fix: prediction e2e — 누락 테이블 12개 + 컬럼 매핑 + NUMERIC precision 통합 수정

- V014: fleet_vessels, fleet_tracking_snapshot, gear_identity_log,
  gear_correlation_scores/raw_metrics, correlation_param_models,
  group_polygon_snapshots, gear_group_episodes/episode_snapshots,
  gear_group_parent_candidate_snapshots, gear_parent_label_tracking_cycles,
  system_config 테이블 추가
- V015: 점수/비율 NUMERIC precision 일괄 확대 (score→7,4 / pct→12,2) +
  vessel_analysis_results UNIQUE(mmsi, analyzed_at) 인덱스 추가
- prediction kcgdb.py: timestamp→analyzed_at, zone→zone_code,
  is_leader→fleet_is_leader, is_transship_suspect→transship_suspect 매핑

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

backend/src/main/resources/db/migration/V014__fleet_prediction_tables.sql

@@ -0,0 +1,283 @@
+-- V014: prediction에서 참조하는 누락 테이블 추가
+-- fleet_vessels, fleet_tracking_snapshot, gear_identity_log,
+-- gear_correlation_scores, gear_correlation_raw_metrics, correlation_param_models,
+-- group_polygon_snapshots, gear_group_episodes, gear_group_episode_snapshots,
+-- gear_group_parent_candidate_snapshots, gear_parent_label_tracking_cycles, system_config
+
+-- ===== 1. fleet_vessels =====
+CREATE TABLE IF NOT EXISTS kcg.fleet_vessels (
+    id BIGSERIAL PRIMARY KEY,
+    company_id BIGINT NOT NULL REFERENCES kcg.fleet_companies(id),
+    permit_no VARCHAR(50),
+    name_cn VARCHAR(100),
+    name_en VARCHAR(100),
+    tonnage NUMERIC(10,2),
+    gear_code VARCHAR(20),
+    fleet_role VARCHAR(20) DEFAULT 'CREW',  -- MAIN, CREW, TRANSPORT, NOISE
+    pair_vessel_id BIGINT,
+    mmsi VARCHAR(20),
+    match_confidence NUMERIC(4,3),
+    match_method VARCHAR(30),  -- NAME_EXACT, NAME_PARENT
+    last_seen_at TIMESTAMPTZ,
+    created_at TIMESTAMPTZ DEFAULT now(),
+    updated_at TIMESTAMPTZ DEFAULT now()
+);
+
+CREATE INDEX idx_fleet_vessels_company ON kcg.fleet_vessels(company_id);
+CREATE INDEX idx_fleet_vessels_mmsi ON kcg.fleet_vessels(mmsi);
+CREATE INDEX idx_fleet_vessels_name_cn ON kcg.fleet_vessels(name_cn);
+
+-- ===== 2. fleet_tracking_snapshot =====
+CREATE TABLE IF NOT EXISTS kcg.fleet_tracking_snapshot (
+    id BIGSERIAL PRIMARY KEY,
+    company_id BIGINT NOT NULL REFERENCES kcg.fleet_companies(id),
+    snapshot_time TIMESTAMPTZ NOT NULL,
+    total_vessels INT NOT NULL DEFAULT 0,
+    active_vessels INT NOT NULL DEFAULT 0,
+    center_lat NUMERIC(9,6),
+    center_lon NUMERIC(10,6)
+);
+
+CREATE INDEX idx_fleet_snapshot_company ON kcg.fleet_tracking_snapshot(company_id, snapshot_time DESC);
