104 lines
5.7 KiB
SQL
104 lines
5.7 KiB
SQL
-- astock-kg 候选卡插槽视图：三张只读视图，供 akg-factor-bridge 的候选卡与复盘消费。
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-- 应用【桥机 155 · ~/project/akg-factor-bridge】：
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-- docker compose exec -T akg-factor-bridge python run.py apply-views --file sql/astock_kg_card_views.sql --dry-run
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-- docker compose exec -T -e AKG_PG_USER=<owner> -e AKG_PG_PASSWORD=<pw> \
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-- akg-factor-bridge python run.py apply-views --file sql/astock_kg_card_views.sql
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--
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-- 与 sql/astock_kg_slot_views.sql 分开放：那份文件用 DROP + CREATE 且含 ALTER TABLE，
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-- 整文件重跑会把生产在用的四张视图重删重建；本文件只用 CREATE OR REPLACE，反复应用无害。
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-- 基座零代码：只读现有表 transmission_candidates、segment_members_projection、
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-- segment_member_review、mkt_daily。应用时避开 06:10 的投影重建窗口。
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-- 出处：docs/主观选股改进方案_2026-09-02.md 第 2.2 节第二项。
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-- 一、已动成员视图 v_factor_transmission_moved
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-- 被传导指向的环节（只认 Segment 目标；Concept 与 Company 目标的成员不在投影表里）的
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-- 投影成员，减去传导台账里的未动名单 quiet，再减去复核账本判定"不属于本环节"的成员
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-- （verdict = 'exclude'，与基座 transmission.scan 在算已动之前的剔除口径一致）。
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-- 连接键用投影表的原名 COALESCE(orig_segment_name, segment_name)：投影期有改派重排，
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-- 传导扫描用的目标名是图上原名。
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-- 本视图只做集合差，不重算涨幅；"已动"的口径与基座 hotspot._movers_set 同源
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-- （数据日涨幅达到 3%），涨幅本身从 v_factor_stock_daily 取。
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-- 对账：按 (scan_date, target) 数本视图行数 + quiet 行数，与 transmission_candidates 的
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-- members_total 比；不等的环节多半是基座扫描时成员集有上限（cap=200）而投影表没有，
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-- 差异分"截断"与"真差异"两类，只对后者要求为零。
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CREATE OR REPLACE VIEW v_factor_transmission_moved AS
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WITH tc AS (
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SELECT t.scan_date, t.rank, t.target, t.mkt_trade_date, t.chain_fit,
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t.members_total, t.moved, t.moved_ratio,
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(SELECT count(DISTINCT p->>'source')
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FROM jsonb_array_elements(COALESCE(t.paths, '[]'::jsonb)) p) AS n_sources,
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t.quiet
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FROM transmission_candidates t
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WHERE t.target_type = 'Segment'
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),
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quiet AS (
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SELECT c.scan_date, c.target, q->>'ts_code' AS ts_code
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FROM tc c
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CROSS JOIN LATERAL jsonb_array_elements(COALESCE(c.quiet, '[]'::jsonb)) q
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WHERE q->>'ts_code' IS NOT NULL AND q->>'ts_code' <> ''
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),
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members AS (
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SELECT DISTINCT COALESCE(orig_segment_name, segment_name) AS seg,
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ts_code, member_name, segment_name AS projected_segment
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FROM segment_members_projection
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WHERE ts_code IS NOT NULL AND ts_code <> ''
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)
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SELECT c.scan_date, c.target, c.rank, c.n_sources, c.chain_fit,
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c.members_total, c.moved, c.moved_ratio, c.mkt_trade_date,
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m.ts_code, m.member_name, m.projected_segment
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FROM tc c
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JOIN members m ON m.seg = c.target
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LEFT JOIN quiet q
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ON q.scan_date = c.scan_date AND q.target = c.target AND q.ts_code = m.ts_code
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WHERE q.ts_code IS NULL
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AND NOT EXISTS (
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SELECT 1 FROM segment_member_review r
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WHERE r.ts_code = m.ts_code AND r.segment_name = c.target AND r.verdict = 'exclude');
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-- 二、个股日行情视图 v_factor_stock_daily
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-- 候选卡"已启动"门槛（pct_change）与两条展示线（net_z 主力净额对自身二十日基线的
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-- 标准化偏离、heat_chg 热度较往前第五个交易日的变化）的数据来源，只留行情列。
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-- 吸筹不从这里取：基座落库的吸筹状态没有评分日，候选卡的吸筹三项只认决策系统结论表。
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CREATE OR REPLACE VIEW v_factor_stock_daily AS
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SELECT trade_date,
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code AS ts_code,
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(metrics->>'pct_change')::numeric AS pct_change,
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(metrics->>'net_z')::numeric AS net_z,
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(metrics->>'heat_chg')::numeric AS heat_chg,
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(metrics->>'heat')::numeric AS heat,
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(metrics->>'net_amount')::numeric AS net_amount
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FROM mkt_daily
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WHERE kind = 'stock';
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-- 三、环节日行情视图 v_factor_segment_daily
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-- 按投影表把个股日行情聚成环节行，只给原始值与成员明细集合；"主力净额前两名"、
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-- "涨停近似（涨幅超 9.8%）"这类派生判断在桥的 card.py 算，不写进基座视图。
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-- 投影表是当前态（每晨 06:10 删后插），历史日的成员集合带成员前视，复盘按冻结快照重建。
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CREATE OR REPLACE VIEW v_factor_segment_daily AS
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WITH members AS (
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SELECT DISTINCT COALESCE(orig_segment_name, segment_name) AS seg, ts_code, member_name
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FROM segment_members_projection
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WHERE ts_code IS NOT NULL AND ts_code <> ''
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)
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SELECT s.trade_date,
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p.seg AS segment_name,
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count(*) AS members,
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count(*) FILTER (WHERE s.pct_change >= 3) AS moved,
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percentile_cont(0.5) WITHIN GROUP (ORDER BY s.pct_change) AS pct_median,
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percentile_cont(0.5) WITHIN GROUP (ORDER BY s.heat_chg) AS heat_chg_median,
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jsonb_agg(jsonb_build_object('ts_code', p.ts_code, 'name', p.member_name,
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'pct', s.pct_change, 'net_amount', s.net_amount)
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ORDER BY s.pct_change DESC NULLS LAST) AS members_detail
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FROM members p
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JOIN (
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SELECT trade_date, code AS ts_code,
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(metrics->>'pct_change')::numeric AS pct_change,
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(metrics->>'heat_chg')::numeric AS heat_chg,
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(metrics->>'net_amount')::numeric AS net_amount
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FROM mkt_daily WHERE kind = 'stock'
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) s ON s.ts_code = p.ts_code
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GROUP BY s.trade_date, p.seg;
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