247 lines
11 KiB
PL/PgSQL
247 lines
11 KiB
PL/PgSQL
-- =====================================================================================
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-- 商城分析模块 RPC 函数增量脚本
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-- 依赖: ml_* 系列表, ak_users 表
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-- 目标: 为数据分析模块提供核心数据接口，优先使用现有表，不新建表。
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-- =====================================================================================
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-- =====================================================================================
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-- 1. 函数: rpc_analytics_user_kpis
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-- 描述: 获取用户分析核心KPI指标，并与上一周期对比。
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-- =====================================================================================
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CREATE OR REPLACE FUNCTION public.rpc_analytics_user_kpis(
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p_start_date DATE,
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p_end_date DATE
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)
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RETURNS TABLE (
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total_users BIGINT,
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user_growth FLOAT,
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new_users BIGINT,
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new_user_growth FLOAT,
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active_users BIGINT,
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active_growth FLOAT,
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ordering_users BIGINT,
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ordering_growth FLOAT,
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paid_users BIGINT,
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paid_growth FLOAT,
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new_user_conversion_rate FLOAT,
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repurchase_rate FLOAT,
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repurchase_growth FLOAT
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)
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LANGUAGE plpgsql
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AS $$
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DECLARE
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prev_start_date DATE;
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prev_end_date DATE;
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period_days INT;
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BEGIN
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-- 计算上一周期日期范围
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period_days := p_end_date - p_start_date + 1;
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prev_start_date := p_start_date - period_days;
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prev_end_date := p_start_date - 1;
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RETURN QUERY
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WITH
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-- 当前周期数据
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current_period AS (
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SELECT
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(SELECT COUNT(*) FROM public.ak_users WHERE created_at <= p_end_date::timestamp) AS total_users,
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COUNT(DISTINCT CASE WHEN u.created_at::DATE BETWEEN p_start_date AND p_end_date THEN u.id END)::BIGINT AS new_users,
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(SELECT COUNT(DISTINCT bh.user_id) FROM public.ml_browse_history bh WHERE bh.created_at::DATE BETWEEN p_start_date AND p_end_date) AS active_users,
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(SELECT COUNT(DISTINCT o.user_id) FROM public.ml_orders o WHERE o.created_at::DATE BETWEEN p_start_date AND p_end_date) AS ordering_users,
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(SELECT COUNT(DISTINCT o.user_id) FROM public.ml_orders o WHERE o.created_at::DATE BETWEEN p_start_date AND p_end_date AND o.payment_status = 2) AS paid_users,
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(
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SELECT COUNT(DISTINCT o.user_id) * 100.0 / NULLIF(COUNT(DISTINCT u_new.id), 0)
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FROM public.ak_users u_new
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LEFT JOIN public.ml_orders o ON u_new.id = o.user_id AND o.payment_status = 2 AND o.created_at::DATE BETWEEN p_start_date AND p_end_date
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WHERE u_new.created_at::DATE BETWEEN p_start_date AND p_end_date
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) AS new_user_conversion_rate,
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(
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SELECT COUNT(DISTINCT CASE WHEN user_orders.order_count > 1 THEN user_orders.user_id END) * 100.0 / NULLIF(COUNT(DISTINCT user_orders.user_id), 0)
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FROM (
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SELECT user_id, COUNT(id) as order_count
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FROM public.ml_orders
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WHERE created_at::DATE <= p_end_date AND payment_status = 2
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GROUP BY user_id
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) user_orders
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WHERE user_orders.user_id IN (SELECT user_id FROM public.ml_orders WHERE created_at::DATE BETWEEN p_start_date AND p_end_date AND payment_status = 2)
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) AS repurchase_rate
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FROM public.ak_users u
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),
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-- 上一周期数据
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previous_period AS (
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SELECT
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(SELECT COUNT(*) FROM public.ak_users WHERE created_at <= prev_end_date::timestamp) AS total_users,
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COUNT(DISTINCT CASE WHEN u.created_at::DATE BETWEEN prev_start_date AND prev_end_date THEN u.id END)::BIGINT AS new_users,
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(SELECT COUNT(DISTINCT bh.user_id) FROM public.ml_browse_history bh WHERE bh.created_at::DATE BETWEEN prev_start_date AND prev_end_date) AS active_users,
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(SELECT COUNT(DISTINCT o.user_id) FROM public.ml_orders o WHERE o.created_at::DATE BETWEEN prev_start_date AND prev_end_date) AS ordering_users,