+
+-- ===== 3. gear_identity_log =====
+CREATE TABLE IF NOT EXISTS kcg.gear_identity_log (
+    id BIGSERIAL PRIMARY KEY,
+    mmsi VARCHAR(20) NOT NULL,
+    name VARCHAR(200) NOT NULL,
+    parent_name VARCHAR(100),
+    parent_mmsi VARCHAR(20),
+    parent_vessel_id BIGINT,
+    gear_index_1 INT,
+    gear_index_2 INT,
+    lat NUMERIC(9,6),
+    lon NUMERIC(10,6),
+    match_method VARCHAR(30),
+    match_confidence NUMERIC(4,3),
+    first_seen_at TIMESTAMPTZ NOT NULL,
+    last_seen_at TIMESTAMPTZ NOT NULL,
+    is_active BOOLEAN NOT NULL DEFAULT TRUE
+);
+
+CREATE INDEX idx_gear_identity_mmsi ON kcg.gear_identity_log(mmsi, is_active);
+CREATE INDEX idx_gear_identity_name ON kcg.gear_identity_log(name, is_active);
+
+-- ===== 4. correlation_param_models =====
+CREATE TABLE IF NOT EXISTS kcg.correlation_param_models (
+    id BIGSERIAL PRIMARY KEY,
+    name VARCHAR(100) NOT NULL,
+    params JSONB NOT NULL DEFAULT '{}',
+    is_active BOOLEAN NOT NULL DEFAULT TRUE,
+    is_default BOOLEAN NOT NULL DEFAULT FALSE,
+    created_at TIMESTAMPTZ DEFAULT now()
+);
+
+-- 기본 모델 시드
+INSERT INTO kcg.correlation_param_models (name, params, is_active, is_default) VALUES
+    ('default', '{"ema_alpha": 0.3, "proximity_weight": 0.25, "visit_weight": 0.2, "activity_sync_weight": 0.15, "heading_weight": 0.15, "dtw_weight": 0.1, "speed_weight": 0.1, "drift_weight": 0.05}', TRUE, TRUE)
+ON CONFLICT DO NOTHING;
+
+-- ===== 5. gear_correlation_scores =====
+CREATE TABLE IF NOT EXISTS kcg.gear_correlation_scores (
+    model_id BIGINT NOT NULL REFERENCES kcg.correlation_param_models(id),
+    group_key VARCHAR(255) NOT NULL,
+    sub_cluster_id INT NOT NULL,
+    target_mmsi VARCHAR(20) NOT NULL,
+    target_type VARCHAR(20),           -- VESSEL, GEAR_BUOY
+    target_name VARCHAR(200),
+    current_score NUMERIC(6,4) DEFAULT 0,
+    proximity_ratio NUMERIC(6,4),
+    visit_score NUMERIC(6,4),
+    heading_coherence NUMERIC(6,4),
+    streak_count INT DEFAULT 0,
+    freeze_state VARCHAR(20) DEFAULT 'ACTIVE',  -- ACTIVE, FREEZE, SIGNAL_LOSS
+    observation_count INT DEFAULT 0,
+    first_observed_at TIMESTAMPTZ,
+    last_observed_at TIMESTAMPTZ,
+    updated_at TIMESTAMPTZ DEFAULT now(),
+    PRIMARY KEY (model_id, group_key, sub_cluster_id, target_mmsi)
+);
+
+CREATE INDEX idx_corr_scores_group ON kcg.gear_correlation_scores(group_key, sub_cluster_id);
+CREATE INDEX idx_corr_scores_target ON kcg.gear_correlation_scores(target_mmsi);
