SQL:选择事务不在同一表内的条件的事务 [英] SQL: Select transactions where rows are not of criteria inside the same table
问题描述
我有一个带有交易记录的表:
Transactions
------------
id | account | type | date_time | amount
----------------------------------------------------
1 | 001 | 'R' | '2012-01-01 10:01:00' | 1000
2 | 003 | 'R' | '2012-01-02 12:53:10' | 1500
3 | 003 | 'A' | '2012-01-03 13:10:01' | -1500
4 | 002 | 'R' | '2012-01-03 17:56:00' | 2000
5 | 001 | 'R' | '2012-01-04 12:30:01' | 1000
6 | 002 | 'A' | '2012-01-04 13:23:01' | -2000
7 | 003 | 'R' | '2012-01-04 15:13:10' | 3000
8 | 003 | 'R' | '2012-01-05 12:12:00' | 1250
9 | 003 | 'A' | '2012-01-06 17:24:01' | -1250
，并且我希望选择所有特定类型('R')的所有内容，但不要立即(按date_time字段的顺序)针对同一帐户提交具有另一种类型('A')的另一笔交易...
因此，在给出前面的示例的情况下，查询应引发以下行:
id | account |type | date | amount
----------------------------------------------------
1 | 001 | 'R' | '2012-01-01 10:01:00' | 1000
5 | 001 | 'R' | '2012-01-04 12:30:01' | 1000
7 | 003 | 'R' | '2012-01-04 15:13:10' | 3000
(如您所见，第2行未显示，因为第3行取消了" ...第4行也被第6行"取消了；第7行出现了(即使帐户003属于已取消帐户)第2行，这一次在第7行中没有被任何"A"行取消；并且第8行也不会出现(对于003帐户来说也是如此，因为现在该帐户被9取消了，也不会取消7，只是上一个:8 ...
我尝试了where子句中的Joins，子查询，但是我真的不确定如何进行查询...
我尝试过的事情:
尝试加入:
SELECT trans.type as type,
trans.amount as amount,
trans.date_time as dt,
trans.account as acct,
FROM Transactions trans
INNER JOIN ( SELECT t.type AS type, t.acct AS acct, t.date_time AS date_time
FROM Transactions t
WHERE t.date_time > trans.date_time
ORDER BY t.date_time DESC
) AS nextTrans
ON nextTrans.acct = trans.acct
WHERE trans.type IN ('R')
AND nextTrans.type NOT IN ('A')
ORDER BY DATE(trans.date_time) ASC
这引发了错误，因为我无法在MySQL的JOIN中引入外部值.
在以下位置尝试子查询
SELECT trans.type as type,
trans.amount as amount,
trans.date_time as dt,
trans.account as acct,
FROM Transactions trans
WHERE trans.type IN ('R')
AND trans.datetime <
( SELECT t.date_time AS date_time
FROM Transactions t
WHERE t.account = trans.account
ORDER BY t.date_time DESC
) AS nextTrans
ON nextTrans.acct = trans.acct
ORDER BY DATE(trans.date_time) ASC
这是错误的，我可以在MySQL的WHERE中引入外部值，但是我无法设法找到正确过滤所需内容的方法...
重要
我设法实现了一个解决方案，但现在需要进行认真的优化.在这里:
SELECT *
FROM (SELECT t1.*, tFlagged.id AS cancId, tFlagged.type AS cancFlag
FROM transactions t1
LEFT JOIN (SELECT t2.*
FROM transactions t2
ORDER BY t2.date_time ASC ) tFlagged
ON (t1.account=tFlagged.account
AND
t1.date_time < tFlagged.date_time)
WHERE t1.type = 'R'
GROUP BY t1.id) tCanc
WHERE tCanc.cancFlag IS NULL
OR tCanc.cancFlag <> 'A'
我自己加入了表格，只是考虑到相同的帐户和不错的date_time. Join按date_time排序.按ID分组，我设法仅获得加入的第一个结果，恰好是同一帐户的下一个交易.
然后在外部选择项上，我将那些具有"A"的项过滤掉，因为这意味着下一个事务实际上是对它的取消.换句话说，如果同一个帐户没有下一笔交易，或者下一笔交易是"R"，则该笔交易不会被取消并且必须在结果中显示...
我知道了:
+----+---------+------+---------------------+--------+--------+----------+
| id | account | type | date_time | amount | cancId | cancFlag |
+----+---------+------+---------------------+--------+--------+----------+
| 1 | 001 | R | 2012-01-01 10:01:00 | 1000 | 5 | R |
| 5 | 001 | R | 2012-01-04 12:30:01 | 1000 | NULL | NULL |
| 7 | 003 | R | 2012-01-04 15:13:10 | 3000 | 8 | R |
+----+---------+------+---------------------+--------+--------+----------+
它将同一笔交易的每笔交易及时与下一笔交易关联起来，然后筛选出已取消的交易...成功！
正如我所说，现在的问题是优化.我的真实数据有很多行(因为期望通过时间来保存事务的表具有)，并且对于现在约10,000行的表，此查询在1分44秒内得到了肯定的结果.我想这就是联接的问题……(对于那些在这里了解协议的人，我应该怎么做?在这里发起一个新问题，并将其发布为该问题的解决方案?或者只是在这里等待更多答案?) /p>
此处是基于嵌套子查询的解决方案.首先，我添加了几行来处理更多案例.例如，事务10不应被事务12取消，因为事务11介于两者之间.
