Add one-skill

one-skill/smart-data-developer/references/sql/templates/doris/insert-template.sql

@@ -0,0 +1,147 @@
+-- =====================================================================
+-- @Name:             DORIS-D-SQL-{表名}-INSERT
+-- @Version:          1.0
+-- @Desc:             Apache Doris 数据插入模板
+-- @TargetDatabase:   Apache Doris
+-- =====================================================================
+
+-- ============================================================================
+-- 场景1：INSERT INTO（追加写入）
+-- ============================================================================
+-- 适用：向 Doris 表追加数据，不会删除已有数据
+
+INSERT INTO db_name.target_table
+SELECT 
+    stat_date,
+    department,
+    region,
+    order_count,
+    total_amount
+FROM db_name.source_table
+WHERE stat_date = '${day_id}';
+
+-- ============================================================================
+-- 场景2：INSERT OVERWRITE（覆盖写入）
+-- ============================================================================
+-- 适用：覆盖目标表（或指定分区）的全部数据
+-- 注意：Doris 2.0+ 支持，且仅适用于 Partition 表
+
+-- 覆盖整表
+INSERT OVERWRITE db_name.target_table
+SELECT 
+    stat_date,
+    department,
+    region,
+    order_count,
+    total_amount
+FROM db_name.source_table;
+
+-- 覆盖指定分区（推荐）
+INSERT OVERWRITE db_name.target_table
+PARTITION(p202605)
+SELECT 
+    department,
+    region,
+    order_count,
+    total_amount
+FROM db_name.source_table
+WHERE stat_date >= '2026-05-01'
+  AND stat_date < '2026-06-01';
+
+-- ============================================================================
+-- 场景3：从查询结果写入（ETL 场景）
+-- ============================================================================
+
+-- 简单转换后写入
+INSERT INTO db_name.target_table
+SELECT 
+    order_date,
+    department,
+    COUNT(*) AS order_count,
+    COUNT(DISTINCT user_id) AS unique_users,
+    SUM(total_amount) AS total_amount,
+    AVG(total_amount) AS avg_amount
+FROM db_name.source_orders o
+LEFT JOIN db_name.dim_department d ON o.dept_id = d.dept_id
+WHERE o.order_date = '${day_id}'
+GROUP BY order_date, department;
+
+-- ============================================================================
+-- 场景4：批量 VALUES 写入
+-- ============================================================================
+
+INSERT INTO db_name.target_table (stat_date, department, amount)
+VALUES 
+    ('2026-05-01', '市场部', 10000.00),
+    ('2026-05-01', '技术部', 25000.00),
+    ('2026-05-01', '运营部', 18000.00);
+
+-- ============================================================================
+-- 场景5：Stream Load（数据导入）
+-- ============================================================================
+-- 适用：大批量数据导入（百万级以上）
+-- 注意：Stream Load 通过 HTTP 协议提交，不是 SQL 语法
+
+/*
+-- curl 命令示例
+curl --location-trusted -u user:password \
+    -H "label:load_order_20260501" \
+    -H "column_separator:," \
+    -H "columns:order_id,order_date,user_id,total_amount" \
+    -T data.csv \
+    http://fe_host:8030/api/db_name/orders/_stream_load
+*/
+
+-- ============================================================================
+-- 场景6：Broker Load（外部数据源导入）
+-- ============================================================================
+
+/*
+LOAD LABEL db_name.load_label_20260501
+(
+    DATA INFILE('hdfs://namenode:8020/path/to/data/*')
+    INTO TABLE target_table
+    COLUMNS TERMINATED BY ','
+    (stat_date, department, region, amount)
+    SET (amount = amount * 1.0)
+)
+WITH BROKER 'broker_name'
+(
+    'username' = 'hdfs_user',
+    'password' = 'hdfs_password'
+)
+PROPERTIES
+(
+    'timeout' = '3600',
+    'max_filter_ratio' = '0.01'
+);
+*/
+
+-- ============================================================================
+-- 关键规则说明
+-- ============================================================================
+/*
+1. INSERT INTO vs INSERT OVERWRITE
+   - INSERT INTO：追加数据，不删除已有数据
+   - INSERT OVERWRITE：覆盖数据（Doris 2.0+ 支持）
+   - 日常增量推荐 INSERT INTO，全量刷新推荐 INSERT OVERWRITE
+
+2. Doris 不使用临时表链式处理
+   - 与 Spark 不同，Doris 通常用单条 SQL 或 CTE 完成 ETL
+   - 直接 INSERT INTO ... SELECT ... 即可
+
+3. 字段顺序
+   - SELECT 字段顺序必须与目标表列定义顺序一致
+   - 或显式指定列名：INSERT INTO table (col1, col2) SELECT ...
+
+4. 数据导入方式选择
+   - 少量数据：INSERT INTO ... SELECT ... 或 INSERT INTO ... VALUES ...
+   - 大批量导入：Stream Load（HTTP PUT，最高性能）
+   - HDFS 导入：Broker Load
+   - 外部数据源：Routine Load（Kafka 等）
+
+5. 性能建议
+   - 批量写入优于逐条写入
+   - Stream Load 是最高性能的导入方式
+   - 建议攒批后一次性写入，避免频繁小批量导入
+*/