+
+-- ===== 6. gear_correlation_raw_metrics =====
+CREATE TABLE IF NOT EXISTS kcg.gear_correlation_raw_metrics (
+    id BIGSERIAL PRIMARY KEY,
+    observed_at TIMESTAMPTZ NOT NULL,
+    group_key VARCHAR(255) NOT NULL,
+    sub_cluster_id INT NOT NULL,
+    target_mmsi VARCHAR(20) NOT NULL,
+    target_type VARCHAR(20),
+    target_name VARCHAR(200),
+    proximity_ratio NUMERIC(6,4),
+    visit_score NUMERIC(6,4),
+    activity_sync NUMERIC(6,4),
+    dtw_similarity NUMERIC(6,4),
+    speed_correlation NUMERIC(6,4),
+    heading_coherence NUMERIC(6,4),
+    drift_similarity NUMERIC(6,4),
+    shadow_stay BOOLEAN DEFAULT FALSE,
+    shadow_return BOOLEAN DEFAULT FALSE,
+    gear_group_active_ratio NUMERIC(6,4)
+);
+
+CREATE INDEX idx_raw_metrics_observed ON kcg.gear_correlation_raw_metrics(observed_at);
+CREATE INDEX idx_raw_metrics_group ON kcg.gear_correlation_raw_metrics(group_key, sub_cluster_id, observed_at);
+
+-- ===== 7. group_polygon_snapshots =====
+CREATE TABLE IF NOT EXISTS kcg.group_polygon_snapshots (
+    id BIGSERIAL PRIMARY KEY,
+    group_type VARCHAR(30) NOT NULL,       -- FLEET, GEAR_IN_ZONE, GEAR_OUT_ZONE
+    group_key VARCHAR(255) NOT NULL,
+    group_label VARCHAR(255),
+    sub_cluster_id INT NOT NULL DEFAULT 0,
+    resolution VARCHAR(10) DEFAULT '6h',   -- 6h, 1h
+    snapshot_time TIMESTAMPTZ NOT NULL,
+    polygon GEOMETRY(Polygon, 4326),
+    center_point GEOMETRY(Point, 4326),
+    area_sq_nm NUMERIC(12,4),
+    member_count INT DEFAULT 0,
+    zone_id VARCHAR(50),
+    zone_name VARCHAR(100),
+    members JSONB,
+    color VARCHAR(20)
+);
+
+CREATE INDEX idx_polygon_snap_group ON kcg.group_polygon_snapshots(group_key, sub_cluster_id, snapshot_time DESC);
+CREATE INDEX idx_polygon_snap_time ON kcg.group_polygon_snapshots(snapshot_time);
+CREATE INDEX idx_polygon_snap_geom ON kcg.group_polygon_snapshots USING GIST (polygon);
+
+-- ===== 8. gear_group_episodes =====
+CREATE TABLE IF NOT EXISTS kcg.gear_group_episodes (
+    episode_id VARCHAR(50) PRIMARY KEY,   -- 'ep-{12hex}'
+    lineage_key VARCHAR(255) NOT NULL,
+    group_key VARCHAR(255) NOT NULL,
+    normalized_parent_name VARCHAR(100),
+    current_sub_cluster_id INT,
+    status VARCHAR(20) NOT NULL DEFAULT 'ACTIVE',  -- ACTIVE, EXPIRED, MERGED
+    continuity_source VARCHAR(30),         -- NEW, CONTINUED, SPLIT_NEW, SPLIT_CONTINUE, MERGE_NEW
+    continuity_score NUMERIC(6,4),
+    first_seen_at TIMESTAMPTZ,
+    last_seen_at TIMESTAMPTZ,
