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PIVOT cláusula

  • Artigo

Aplica-se a:Marque Sim Databricks SQL Marque Sim Databricks Runtime

Transforma as linhas da referência de tabela ao converter de forma rotativa elementos values únicos de um columnlist especificado em categorias columnsseparadas.

Sintaxe

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] } [, ...] ) }

Parameters

  • table_reference

    Identifica o assunto da PIVOT operação.

  • aggregate_expression

    Uma expressão de qualquer tipo where todas as referências columntable_reference são argumentos para funções agregadas.

  • agg_column_alias

    Um alias opcional para o resultado da agregação. Se nenhum alias for especificado, PIVOT gerará um alias baseado em aggregate_expression.

  • column_list

    O set de columns a ser rodado.

  • expression_list

    Mapeia values de column_list para column aliases.

    • expressão

      Uma expressão literal com um tipo que shares um tipo menos comum com o respetivo column_name.

      O número de expressões em cada tupla deve corresponder ao número de column_names in column_list.

    • column_alias

      Um alias opcional que especifica o nome do columngerado . Se nenhum alias for especificado PIVOT , gerará um alias baseado no expressions.

Result

Uma table temporária da seguinte forma:

  • Todos os columns do resultado intermédio set dos table_reference que não foram especificados em nenhuma aggregate_expression ou column_list.

    Estes columns estão agrupados columns.

  • Para cada tupla expression e combinação aggregate_expression, PIVOT gera uma column. O tipo é o tipo de aggregate_expression.

    Se houver apenas um aggregate_expression o column é nomeado usando column_alias. Caso contrário, é nomeado column_alias_agg_column_alias.

    O valor em cada célula é o resultado do uso de aggregation_expression um FILTER ( WHERE column_list IN (expression, ...)arquivo .

Exemplos

-- 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;
 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;
 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