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(SELECT COUNT(DISTINCT o.user_id) FROM public.ml_orders o WHERE o.created_at::DATE BETWEEN prev_start_date AND prev_end_date AND o.payment_status = 2) AS paid_users,
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(
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SELECT COUNT(DISTINCT CASE WHEN user_orders.order_count > 1 THEN user_orders.user_id END) * 100.0 / NULLIF(COUNT(DISTINCT user_orders.user_id), 0)
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FROM (
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SELECT user_id, COUNT(id) as order_count
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FROM public.ml_orders
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WHERE created_at::DATE <= prev_end_date AND payment_status = 2
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GROUP BY user_id
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) user_orders
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WHERE user_orders.user_id IN (SELECT user_id FROM public.ml_orders WHERE created_at::DATE BETWEEN prev_start_date AND prev_end_date AND payment_status = 2)
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) AS repurchase_rate
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FROM public.ak_users u
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)
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SELECT
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cp.total_users,
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ROUND(((cp.total_users - pp.total_users) * 100.0 / NULLIF(pp.total_users, 0))::numeric, 2)::FLOAT AS user_growth,
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cp.new_users,
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ROUND(((cp.new_users - pp.new_users) * 100.0 / NULLIF(pp.new_users, 0))::numeric, 2)::FLOAT AS new_user_growth,
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cp.active_users,
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ROUND(((cp.active_users - pp.active_users) * 100.0 / NULLIF(pp.active_users, 0))::numeric, 2)::FLOAT AS active_growth,
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cp.ordering_users,
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ROUND(((cp.ordering_users - pp.ordering_users) * 100.0 / NULLIF(pp.ordering_users, 0))::numeric, 2)::FLOAT AS ordering_growth,
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cp.paid_users,
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ROUND(((cp.paid_users - pp.paid_users) * 100.0 / NULLIF(pp.paid_users, 0))::numeric, 2)::FLOAT AS paid_growth,
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ROUND(cp.new_user_conversion_rate::numeric, 2)::FLOAT,
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ROUND(cp.repurchase_rate::numeric, 2)::FLOAT AS repurchase_rate,
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ROUND((COALESCE(cp.repurchase_rate, 0) - COALESCE(pp.repurchase_rate, 0))::numeric, 2)::FLOAT AS repurchase_growth
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FROM current_period cp, previous_period pp;
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END;
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$$;
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-- -------------------------------------------------------------------------------------
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-- 2. 函数: rpc_analytics_user_growth_trend
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-- 描述: 获取用户增长与活跃趋势（日维度）
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-- -------------------------------------------------------------------------------------
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CREATE OR REPLACE FUNCTION public.rpc_analytics_user_growth_trend(
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p_start_date DATE,
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p_end_date DATE
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)
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RETURNS TABLE (
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date DATE,
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new_users BIGINT,
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active_users BIGINT
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)
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LANGUAGE sql
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AS $$
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WITH date_series AS (
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SELECT generate_series(p_start_date, p_end_date, '1 day'::interval)::DATE AS date
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)
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SELECT
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ds.date,
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(SELECT COUNT(u.id) FROM public.ak_users u WHERE u.created_at::DATE = ds.date)::BIGINT AS new_users,
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(SELECT COUNT(DISTINCT bh.user_id) FROM public.ml_browse_history bh WHERE bh.created_at::DATE = ds.date)::BIGINT AS active_users
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FROM date_series ds
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ORDER BY ds.date;
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$$;
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-- -------------------------------------------------------------------------------------
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-- 3. 函数: rpc_analytics_user_segments
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-- 描述: 获取用户分群（基于新老客、复购的简单模型）
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-- -------------------------------------------------------------------------------------
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CREATE OR REPLACE FUNCTION public.rpc_analytics_user_segments(
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p_start_date DATE,
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p_end_date DATE
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)
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RETURNS TABLE (
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name TEXT,
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value BIGINT
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)
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LANGUAGE sql
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AS $$
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WITH user_orders_stats AS (
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SELECT
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user_id,
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MIN(created_at) as first_order_time,
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COUNT(id) as total_orders
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FROM public.ml_orders
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WHERE payment_status = 2
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GROUP BY user_id
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),
