0

I have three tables:

Value v

+-------------------------------+
| Owner | Location |    Value   |
+-------------------------------+
|Bob    |    A1    |    0.25    |
|Bob    |    B4    |    0.10    |
|Dale   |    Z3    |    0.50    |
|Dale   |    A1    |    0.25    |
|Rick   |    B4    |    0.10    |
|Rick   |    Z3    |    0.50    |
+-------------------------------+

PurchasePercentage p

+-------------------------------+
| Buyer | Location | Percentage |
+-------------------------------+
|Bill   |    A1    |    0.10    |
|Bill   |    B4    |    0.20    |
|Kyle   |    Z3    |    0.30    |
|Kyle   |    A1    |    0.50    |
|Jan    |    B4    |    0.15    |
|Jan    |    Z3    |    0.25    |
+-------------------------------+

Buyout b

+------------------+
| Owner |   Buyer  |
+------------------+
|Bob    |   Bill   |
|Bob    |   Kyle   |
|Dale   |   Jan    |
|Dale   |   Bill   |
|Rick   |   Kyle   |
|Rick   |   Jan    |
+------------------+

What I'm looking for is a fourth table:

PossibleBuyouts

+--------------------------------+
| Owner |   Buyer  |  BuyoutCost |
+--------------------------------+

based on the transactions laid out in the Buyout table
where BuyoutCost is the SUM of v.Value * p.Percentage
for each distinct Location
the Buyer and Owner have in common.

So these examples would return a PossibleBuyouts table of 

+--------------------------------+
| Owner |   Buyer  |  BuyoutCost |
+--------------------------------+
|Bob    |   Bill   |    0.045    |
|Bob    |   Kyle   |    0.125    |
|Dale   |   Jan    |    0.125    |
|Dale   |   Bill   |    0.025    |
|Rick   |   Kyle   |    0.150    |
|Rick   |   Jan    |    0.140    |
+--------------------------------+

Laying out the first row as an example, the math works out like this:

-Bob and Bill both have Locations A1 and B4 in common
-Bob's ownership value for A1 is 0.25 and Bill wants 0.10 percent
-the cost for A1 would be (0.25*0.10) = 0.025
-Bob's ownership value for B4 is 0.10 and Bill wants 0.20 percent
-the cost for B4 would be (0.10*0.20) = 0.020
-Sum(0.025 + 0.020) = the BuyoutCost of 0.045.

If you could help me out, I'm looking for the most efficient way to do this - whether it's multiple queries, one query with a bunch of subqueries, whatever should take the least amount of time.

There are ~1500 different owners, ~1000 different buyers and ~500 different locations, so the number of potential combinations leads to looooooong query times. What do you think will be the fastest way to do this? Everything is indexed and the data pared down to the smallest size I can get it to.

4

1 回答 1

0

我建议您创建一个使用游标来完成目标的过程。遍历三个表之一，这应该是一个非常简单的过程。

MySQL 游标：http ://dev.mysql.com/doc/refman/5.0/en/cursors.html

编辑：以下存储的 MySQL 脚本创建并调用正确再现您正在寻找的结果的存储过程：

DELIMITER $$

DROP PROCEDURE IF EXISTS `computeBuyouts` $$
CREATE PROCEDURE `computeBuyouts` ()
BEGIN
DECLARE done INT DEFAULT FALSE;
DECLARE o, b VARCHAR(32);
DECLARE bc FLOAT;
DECLARE cur CURSOR FOR SELECT Owner,Buyer FROM Buyout;
DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = TRUE;

OPEN cur;

read_loop: LOOP
  FETCH cur INTO o, b;
  IF done THEN
    LEAVE read_loop;
  END IF;

  SET bc = 0;
  -- compute the sum of products of each value/percentage pair for all locations 
  SELECT SUM(v.Value * pp.Percentage) INTO bc FROM Value v LEFT JOIN (PurchasePercentage pp) ON (v.Location = pp.Location) where v.Owner = o and pp.Buyer = b group by v.Owner;

  INSERT INTO PossibleBuyouts VALUES (o, b, bc);

END LOOP;

CLOSE cur;

END $$

DELIMITER ;

CALL computeBuyouts();

希望有帮助。在您提到的表格大小下，这应该非常快地完成。

于 2013-07-28T02:25:28.030 回答