+    last_snapshot_time TIMESTAMPTZ,
+    current_member_count INT DEFAULT 0,
+    current_member_mmsis JSONB,
+    current_center_point GEOMETRY(Point, 4326),
+    split_from_episode_id VARCHAR(50),
+    merged_from_episode_ids JSONB,
+    merged_into_episode_id VARCHAR(50),
+    metadata JSONB,
+    updated_at TIMESTAMPTZ DEFAULT now()
+);
+
+CREATE INDEX idx_episodes_lineage ON kcg.gear_group_episodes(lineage_key, status);
+CREATE INDEX idx_episodes_group ON kcg.gear_group_episodes(group_key, status);
+CREATE INDEX idx_episodes_snapshot ON kcg.gear_group_episodes(last_snapshot_time);
+
+-- ===== 9. gear_group_episode_snapshots =====
+CREATE TABLE IF NOT EXISTS kcg.gear_group_episode_snapshots (
+    episode_id VARCHAR(50) NOT NULL,
+    lineage_key VARCHAR(255),
+    group_key VARCHAR(255) NOT NULL,
+    normalized_parent_name VARCHAR(100),
+    sub_cluster_id INT NOT NULL,
+    observed_at TIMESTAMPTZ NOT NULL,
+    member_count INT DEFAULT 0,
+    member_mmsis JSONB,
+    center_point GEOMETRY(Point, 4326),
+    continuity_source VARCHAR(30),
+    continuity_score NUMERIC(6,4),
+    parent_episode_ids JSONB,
+    top_candidate_mmsi VARCHAR(20),
+    top_candidate_score NUMERIC(6,4),
+    resolution_status VARCHAR(30),
+    metadata JSONB,
+    PRIMARY KEY (episode_id, observed_at)
+);
+
+CREATE INDEX idx_ep_snap_group ON kcg.gear_group_episode_snapshots(group_key, sub_cluster_id, observed_at DESC);
+
+-- ===== 10. gear_group_parent_candidate_snapshots =====
+CREATE TABLE IF NOT EXISTS kcg.gear_group_parent_candidate_snapshots (
+    id BIGSERIAL PRIMARY KEY,
+    observed_at TIMESTAMPTZ NOT NULL,
+    group_key VARCHAR(255) NOT NULL,
+    sub_cluster_id INT NOT NULL,
+    parent_name VARCHAR(100),
+    normalized_parent_name VARCHAR(100),
+    episode_id VARCHAR(50),
+    candidate_mmsi VARCHAR(20) NOT NULL,
+    candidate_name VARCHAR(200),
+    candidate_vessel_id BIGINT,
+    rank INT,
+    candidate_source VARCHAR(30),
+    model_id BIGINT,
+    model_name VARCHAR(100),
+    base_corr_score NUMERIC(6,4),
+    name_match_score NUMERIC(6,4),
+    track_similarity_score NUMERIC(6,4),
+    visit_score_6h NUMERIC(6,4),
+    proximity_score_6h NUMERIC(6,4),
+    activity_sync_score_6h NUMERIC(6,4),
+    stability_score NUMERIC(6,4),
+    registry_bonus NUMERIC(6,4),
+    episode_prior_bonus NUMERIC(6,4),
+    lineage_prior_bonus NUMERIC(6,4),
+    label_prior_bonus NUMERIC(6,4),
+    final_score NUMERIC(6,4),
+    margin_from_top NUMERIC(6,4),
