Klauzula PIVOT

Artykuł
03/01/2024

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Przekształca wiersze table_reference , obracając unikatowe wartości określonej listy kolumn na oddzielne kolumny.

Składni

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] } [, ...] ) }

Parametry

table_reference

Identyfikuje temat PIVOT operacji.
aggregate_expression

Wyrażenie dowolnego typu, w którym wszystkie odwołania do kolumn są argumentami table_referencefunkcji agregujących.
agg_column_alias

Opcjonalny alias wyniku agregacji. Jeśli alias nie zostanie określony, PIVOT wygeneruje alias na podstawie .aggregate_expression
Column_list

Zestaw kolumn do obrócenia.
- Column_name
  
  Kolumna z table_reference.
expression_list

Mapuje wartości z column_list do aliasów kolumn.
- Wyrażenie
  
  Wyrażenie literału z typem, który współudzieli najmniej wspólny typ z odpowiednim column_nametypem .
  
  Liczba wyrażeń w każdej krotki musi być zgodna z column_names liczbą w column_list.
- column_alias
  
  Opcjonalny alias określający nazwę wygenerowanej kolumny. Jeśli nie określono PIVOT aliasu, zostanie wygenerowany alias na podstawie parametru expressions.

Wynik

Tabela tymczasowa następującego formularza:

Wszystkie kolumny z zestawu table_reference wyników pośrednich, które nie zostały określone w żadnym aggregate_expression zestawie lub column_list.

Te kolumny grupują kolumny.
Dla każdej expression krotki i aggregate_expression kombinacji PIVOT generuje jedną kolumnę. Typ jest typem aggregate_expression.

Jeśli istnieje tylko jedna aggregate_expression kolumna o nazwie , użyj polecenia column_alias. W przeciwnym razie nazwa column_alias_agg_column_aliasto .

Wartość w każdej komórce jest wynikiem aggregation_expression użycia obiektu FILTER ( WHERE column_list IN (expression, ...).

Przykłady

-- 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) = (1, 'east')) AS q1_east,
    sum(sales) FILTER(WHERE (quarter, region) = (1, 'west')) AS q1_west,
    sum(sales) FILTER(WHERE (quarter, region) = (2, 'east')) AS q2_east,
    sum(sales) FILTER(WHERE (quarter, region) = (2, 'west')) AS q2_west,
    sum(sales) FILTER(WHERE (quarter, region) = (3, 'east')) AS q3_east,
    sum(sales) FILTER(WHERE (quarter, region) = (3, 'west')) AS q3_west,
    sum(sales) FILTER(WHERE (quarter, region) = (4, 'east')) AS q4_east,
    sum(sales) FILTER(WHERE (quarter, region) = (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

Klauzula PIVOT

Składni

Parametry

Wynik

Przykłady

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