您可能需要计算索引.
让我们创建一个表:
create table sales(day date, amount real);
然后用一些随机的东西填满它:
insert into sales
select current_date + s.a as day, random()*100 as amount
from generate_series(1,20);
按天编制索引,这里没有什么特别之处:
create index sales_by_day on sales(day);
创建行位置函数.还有其他方法,这是最简单的方法:
create or replace function sales_pos (date) returns bigint
as 'select count(day) from sales where day <= $1;'
language sql immutable;
判断它是否有效(但不要在大型数据集上这样称呼它):
select sales_pos(day), day, amount from sales;
sales_pos | day | amount
-----------+------------+----------
1 | 2011-07-08 | 41.6135
2 | 2011-07-09 | 19.0663
3 | 2011-07-10 | 12.3715
..................
现在是棘手的部分:添加另一个根据Sales_pos函数值计算的索引:
create index sales_by_pos on sales using btree(sales_pos(day));
下面是你如何使用它.5是你的"补偿",10是"限制":
select * from sales where sales_pos(day) >= 5 and sales_pos(day) < 5+10;
day | amount
------------+---------
2011-07-12 | 94.3042
2011-07-13 | 12.9532
2011-07-14 | 74.7261
...............
它很快,因为当您这样调用它时,postgres使用索引中的预先计算的值:
explain select * from sales
where sales_pos(day) >= 5 and sales_pos(day) < 5+10;
QUERY PLAN
--------------------------------------------------------------------------
Index Scan using sales_by_pos on sales (cost=0.50..8.77 rows=1 width=8)
Index Cond: ((sales_pos(day) >= 5) AND (sales_pos(day) < 15))
希望有帮助.