PIVOT 절

적용 대상: Databricks SQL Databricks Runtime

지정된 열 목록의 고유 값을 별도의 열로 회전하여 이전 table_reference 행을 변환합니다.

구문

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] } [, ...] ) }

매개 변수

• aggregate_expression

  모든 열 참조가집계 함수를 인수인 모든 형식의 식입니다.

• agg_column_alias

  집계 결과에 대한 선택적 별칭입니다. 별칭이 지정되지 않은 경우 PIVOT은 aggregate_expression을 기반으로 별칭을 생성합니다.

• column_list

  회전할 열 집합입니다.

  • column_name

    table_reference열입니다.

• expression_list

  column_list 값을 열 별칭에 매핑합니다.

  • expression

    해당 리터럴 식은 column_name와 최소 공통 형식을 공유하는 형식을 가지고 있습니다.

    각 튜플의 식 수는 column_names에서 column_list의 수와 일치해야 합니다.

  • column_alias

    생성된 열의 이름을 지정하는 선택적 별칭입니다. 별칭이 지정되지 않은 경우 PIVOT은 expression을 기반으로 별칭을 생성합니다.

결과

다음 형식의 임시 테이블입니다.

• table_reference 중간 결과 집합의 모든 열 중 aggregate_expression 또는 column_list에 지정되지 않은 열입니다.

  이러한 열은 그룹화용 열입니다.

• 각 expression 튜플 및 aggregate_expression 조합에 대해 PIVOT 하나의 열을 생성합니다. 형식은 aggregate_expression의 형식입니다.

  aggregate_expression 하나만 있는 경우 column_alias사용하여 열의 이름을 지정합니다. 그렇지 않으면 column_alias_agg_column_alias로 이름이 지정됩니다.

  각 셀의 값은 aggregation_expression을 사용하는 FILTER ( WHERE column_list IN (expression, ...)의 결과입니다.

예제

-- 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

관련된 문서

• SELECT
• 집계 함수
• UNPIVOT 절