PIVOT-clausule
Van toepassing op: Databricks SQL
Databricks Runtime
Transformeert de rijen van de voorgaande table_reference door unieke waarden van een opgegeven kolomlijst te draaien in afzonderlijke kolommen.
Syntaxis
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
-
Een expressie van elk type waarvan alle kolomverwijzingen
table_reference
argumenten zijn voor statistische functies. -
Een optionele alias voor het resultaat van de aggregatie. Als er geen alias is opgegeven,
PIVOT
genereert u een alias opaggregate_expression
basis van . column_list
De verzameling kolommen die moeten worden gedraaid.
-
Een kolom uit
table_reference
.
-
expression_list
Hiermee worden waarden van
column_list
toegewezen aan kolomaliassen.-
Een letterlijke expressie met een type dat een minst gangbaar type deelt met de respectieve
column_name
.Het aantal expressies in elke tuple moet overeenkomen met het aantal
column_names
incolumn_list
. -
Een optionele alias die de naam van de gegenereerde kolom opgeeft. Als er geen alias is opgegeven, wordt er een alias gegenereerd
PIVOT
op basis van deexpression
s.
-
Resultaat
Een tijdelijke tabel van het volgende formulier:
Alle kolommen uit de intermediaire resultaatset van
table_reference
die niet zijn opgegeven in eenaggregate_expression
ofcolumn_list
.Dit zijn groeperingskolommen.
Voor elke combinatie van
expression
tuple enaggregate_expression
genereertPIVOT
één kolom. Het type is het typeaggregate_expression
.Als er slechts één
aggregate_expression
is, krijgt de kolom een naam met behulp vancolumn_alias
. Anders heeft het de naamcolumn_alias_agg_column_alias
.De waarde in elke cel is het resultaat van het
aggregation_expression
gebruik van eenFILTER ( WHERE column_list IN (expression, ...)
.
Voorbeelden
-- 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