+    evidence JSONB
+);
+
+CREATE INDEX idx_candidate_snap_group ON kcg.gear_group_parent_candidate_snapshots(group_key, sub_cluster_id, observed_at DESC);
+CREATE INDEX idx_candidate_snap_episode ON kcg.gear_group_parent_candidate_snapshots(episode_id, observed_at DESC);
+CREATE INDEX idx_candidate_snap_norm ON kcg.gear_group_parent_candidate_snapshots(normalized_parent_name);
+
+-- ===== 11. gear_parent_label_tracking_cycles =====
+CREATE TABLE IF NOT EXISTS kcg.gear_parent_label_tracking_cycles (
+    label_session_id BIGINT NOT NULL REFERENCES kcg.gear_parent_label_sessions(id),
+    observed_at TIMESTAMPTZ NOT NULL,
+    candidate_snapshot_observed_at TIMESTAMPTZ,
+    auto_status VARCHAR(30),
+    top_candidate_mmsi VARCHAR(20),
+    top_candidate_name VARCHAR(200),
+    top_candidate_score NUMERIC(6,4),
+    top_candidate_margin NUMERIC(6,4),
+    candidate_count INT,
+    labeled_candidate_present BOOLEAN,
+    labeled_candidate_rank INT,
+    labeled_candidate_score NUMERIC(6,4),
+    labeled_candidate_pre_bonus_score NUMERIC(6,4),
+    labeled_candidate_margin_from_top NUMERIC(6,4),
+    matched_top1 BOOLEAN,
+    matched_top3 BOOLEAN,
+    evidence_summary JSONB,
+    PRIMARY KEY (label_session_id, observed_at)
+);
+
+-- ===== 12. system_config =====
+CREATE TABLE IF NOT EXISTS kcg.system_config (
+    key VARCHAR(100) PRIMARY KEY,
+    value JSONB,
+    description TEXT,
+    updated_at TIMESTAMPTZ DEFAULT now()
+);
+
+-- 파티션 기본값 시드
+INSERT INTO kcg.system_config (key, value, description) VALUES
+    ('partition.raw_metrics.retention_days', '7', '원시 메트릭 보관 일수'),
+    ('partition.raw_metrics.create_ahead_days', '3', '파티션 사전 생성 일수'),
+    ('partition.scores.cleanup_days', '30', '점수 정리 일수')
+ON CONFLICT (key) DO NOTHING;
+
+-- ===== fleet_vessels 시드 데이터 (fleet_companies 기반) =====
+-- 중국 원양어업 회사 소속 선박 (데모용)
+INSERT INTO kcg.fleet_vessels (company_id, permit_no, name_cn, name_en, tonnage, gear_code, fleet_role) VALUES
+    (1, 'ZY-2024-001', '鲁荣渔2682', 'LU RONG YU 2682', 450.0, 'TRAWL', 'MAIN'),
+    (1, 'ZY-2024-002', '鲁荣渔2683', 'LU RONG YU 2683', 380.0, 'TRAWL', 'CREW'),
+    (1, 'ZY-2024-003', '鲁荣渔2680', 'LU RONG YU 2680', 520.0, 'PURSE', 'MAIN'),
+    (2, 'ZY-2024-010', '浙岱渔11032', 'ZHE DAI YU 11032', 600.0, 'PURSE', 'MAIN'),
+    (2, 'ZY-2024-011', '浙岱渔11033', 'ZHE DAI YU 11033', 550.0, 'PURSE', 'CREW'),
+    (2, 'ZY-2024-012', '浙岱渔运108', 'ZHE DAI YU YUN 108', 800.0, 'TRANSPORT', 'TRANSPORT')
+ON CONFLICT DO NOTHING;

