129 lines
4.6 KiB
SQL
129 lines
4.6 KiB
SQL
-- =====================================================================
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-- @Name: DORIS-D-SQL-{表名}-ETL
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-- @Version: 2.0
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-- @Desc: Apache Doris ETL 数据处理模板（临时表链式处理）
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-- @TargetDatabase: Apache Doris
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-- @说明: 统一规范：禁止 CTE，每步物化为临时表，先 DROP 再 CREATE
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-- =====================================================================
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-- ============================================================================
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-- Step01: 基础清洗与过滤
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-- ============================================================================
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-- 说明：从源表读取数据，进行基础过滤和清洗
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-- 输入：{源表名}
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-- 输出：${db_tmp_env}.tmp_xxx_01
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DROP TABLE IF EXISTS ${db_tmp_env}.tmp_xxx_01;
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CREATE TABLE ${db_tmp_env}.tmp_xxx_01 AS
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SELECT
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order_id,
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user_id,
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dept_id,
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total_amount,
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status,
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order_date
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FROM db_name.source_table
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WHERE order_date = '${day_id}'
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AND status IN ('completed', 'shipped') -- 业务过滤
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AND total_amount > 0 -- 数据质量过滤
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AND user_id IS NOT NULL; -- NULL过滤
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-- ============================================================================
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-- Step02: 多表关联与维度补全
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-- ============================================================================
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-- 说明：关联维度表，补全业务属性字段
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-- 输入：${db_tmp_env}.tmp_xxx_01, dim_department, dim_category
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-- 输出：${db_tmp_env}.tmp_xxx_02
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DROP TABLE IF EXISTS ${db_tmp_env}.tmp_xxx_02;
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CREATE TABLE ${db_tmp_env}.tmp_xxx_02 AS
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SELECT
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a.order_id,
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a.user_id,
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a.total_amount,
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a.status,
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b.dept_name, -- 维度补全：部门名称
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c.category_name, -- 维度补全：类别名称
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a.order_date
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FROM ${db_tmp_env}.tmp_xxx_01 a
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LEFT JOIN db_name.dim_department b
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ON a.dept_id = b.dept_id
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LEFT JOIN db_name.dim_category c
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ON a.category_id = c.category_id;
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-- ============================================================================
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-- Step03: 聚合计算与指标生成
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-- ============================================================================
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-- 说明：按业务维度聚合，计算统计指标
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-- 输入：${db_tmp_env}.tmp_xxx_02
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-- 输出：${db_tmp_env}.tmp_xxx_03
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DROP TABLE IF EXISTS ${db_tmp_env}.tmp_xxx_03;
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CREATE TABLE ${db_tmp_env}.tmp_xxx_03 AS
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SELECT
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order_date,
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dept_name,
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category_name,
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COUNT(*) AS record_count, -- 记录数
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COUNT(DISTINCT user_id) AS unique_users, -- 去重用户数
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SUM(total_amount) AS total_amount, -- 总金额
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AVG(total_amount) AS avg_amount, -- 平均金额
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MAX(total_amount) AS max_amount -- 最大金额
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FROM ${db_tmp_env}.tmp_xxx_02
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GROUP BY order_date, dept_name, category_name;
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-- ============================================================================
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-- Step04: 最终输出写入目标表
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-- ============================================================================
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-- 说明：补全目标表标准字段，写入结果表
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-- 输入：${db_tmp_env}.tmp_xxx_03
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-- 输出：目标表
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INSERT INTO ${db_eda_env}.target_table
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SELECT
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-- 业务字段
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dept_name,
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category_name,
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record_count,
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unique_users,
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total_amount,
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avg_amount,
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max_amount,
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-- 技术字段
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NOW() AS etl_time, -- 数据加工时间
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'${day_id}' AS stat_date -- 统计日期
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FROM ${db_tmp_env}.tmp_xxx_03;
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-- ============================================================================
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-- 关键规则说明
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-- ============================================================================
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/*
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1. 禁止使用 CTE (WITH 子句)
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- 每个步骤必须物化为临时表
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- 原因：便于调试、断点续跑、统一编码规范
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2. 先 DROP 再 CREATE
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- 每个临时表创建前必须先 DROP TABLE IF EXISTS
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- 原因：防止表已存在导致失败
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3. Doris 写入方式
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- 默认使用 INSERT INTO
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- Aggregate Key 表：自动合并相同 Key 的数据
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- Unique Key 表：自动按主键去重，保留最新数据
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- Doris 2.0+ 也支持 INSERT OVERWRITE
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4. 过滤条件前置
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- 所有过滤在最早阶段应用
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- 减少中间数据量
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5. 临时表命名规范
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- 格式：tmp_{业务简称}_{步骤序号}
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- 示例：tmp_order_stats_01, tmp_order_stats_02
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6. Doris 特有注意事项
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- 不支持 LEFT SEMI JOIN / LEFT ANTI JOIN
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- 日期函数用 MySQL 风格：DATE_FORMAT, DATE_ADD(INTERVAL)
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- 不支持 collect_list/collect_set，用 GROUP_CONCAT 替代
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*/
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