I have a table like this:
Products
(
ID int not null primary key,
Type int not null,
Route varchar(20) null
)
I have a list on the client in this format:
Type=1, Percent=0.4, Route=A
Type=1, Percent=0.4, Route=B
Type=1, Percent=0.2, Route=C
Type=2, Percent=0.5, Route=A
Type=2, Percent=0.5, Route=B
Type=3, Percent=1.0, Route=C
...etc
When done, I'd like to assign 40% of type 1 products to Route A, 40% to Route B and 20% to Route C. Then 50% of type 2 products to Route A and 50% of type 2 products to Route B, etc.
Is there some way to do this in a single update statement?
If not in one giant statement, can it be done in one statement per type or one statement per route? As currently we're doing one per type+route any of the above would be an improvement.
Here's an Oracle statement that I prepared before you posted that you were using SQL-Server, but it might give you some ideas, though you will have to roll your own ratio_to_report analytic function using CTE and self-joins. We calculate the cumulative proportion of each type in the products and client route tables and do a non equi-join on the matching proportion bands. The sample data I have used has some round-offs but these will reduce for larger data sets.
Here's the setup:
create table products (id int not null primary key, "type" int not null, route varchar (20) null);
create table clienttable ( "type" int not null, percent number (10, 2) not null, route varchar (20) not null);
insert into clienttable ("type", percent, route) values (1, 0.4, 'A');
insert into clienttable ("type", percent, route) values (1, 0.4, 'B');
insert into clienttable ("type", percent, route) values (1, 0.2, 'C');
insert into clienttable ("type", percent, route) values (2, 0.5, 'A');
insert into clienttable ("type", percent, route) values (2, 0.5, 'B');
insert into clienttable ("type", percent, route) values (3, 1.0, 'C');
insert into products (id, "type", route) values (1, 1, null);
insert into products (id, "type", route) values (2, 1, null);
insert into products (id, "type", route) values (3, 1, null);
insert into products (id, "type", route) values (4, 1, null);
insert into products (id, "type", route) values (5, 1, null);
insert into products (id, "type", route) values (6, 1, null);
insert into products (id, "type", route) values (7, 1, null);
-- 7 rows for product type 1 so we will expect 3 of route A, 3 of route B, 1 of route C (rounded)
insert into products (id, "type", route) values (8, 2, null);
insert into products (id, "type", route) values (9, 2, null);
insert into products (id, "type", route) values (10, 2, null);
insert into products (id, "type", route) values (11, 2, null);
insert into products (id, "type", route) values (12, 2, null);
-- 5 rows for product type 2 so we will expect 3 of route A and 2 of route B (rounded)
insert into products (id, "type", route) values (13, 3, null);
insert into products (id, "type", route) values (14, 3, null);
-- 2 rows for product type 3 so we will expect 2 of route C
and here's the statement
select prods.id, prods."type", client.route cr from
(
select
p.id,
p."type",
row_number () over (partition by p."type" order by p.id) / count (*) over (partition by p."type") cum_ratio
from
products p
) prods
inner join
(
select "type", route, nvl (lag (cum_ratio, 1) over (partition by "type" order by route), 0) ratio_start, cum_ratio ratio_end from
(select "type", route, sum (rr) over (partition by "type" order by route) cum_ratio
from (select c."type", c.route, ratio_to_report (c.percent) over (partition by "type") rr from clienttable c))) client
on prods."type" = client."type"
and prods.cum_ratio >= client.ratio_start and prods.cum_ratio < client.ratio_end
This gives the following result:-
+----+------+----+
| ID | type | CR |
+----+------+----+
| 1 | 1 | A |
| 2 | 1 | A |
| 3 | 1 | B |
| 4 | 1 | B |
| 5 | 1 | B |
| 6 | 1 | C |
| 8 | 2 | A |
| 9 | 2 | A |
| 10 | 2 | B |
| 11 | 2 | B |
| 13 | 3 | C |
+----+------+----+
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