数据：
CREATE TABLE test (
id SERIAL PRIMARY KEY NOT NULL,range DATERANGE
);
INSERT INTO test (range) VALUES
(DATERANGE('2015-01-01','2015-01-05')),(DATERANGE('2015-01-01','2015-01-03')),(DATERANGE('2015-01-03','2015-01-06')),(DATERANGE('2015-01-07','2015-01-09')),(DATERANGE('2015-01-08',(DATERANGE('2015-01-12',NULL)),(DATERANGE('2015-01-10','2015-01-12')),'2015-01-12'));
表看起来像：
id | range ----+------------------------- 1 | [2015-01-01,2015-01-05) 2 | [2015-01-01,2015-01-03) 3 | [2015-01-03,2015-01-06) 4 | [2015-01-07,2015-01-09) 5 | [2015-01-08,2015-01-09) 6 | [2015-01-12,) 7 | [2015-01-10,2015-01-12) 8 | [2015-01-10,2015-01-12) (8 rows)
期望的结果：
combined -------------------------- [2015-01-01,2015-01-06) [2015-01-07,2015-01-09) [2015-01-10,)
视觉表现：
1 | ===== 2 | === 3 | === 4 | == 5 | = 6 | =============> 7 | == 8 | == --+--------------------------- | ====== == ===============>
>无需区分无穷大和开放上限(上限(范围)IS NULL). (你可以用任何一种方式,但这种方式更简单.)
> NULL vs. infinity in PostgreSQL range types
>由于date是离散类型,因此所有范围都具有default [)边界.
Per documentation:
The built-in range types
int4range,int8range,anddaterangeall use a
canonical form that includes the lower bound and excludes the upper
bound; that is,[).
对于其他类型(如tsrange！),如果可能,我会强制执行相同的操作：
> Preventing adjacent/overlapping entries with EXCLUDE in PostgreSQL
纯SQL解决方案
为了清楚起见,CTE：
WITH a AS ( SELECT range,COALESCE(lower(range),'-infinity') AS startdate,max(COALESCE(upper(range),'infinity')) OVER (ORDER BY range) AS enddate FROM test ),b AS ( SELECT *,lag(enddate) OVER (ORDER BY range) < startdate OR NULL AS step FROM a ),c AS ( SELECT *,count(step) OVER (ORDER BY range) AS grp FROM b ) SELECT daterange(min(startdate),max(enddate)) AS range FROM c GROUP BY grp ORDER BY 1;
或者,与子查询相同,更快但不太容易阅读：
SELECT daterange(min(startdate),max(enddate)) AS range
FROM (
SELECT *,count(step) OVER (ORDER BY range) AS grp
FROM (
SELECT *,lag(enddate) OVER (ORDER BY range) < startdate OR NULL AS step
FROM (
SELECT range,'infinity')) OVER (ORDER BY range) AS enddate
FROM test
) a
) b
) c
GROUP BY grp
ORDER BY 1;
或者使用少一个子查询级别,但翻转排序顺序：
SELECT daterange(min(COALESCE(lower(range),'-infinity')),count(nextstart > enddate OR NULL) OVER (ORDER BY range DESC NULLS LAST) AS grp
FROM (
SELECT range,'infinity')) OVER (ORDER BY range) AS enddate,lead(lower(range)) OVER (ORDER BY range) As nextstart
FROM test
) a
) b
GROUP BY grp
ORDER BY 1;
>使用ORDER BY范围DESC NULLS LAST(使用NULLS LAST)在第二步中对窗口进行排序,以获得完全颠倒的排序顺序.这应该更便宜(更容易生成,完全匹配建议索引的排序顺序),并且对于具有等级IS NULL的角落情况是准确的.
> PostgreSQL sort by datetime asc,null first?
说明
a：按范围排序时,使用窗口函数计算上限(enddate)的运行最大值.
用/ – 无穷大替换NULL边界(无界)只是为了简化(没有特殊的NULL情况).
b：在相同的排序顺序中,如果前一个enddate早于startdate,我们有一个间隙并开始一个新的范围(步骤).
请记住,上限始终被排除在外.
c：通过使用另一个窗口函数计算步骤来形成组(grp).
在外部SELECT构建范围从每个组的下限到上限.瞧.
关于SO的密切相关答案有更多解释：
> Compare multiple date ranges
用plpgsql编写程序解决方案
适用于任何表/列名称,但仅适用于类型daterange.
带循环的程序解决方案通常较慢,但在这种特殊情况下,我希望功能大大加快,因为它只需要一次顺序扫描：
CREATE OR REPLACE FUNCTION f_range_agg(_tbl text,_col text)
RETURNS SETOF daterange AS
$func$
DECLARE
_lower date;
_upper date;
_enddate date;
_startdate date;
BEGIN
FOR _lower,_upper IN EXECUTE
format($$SELECT COALESCE(lower(t.%2$I),'-infinity') -- replace NULL with ...,COALESCE(upper(t.%2$I),'infinity') -- ... +/- infinity
FROM %1$I t
ORDER BY t.%2$I$$,_tbl,_col)
LOOP
IF _lower > _enddate THEN -- return previous range
RETURN NEXT daterange(_startdate,_enddate);
SELECT _lower,_upper INTO _startdate,_enddate;
ELSIF _upper > _enddate THEN -- expand range
_enddate := _upper;
-- do nothing if _upper <= _enddate (range already included) ...
ELSIF _enddate IS NULL THEN -- init 1st round
SELECT _lower,_enddate;
END IF;
END LOOP;
IF FOUND THEN -- return last row
RETURN NEXT daterange(_startdate,_enddate);
END IF;
END
$func$ LANGUAGE plpgsql;
呼叫：
SELECT * FROM f_range_agg('test','range'); -- table and column name
逻辑类似于SQL解决方案,但我们可以通过单次传递来完成.
有关：
> GROUP BY and aggregate sequential numeric values
在动态SQL中处理用户输入的常用练习：
> SQL injection in Postgres functions vs prepared queries
指数
对于这些解决方案中的每一个,范围上的普通(默认)btree索引将有助于大表中的性能：
CREATE INDEX foo on test (range);
A btree index is of limited use for range types,但我们可以获得预先排序的数据,甚至可以进行仅索引扫描.
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