PIVOT 子句
适用于: Databricks SQL Databricks Runtime
通过将指定列列表的唯一值轮换到单独的列中,转换 table_reference 的行。
语法
table_reference PIVOT ( { aggregate_expression [ [ AS ] agg_column_alias ] } [, ...]
FOR column_list IN ( expression_list ) )
column_list
{ column_name |
( column_name [, ...] ) }
expression_list
{ expression [ AS ] [ column_alias ] |
{ ( expression [, ...] ) [ AS ] [ column_alias] } [, ...] ) }
参数
-
标识
PIVOT
操作的主题。 -
任何类型的表达式,其中的所有列引用
table_reference
都是聚合函数的参数。 -
聚合结果的可选别名。 如果未指定别名,
PIVOT
会根据aggregate_expression
生成别名。 column_list
要轮换的列集。
-
来自
table_reference
的列。
-
expression_list
将
column_list
中的值映射到列别名。-
一种文本表达式,它与相应的
column_name
都使用一个最不常见的类型。每个元组中表达式的数量必须与
column_list
中column_names
的数量匹配。 column_alias
一个可选别名,用于指定生成的列的名称。 如果未指定别名,
PIVOT
会根据expression
生成别名。
-
结果
采用以下形式的临时表:
table_reference
的中间结果集中尚未在任何aggregate_expression
或column_list
中指定的所有列。这些列是分组列。
对于每个
expression
元组和aggregate_expression
组合,PIVOT
都会生成一列。 类型为aggregate_expression
的类型。如果只有一个
aggregate_expression
,则使用column_alias
命名该列。 否则,使用column_alias_agg_column_alias
命名。每个单元格中的值是使用
FILTER ( WHERE column_list IN (expression, ...)
的aggregation_expression
的结果。
示例
-- A very basic PIVOT
-- Given a table with sales by quarter, return a table that returns sales across quarters per year.
> CREATE TEMP VIEW sales(year, quarter, region, sales) AS
VALUES (2018, 1, 'east', 100),
(2018, 2, 'east', 20),
(2018, 3, 'east', 40),
(2018, 4, 'east', 40),
(2019, 1, 'east', 120),
(2019, 2, 'east', 110),
(2019, 3, 'east', 80),
(2019, 4, 'east', 60),
(2018, 1, 'west', 105),
(2018, 2, 'west', 25),
(2018, 3, 'west', 45),
(2018, 4, 'west', 45),
(2019, 1, 'west', 125),
(2019, 2, 'west', 115),
(2019, 3, 'west', 85),
(2019, 4, 'west', 65);
> SELECT year, region, q1, q2, q3, q4
FROM sales
PIVOT (sum(sales) AS sales
FOR quarter
IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
2018 east 100 20 40 40
2019 east 120 110 80 60
2018 west 105 25 45 45
2019 west 125 115 85 65
-- The same query written without PIVOT
> SELECT year, region,
sum(sales) FILTER(WHERE quarter = 1) AS q1,
sum(sales) FILTER(WHERE quarter = 2) AS q2,
sum(sales) FILTER(WHERE quarter = 3) AS q2,
sum(sales) FILTER(WHERE quarter = 4) AS q4
FROM sales
GROUP BY year, region;
2018 east 100 20 40 40
2019 east 120 110 80 60
2018 west 105 25 45 45
2019 west 125 115 85 65
-- Also PIVOT on region
> SELECT year, q1_east, q1_west, q2_east, q2_west, q3_east, q3_west, q4_east, q4_west
FROM sales
PIVOT (sum(sales) AS sales
FOR (quarter, region)
IN ((1, 'east') AS q1_east, (1, 'west') AS q1_west, (2, 'east') AS q2_east, (2, 'west') AS q2_west,
(3, 'east') AS q3_east, (3, 'west') AS q3_west, (4, 'east') AS q4_east, (4, 'west') AS q4_west));
2018 100 105 20 25 40 45 40 45
2019 120 125 110 115 80 85 60 65
-- The same query written without PIVOT
> SELECT year,
sum(sales) FILTER(WHERE (quarter, region) IN ((1, 'east'))) AS q1_east,
sum(sales) FILTER(WHERE (quarter, region) IN ((1, 'west'))) AS q1_west,
sum(sales) FILTER(WHERE (quarter, region) IN ((2, 'east'))) AS q2_east,
sum(sales) FILTER(WHERE (quarter, region) IN ((2, 'west'))) AS q2_west,
sum(sales) FILTER(WHERE (quarter, region) IN ((3, 'east'))) AS q3_east,
sum(sales) FILTER(WHERE (quarter, region) IN ((3, 'west'))) AS q3_west,
sum(sales) FILTER(WHERE (quarter, region) IN ((4, 'east'))) AS q4_east,
sum(sales) FILTER(WHERE (quarter, region) IN ((4, 'west'))) AS q4_west
FROM sales
GROUP BY year, region;
2018 100 105 20 25 40 45 40 45
2019 120 125 110 115 80 85 60 65
-- To aggregate across regions the column must be removed from the input.
> SELECT year, q1, q2, q3, q4
FROM (SELECT year, quarter, sales FROM sales) AS s
PIVOT (sum(sales) AS sales
FOR quarter
IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
2018 205 45 85 85
2019 245 225 165 125
-- The same query without PIVOT
> SELECT year,
sum(sales) FILTER(WHERE quarter = 1) AS q1,
sum(sales) FILTER(WHERE quarter = 2) AS q2,
sum(sales) FILTER(WHERE quarter = 3) AS q3,
sum(sales) FILTER(WHERE quarter = 4) AS q4
FROM sales
GROUP BY year;
-- A PIVOT with multiple aggregations
> SELECT year, q1_total, q1_avg, q2_total, q2_avg, q3_total, q3_avg, q4_total, q4_avg
FROM (SELECT year, quarter, sales FROM sales) AS s
PIVOT (sum(sales) AS total, avg(sales) AS avg
FOR quarter
IN (1 AS q1, 2 AS q2, 3 AS q3, 4 AS q4));
2018 205 102.5 45 22.5 85 42.5 85 42.5
2019 245 122.5 225 112.5 165 82.5 125 62.5
-- The same query without PIVOT
> SELECT year,
sum(sales) FILTER(WHERE quarter = 1) AS q1_total,
avg(sales) FILTER(WHERE quarter = 1) AS q1_avg,
sum(sales) FILTER(WHERE quarter = 2) AS q2_total,
avg(sales) FILTER(WHERE quarter = 2) AS q2_avg,
sum(sales) FILTER(WHERE quarter = 3) AS q3_total,
avg(sales) FILTER(WHERE quarter = 3) AS q3_avg,
sum(sales) FILTER(WHERE quarter = 4) AS q4_total,
avg(sales) FILTER(WHERE quarter = 4) AS q4_avg
FROM sales
GROUP BY year;
> CREATE TEMP VIEW person (id, name, age, class, address) AS
VALUES (100, 'John', 30, 1, 'Street 1'),
(200, 'Mary', NULL, 1, 'Street 2'),
(300, 'Mike', 80, 3, 'Street 3'),
(400, 'Dan', 50, 4, 'Street 4');
2018 205 102.5 45 22.5 85 42.5 85 42.5
2019 245 122.5 225 112.5 165 82.5 125 62.5