> select * from transactions order by date_time;
+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+
| 1 | 1 | R | 2012-01-01 10:01:00 | 1000 |
| 2 | 3 | R | 2012-01-02 12:53:10 | 1500 |
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 |
| 4 | 2 | R | 2012-01-03 17:56:00 | 2000 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 |
| 8 | 3 | R | 2012-01-05 12:12:00 | 1250 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 |
| 12 | 3 | A | 2012-01-08 00:00:00 | -1250 |
| 14 | 2 | R | 2012-01-09 00:00:00 | 2000 |
| 13 | 3 | A | 2012-01-10 00:00:00 | -1500 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 |
+----+---------+------+---------------------+--------+
16 rows in set (0.00 sec)
首先，创建一个查询以针对每笔交易获取同一帐户中最近一笔交易的日期":
SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time
ORDER BY t2.date_time;
+----+---------+------+---------------------+--------+---------------------+
| id | account | type | date_time | amount | prev_date |
+----+---------+------+---------------------+--------+---------------------+
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 | 2012-01-02 12:53:10 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 | 2012-01-01 10:01:00 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 | 2012-01-03 17:56:00 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 | 2012-01-03 13:10:01 |
| 8 | 3 | R | 2012-01-05 12:12:00 | 1250 | 2012-01-04 15:13:10 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 | 2012-01-05 12:12:00 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 | 2012-01-06 17:24:01 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 | 2012-01-07 00:00:00 |
| 12 | 3 | A | 2012-01-08 00:00:00 | -1250 | 2012-01-07 05:00:00 |
| 14 | 2 | R | 2012-01-09 00:00:00 | 2000 | 2012-01-04 13:23:01 |
| 13 | 3 | A | 2012-01-10 00:00:00 | -1500 | 2012-01-08 00:00:00 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 | 2012-01-09 00:00:00 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 | 2012-01-11 04:00:00 |
+----+---------+------+---------------------+--------+---------------------+
13 rows in set (0.00 sec)
将其用作子查询，以使每个事务及其前身在同一行上.使用一些过滤来提取我们感兴趣的交易-即，其前身是完全取消的"R"交易的"A"交易-
SELECT
t3.*,transactions.*
FROM
transactions
JOIN
(SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time) t3
ON t3.account = transactions.account
AND t3.prev_date = transactions.date_time
AND t3.type='A'
AND transactions.type='R'
AND t3.amount + transactions.amount = 0
ORDER BY t3.date_time;
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount | prev_date | id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 | 2012-01-02 12:53:10 | 2 | 3 | R | 2012-01-02 12:53:10 | 1500 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 | 2012-01-03 17:56:00 | 4 | 2 | R | 2012-01-03 17:56:00 | 2000 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 | 2012-01-05 12:12:00 | 8 | 3 | R | 2012-01-05 12:12:00 | 1250 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 | 2012-01-09 00:00:00 | 14 | 2 | R | 2012-01-09 00:00:00 | 2000 |
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
4 rows in set (0.00 sec)
从上面的结果可以明显看出，我们已经快到了-我们已经确定了不需要的交易.使用LEFT JOIN，我们可以将它们从整个交易集中过滤掉:
SELECT
transactions.*
FROM
transactions
LEFT JOIN
(SELECT
transactions.id
FROM
transactions
JOIN
(SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time) t3
ON t3.account = transactions.account
AND t3.prev_date = transactions.date_time
AND t3.type='A'
AND transactions.type='R'
AND t3.amount + transactions.amount = 0) t4
USING(id)
WHERE t4.id IS NULL
AND transactions.type = 'R'
ORDER BY transactions.date_time;
+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+
| 1 | 1 | R | 2012-01-01 10:01:00 | 1000 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 |
+----+---------+------+---------------------+--------+
I have a table with transactions:
Transactions
------------
id | account | type | date_time | amount
----------------------------------------------------
1 | 001 | 'R' | '2012-01-01 10:01:00' | 1000
2 | 003 | 'R' | '2012-01-02 12:53:10' | 1500
3 | 003 | 'A' | '2012-01-03 13:10:01' | -1500
4 | 002 | 'R' | '2012-01-03 17:56:00' | 2000
5 | 001 | 'R' | '2012-01-04 12:30:01' | 1000
6 | 002 | 'A' | '2012-01-04 13:23:01' | -2000
7 | 003 | 'R' | '2012-01-04 15:13:10' | 3000
8 | 003 | 'R' | '2012-01-05 12:12:00' | 1250
9 | 003 | 'A' | '2012-01-06 17:24:01' | -1250
and I wish to select all of certain type ('R'), but not those that immediatly (in order of the date_time field) have another transaction of another type ('A') for the same account filed...
