match_method,
|
||
match_confidence, last_seen_at
|
||
FROM kcg.fleet_vessels
|
||
WHERE permit_year = EXTRACT(YEAR FROM now())::int AND mmsi IS NOT NULL
|
||
ORDER BY last_seen_at DESC NULLS LAST LIMIT 10;
|
||
SQL
|
||
|
||
#===================================================================
|
||
# PART 8: 해역별 종합 교차
|
||
#===================================================================
|
||
echo ""
|
||
echo "================================================================="
|
||
echo "PART 8: 해역별 종합 교차표"
|
||
echo "================================================================="
|
||
$PSQL_TABLE << 'SQL'
|
||
SELECT zone_code, count(*) total,
|
||
count(*) FILTER (WHERE is_dark) dark,
|
||
count(*) FILTER (WHERE transship_suspect) transship,
|
||
count(*) FILTER (WHERE gear_judgment IS NOT NULL AND gear_judgment != '') gear_viol,
|
||
count(*) FILTER (WHERE risk_level='CRITICAL') crit,
|
||
count(*) FILTER (WHERE risk_level='HIGH') high,
|
||
round(avg(risk_score)::numeric, 1) avg_risk
|
||
FROM kcg.vessel_analysis_results
|
||
WHERE analyzed_at > now() - interval '5 minutes'
|
||
GROUP BY zone_code ORDER BY total DESC;
|
||
SQL
|
||
|
||
echo ""
|
||
echo "================================================================="
|
||
echo "END OF SNAPSHOT $STAMP"
|
||
echo "================================================================="
|
||
|
||
} > "$OUT" 2>&1
|
||
|
||
echo "[diag] $(date '+%H:%M:%S') saved: $OUT ($(wc -l < "$OUT") lines)"
|
||
|
||
sleep $INTERVAL_SEC
|
||
done
|