backend/src/main/resources/db/migration/V015__fix_numeric_precision.sql

@@ -0,0 +1,80 @@
+-- V015: 점수/비율 NUMERIC 컬럼 precision 일괄 확대 + vessel_analysis_results UNIQUE 제약
+
+-- === 1. vessel_analysis_results 점수 컬럼 ===
+ALTER TABLE kcg.vessel_analysis_results ALTER COLUMN confidence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.vessel_analysis_results ALTER COLUMN fishing_pct TYPE NUMERIC(7,4);
+ALTER TABLE kcg.vessel_analysis_results ALTER COLUMN ucaf_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.vessel_analysis_results ALTER COLUMN ucft_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.vessel_analysis_results ALTER COLUMN spoofing_score TYPE NUMERIC(7,4);
+
+-- ON CONFLICT용 UNIQUE 제약 (파티션 테이블은 PK가 있지만 ON CONFLICT 절에서 인식 안 됨)
+-- 파티션 PK (id, analyzed_at)와 별도로 mmsi+analyzed_at UNIQUE 추가
+CREATE UNIQUE INDEX IF NOT EXISTS idx_var_mmsi_analyzed ON kcg.vessel_analysis_results (mmsi, analyzed_at);
+
+-- === 2. prediction_events/alerts ai_confidence ===
+ALTER TABLE kcg.prediction_events ALTER COLUMN ai_confidence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.prediction_alerts ALTER COLUMN ai_confidence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.enforcement_records ALTER COLUMN ai_confidence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.prediction_label_input ALTER COLUMN confidence TYPE NUMERIC(7,4);
+
+-- === 3. AI 모델 메트릭 ===
+ALTER TABLE kcg.ai_model_versions ALTER COLUMN accuracy_pct TYPE NUMERIC(7,2);
+ALTER TABLE kcg.ai_model_versions ALTER COLUMN precision_pct TYPE NUMERIC(7,2);
+ALTER TABLE kcg.ai_model_versions ALTER COLUMN recall_pct TYPE NUMERIC(7,2);
+ALTER TABLE kcg.ai_model_versions ALTER COLUMN f1_score TYPE NUMERIC(7,4);
+
+-- === 4. gear 관련 score 컬럼 NUMERIC(6,4) → NUMERIC(7,4) ===
+-- gear_correlation_scores
+ALTER TABLE kcg.gear_correlation_scores ALTER COLUMN current_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_scores ALTER COLUMN proximity_ratio TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_scores ALTER COLUMN visit_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_scores ALTER COLUMN heading_coherence TYPE NUMERIC(7,4);
+
+-- gear_correlation_raw_metrics
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN proximity_ratio TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN visit_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN activity_sync TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN dtw_similarity TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN speed_correlation TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN heading_coherence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN drift_similarity TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_correlation_raw_metrics ALTER COLUMN gear_group_active_ratio TYPE NUMERIC(7,4);
+
+-- gear_group_episodes
+ALTER TABLE kcg.gear_group_episodes ALTER COLUMN continuity_score TYPE NUMERIC(7,4);
+
+-- gear_group_episode_snapshots
+ALTER TABLE kcg.gear_group_episode_snapshots ALTER COLUMN continuity_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_episode_snapshots ALTER COLUMN top_candidate_score TYPE NUMERIC(7,4);
+
+-- gear_group_parent_candidate_snapshots (13개 score 컬럼)
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN base_corr_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN name_match_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN track_similarity_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN visit_score_6h TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN proximity_score_6h TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN activity_sync_score_6h TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN stability_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN registry_bonus TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN episode_prior_bonus TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN lineage_prior_bonus TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN label_prior_bonus TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN final_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_group_parent_candidate_snapshots ALTER COLUMN margin_from_top TYPE NUMERIC(7,4);
+
+-- gear_parent_label_tracking_cycles
+ALTER TABLE kcg.gear_parent_label_tracking_cycles ALTER COLUMN top_candidate_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_parent_label_tracking_cycles ALTER COLUMN top_candidate_margin TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_parent_label_tracking_cycles ALTER COLUMN labeled_candidate_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_parent_label_tracking_cycles ALTER COLUMN labeled_candidate_pre_bonus_score TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_parent_label_tracking_cycles ALTER COLUMN labeled_candidate_margin_from_top TYPE NUMERIC(7,4);
+
+-- === 5. match_confidence NUMERIC(4,3) → NUMERIC(7,4) ===
+ALTER TABLE kcg.fleet_vessels ALTER COLUMN match_confidence TYPE NUMERIC(7,4);
+ALTER TABLE kcg.gear_identity_log ALTER COLUMN match_confidence TYPE NUMERIC(7,4);
+
+-- === 6. stats/kpi 테이블 ===
+ALTER TABLE kcg.prediction_stats_daily ALTER COLUMN ai_accuracy_pct TYPE NUMERIC(12,2);
+ALTER TABLE kcg.prediction_stats_monthly ALTER COLUMN ai_accuracy_pct TYPE NUMERIC(12,2);
+ALTER TABLE kcg.prediction_kpi_realtime ALTER COLUMN delta_pct TYPE NUMERIC(12,2);
+ALTER TABLE kcg.prediction_risk_grid ALTER COLUMN avg_risk TYPE NUMERIC(12,2);

prediction/db/kcgdb.py

@@ -71,22 +71,22 @@ def upsert_results(results: list['AnalysisResult']) -> int:
 
