PIVOT 子句
適用於： 
Databricks SQL Databricks Runtime
藉由將指定數據列清單的唯一值旋轉成不同的數據行，將table_reference的數據列轉換。
語法
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] } [, ...] ) }
參數
-
識別作業的主
PIVOT旨。 -
任何類型的表達式，其中所有數據行參考
table_reference都是聚合函數的自變數。 -
匯總結果的選擇性別名。 如果未指定別名，
PIVOT則根據aggregate_expression產生別名。 column_list
要旋轉的數據行集。
-
的數據行。
table_reference
-
expression_list
將值從
column_list對應至數據行別名。-
具有類型且與個別
column_name共用最不通用型別的常值表達式。每個 Tuple 中的運算式數目必須符合 中的
column_list數目column_names。 -
指定所產生資料行名稱的選擇性別名。 如果未指定
PIVOT別名，則根據expressions 產生別名。
-
結果
下列表單的臨時表：
任何或
column_list中未指定之table_reference之中繼結果集中的所有aggregate_expression數據行。這些數據行會分組數據行。
針對每個
expressionTuple 和aggregate_expression組合，PIVOT產生一個數據行。 類型是的型別aggregate_expression。如果只有一個
aggregate_expression數據行會使用column_alias來命名。 否則，它會命名為column_alias_agg_column_alias。每個儲存格中的值都是使用
FILTER ( WHERE column_list IN (expression, ...)的結果aggregation_expression。
範例
-- 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