中级聚合函数

Snowflake 中的数据管道自动化

Emily Melhuish

Technical Curriculum Developer, Snowflake

运算顺序

运算顺序.png

SQL 的执行顺序与书写顺序不同

行：构建数据集
分组：汇总
结果：整理输出

¹ * Snowflake 学习资料

常用聚合函数

COUNT(*) / COUNT(DISTINCT col) —— 总行数；唯一值数
SUM —— 列总和
AVG —— 平均值
MIN / MAX —— 范围

SELECT COUNT(*) AS total_shipments,
       COUNT(DISTINCT carrier_id) AS unique_carriers,
       SUM(delivery_days) AS total_days,
       AVG(delivery_days) AS avg_days
FROM shipments;

多条查询的问题

按区域与仓库返回用量

SELECT 
region
, warehouse_name
, SUM(credits_used) 
FROM usage 
GROUP BY region, warehouse_name;

按区域返回小计

SELECT region
, SUM(credits_used) 
FROM usage GROUP BY region;

返回总用量

SELECT 
SUM(credits_used) 
FROM usage;

GROUPING SETS

输入

SELECT region
, warehouse_name
, SUM(credits_used) AS total 
FROM usage 
GROUP BY GROUPING SETS ( 
  (region, warehouse_name)
  , (region)
  , () 
);

输出

REGION	WAREHOUSE_NAME	TOTAL
EMEA	harbr_wh_prod	1240.50
EMEA	harbr_wh_dev	380.00
EMEA	NULL	1620.50
APAC	harbr_wh_prod	890.25
APAC	NULL	890.25
NULL	NULL	2510.75

注意：通过 CASE 语句为 NULL 增加含义

ROLLUP

输入

SELECT 
region
, warehouse_name
, SUM(credits_used) AS total 
FROM usage 
GROUP BY ROLLUP (region, warehouse_name);

输出

REGION	WAREHOUSE_NAME	TOTAL
EMEA	harbr_wh_prod	1240.50
EMEA	harbr_wh_dev	380.00
EMEA	NULL	1620.50
APAC	harbr_wh_prod	890.25
APAC	NULL	890.25
NULL	NULL	2510.75

CUBE

输入

SELECT 
region
, warehouse_name
, SUM(credits_used) AS total
FROM usage 
GROUP BY CUBE (region, warehouse_name);

输出

REGION	WAREHOUSE_NAME	TOTAL
EMEA	harbr_wh_prod	1240.50
EMEA	harbr_wh_dev	380.00
EMEA	NULL	1620.50
APAC	harbr_wh_prod	890.25
APAC	NULL	890.25	}
NULL	harbr_wh_prod	2130.75
NULL	harbr_wh_dev	380.00
NULL	NULL	2510.75

GROUPING() 与 GROUPING_ID()

SELECT region, warehouse_name, SUM(credits_used) AS total_credits, GROUPING(region) AS is_region_agg, GROUPING(warehouse_name) AS is_wh_agg , 
GROUPING_ID(region, warehouse_name) AS grouping_level 
FROM usage 
GROUP BY ROLLUP (region, warehouse_name);

Markdown 表格输出的截图

Vamos praticar!

Snowflake 中的数据管道自动化