     insert_sql = """
         INSERT INTO vessel_analysis_results (
-            mmsi, timestamp, vessel_type, confidence, fishing_pct,
+            mmsi, analyzed_at, vessel_type, confidence, fishing_pct,
-            cluster_id, season, zone, dist_to_baseline_nm, activity_state,
+            cluster_id, season, zone_code, dist_to_baseline_nm, activity_state,
             ucaf_score, ucft_score, is_dark, gap_duration_min,
             spoofing_score, bd09_offset_m, speed_jump_count,
-            cluster_size, is_leader, fleet_role,
+            fleet_cluster_id, fleet_is_leader, fleet_role,
             risk_score, risk_level,
-            is_transship_suspect, transship_pair_mmsi, transship_duration_min,
+            transship_suspect, transship_pair_mmsi, transship_duration_min,
-            features, analyzed_at
+            features
         ) VALUES %s
-        ON CONFLICT (mmsi, timestamp) DO UPDATE SET
+        ON CONFLICT (mmsi, analyzed_at) DO UPDATE SET
             vessel_type = EXCLUDED.vessel_type,
             confidence = EXCLUDED.confidence,
             fishing_pct = EXCLUDED.fishing_pct,
             cluster_id = EXCLUDED.cluster_id,
             season = EXCLUDED.season,
-            zone = EXCLUDED.zone,
+            zone_code = EXCLUDED.zone_code,
             dist_to_baseline_nm = EXCLUDED.dist_to_baseline_nm,
             activity_state = EXCLUDED.activity_state,
             ucaf_score = EXCLUDED.ucaf_score,
@@ -96,16 +96,15 @@ def upsert_results(results: list['AnalysisResult']) -> int:
             spoofing_score = EXCLUDED.spoofing_score,
             bd09_offset_m = EXCLUDED.bd09_offset_m,
             speed_jump_count = EXCLUDED.speed_jump_count,
-            cluster_size = EXCLUDED.cluster_size,
+            fleet_cluster_id = EXCLUDED.fleet_cluster_id,
-            is_leader = EXCLUDED.is_leader,
+            fleet_is_leader = EXCLUDED.fleet_is_leader,
             fleet_role = EXCLUDED.fleet_role,
             risk_score = EXCLUDED.risk_score,
             risk_level = EXCLUDED.risk_level,
-            is_transship_suspect = EXCLUDED.is_transship_suspect,
+            transship_suspect = EXCLUDED.transship_suspect,
             transship_pair_mmsi = EXCLUDED.transship_pair_mmsi,
             transship_duration_min = EXCLUDED.transship_duration_min,
-            features = EXCLUDED.features,
+            features = EXCLUDED.features
-            analyzed_at = EXCLUDED.analyzed_at
     """
 
     try:

prediction/models/result.py

@@ -75,13 +75,13 @@ class AnalysisResult:
 
         return (
             str(self.mmsi),
-            self.timestamp,
+            self.analyzed_at,           # analyzed_at (PK 파티션키)
             str(self.vessel_type),
             _f(self.confidence),
             _f(self.fishing_pct),
             _i(self.cluster_id),
             str(self.season),
-            str(self.zone),
+            str(self.zone),             # → zone_code
             _f(self.dist_to_baseline_nm),
             str(self.activity_state),
             _f(self.ucaf_score),
@@ -91,14 +91,13 @@ class AnalysisResult:
             _f(self.spoofing_score),
             _f(self.bd09_offset_m),
             _i(self.speed_jump_count),
-            _i(self.cluster_size),
+            _i(self.cluster_id),        # → fleet_cluster_id
-            bool(self.is_leader),
+            bool(self.is_leader),       # → fleet_is_leader
             str(self.fleet_role),
             _i(self.risk_score),
             str(self.risk_level),
-            bool(self.is_transship_suspect),
+            bool(self.is_transship_suspect),  # → transship_suspect
             str(self.transship_pair_mmsi),
             _i(self.transship_duration_min),
             json.dumps(safe_features),
-            self.analyzed_at,
         )