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active_users_in_period AS (
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SELECT DISTINCT user_id FROM public.ml_orders WHERE created_at::DATE BETWEEN p_start_date AND p_end_date
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)
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SELECT
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segment as name,
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COUNT(user_id) as value
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FROM (
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SELECT
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auip.user_id,
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CASE
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WHEN uos.first_order_time::DATE BETWEEN p_start_date AND p_end_date THEN '新客'
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WHEN uos.total_orders > 1 THEN '复购客户'
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ELSE '老客'
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END as segment
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FROM active_users_in_period auip
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JOIN user_orders_stats uos ON auip.user_id = uos.user_id
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) segments
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GROUP BY segment;
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$$;
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-- -------------------------------------------------------------------------------------
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-- 4. 函数: rpc_analytics_traffic_sources
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-- 描述: 获取流量来源分布 (基于注册来源)
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-- 兼容性说明：部分环境的 ak_users 可能不存在 registration_source 字段。
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-- 为避免 RPC 报错导致页面加载失败，这里做“字段存在则分组统计，不存在则全部归为未知”的兼容。
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-- -------------------------------------------------------------------------------------
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CREATE OR REPLACE FUNCTION public.rpc_analytics_traffic_sources(
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p_start_date DATE,
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p_end_date DATE
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)
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RETURNS TABLE (
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name TEXT,
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value BIGINT
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)
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LANGUAGE plpgsql
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AS $
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DECLARE
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has_registration_source BOOLEAN := FALSE;
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BEGIN
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SELECT EXISTS (
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SELECT 1
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FROM information_schema.columns
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WHERE table_schema = 'public'
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AND table_name = 'ak_users'
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AND column_name = 'registration_source'
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) INTO has_registration_source;
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IF has_registration_source THEN
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RETURN QUERY
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EXECUTE '
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SELECT
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COALESCE(registration_source, ''未知'') AS name,
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COUNT(id)::BIGINT AS value
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FROM public.ak_users
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WHERE created_at::DATE BETWEEN $1 AND $2
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GROUP BY name
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ORDER BY value DESC
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'
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USING p_start_date, p_end_date;
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ELSE
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RETURN QUERY
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SELECT '未知'::TEXT AS name,
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COUNT(id)::BIGINT AS value
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FROM public.ak_users
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WHERE created_at::DATE BETWEEN p_start_date AND p_end_date;
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END IF;
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END;
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$;
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-- =====================================================================================
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-- 5. 完成提示
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-- =====================================================================================
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DO $$
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BEGIN
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RAISE NOTICE '=======================================================';
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RAISE NOTICE '商城分析模块 RPC 函数创建/更新完成！';
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RAISE NOTICE '=======================================================';
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RAISE NOTICE '✓ RPC 函数创建/更新完成:';
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RAISE NOTICE ' - rpc_analytics_user_kpis';
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RAISE NOTICE ' - rpc_analytics_user_growth_trend';
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RAISE NOTICE ' - rpc_analytics_user_segments';
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RAISE NOTICE ' - rpc_analytics_traffic_sources';
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RAISE NOTICE '=======================================================';
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RAISE NOTICE '下一步:';
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RAISE NOTICE '1. 在数据库中执行此脚本。';
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RAISE NOTICE '2. 确认前端 user-analysis.uvue 页面已调用这些 RPC。';
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RAISE NOTICE '3. 如果缺少活跃数据，请确保 ml_browse_history 表有数据写入。';
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RAISE NOTICE '=======================================================';
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END $$;
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