So, the query should throw the following rows, given the previous example:
id | account |type | date | amount
----------------------------------------------------
1 | 001 | 'R' | '2012-01-01 10:01:00' | 1000
5 | 001 | 'R' | '2012-01-04 12:30:01' | 1000
7 | 003 | 'R' | '2012-01-04 15:13:10' | 3000
(As you can see, row 2 isn't displayed because row 3 'cancels' it... also row 4 is 'cancelled' by row 6'; Row 7 do appears (even though the account 003 belongs to cancelled row #2, this time in row 7 it's not cancelled by any 'A' row); And row 8 won't appear (it's too for 003 account since now this one is cancelled by 9, which doesn't cancels 7 too, just the previouse one: 8...
I have tried Joins, subqueries in Where clauses but I'm really not sure how do I must make my query...
What I have tried:
Trying joins:
SELECT trans.type as type,
trans.amount as amount,
trans.date_time as dt,
trans.account as acct,
FROM Transactions trans
INNER JOIN ( SELECT t.type AS type, t.acct AS acct, t.date_time AS date_time
FROM Transactions t
WHERE t.date_time > trans.date_time
ORDER BY t.date_time DESC
) AS nextTrans
ON nextTrans.acct = trans.acct
WHERE trans.type IN ('R')
AND nextTrans.type NOT IN ('A')
ORDER BY DATE(trans.date_time) ASC
This throws an error, since I can't introduce external values to the JOIN in MySQL.
Trying subquery in where:
SELECT trans.type as type,
trans.amount as amount,
trans.date_time as dt,
trans.account as acct,
FROM Transactions trans
WHERE trans.type IN ('R')
AND trans.datetime <
( SELECT t.date_time AS date_time
FROM Transactions t
WHERE t.account = trans.account
ORDER BY t.date_time DESC
) AS nextTrans
ON nextTrans.acct = trans.acct
ORDER BY DATE(trans.date_time) ASC
This is wrong, I can get to introduce external values to the WHERE in MySQL but I cannot manage to find the way to filter correctly for what I need...
IMPORTANT EDIT:
I managed to achieve a solution, but it now needs serious optimization. Here it is:
SELECT *
FROM (SELECT t1.*, tFlagged.id AS cancId, tFlagged.type AS cancFlag
FROM transactions t1
LEFT JOIN (SELECT t2.*
FROM transactions t2
ORDER BY t2.date_time ASC ) tFlagged
ON (t1.account=tFlagged.account
AND
t1.date_time < tFlagged.date_time)
WHERE t1.type = 'R'
GROUP BY t1.id) tCanc
WHERE tCanc.cancFlag IS NULL
OR tCanc.cancFlag <> 'A'
I joined the table with itself, just considering same account and great date_time. The Join goes ordered by date_time. Grouping by id I managed to get only the first result of the join, which happens to be the next transaction for the same account.
Then on the outer select, I filter out those that have an 'A', since that means that the next transaction was effectively a cancelation for it. In other words, if there is no next transaction for the same account or if the next transaction is an 'R', then it is not cancelled and it must be shown in the result...
I got this:
+----+---------+------+---------------------+--------+--------+----------+
| id | account | type | date_time | amount | cancId | cancFlag |
+----+---------+------+---------------------+--------+--------+----------+
| 1 | 001 | R | 2012-01-01 10:01:00 | 1000 | 5 | R |
| 5 | 001 | R | 2012-01-04 12:30:01 | 1000 | NULL | NULL |
| 7 | 003 | R | 2012-01-04 15:13:10 | 3000 | 8 | R |
+----+---------+------+---------------------+--------+--------+----------+
It relates each transaction with the next one in time for the same account and then filters out those that have been cancelled... Success!!
As I said, the problem now is optimization. My real data has a lot of rows (as a table holding transactions through time is expected to have), and for a table of ~10,000 rows right now, I got a positive result with this query in 1min.44sec. I suppose that's the thing with joins... (For those who know the protocol in here, what should I do? launch a new question here and post this as a solution to this one? Or just wait for more answers here?)
Here is a solution based on nested subqueries. First, I added a few rows to catch a few more cases. Transaction 10, for example, should not be cancelled by transaction 12, because transaction 11 comes in between.
> select * from transactions order by date_time;
+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+
| 1 | 1 | R | 2012-01-01 10:01:00 | 1000 |
| 2 | 3 | R | 2012-01-02 12:53:10 | 1500 |
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 |
| 4 | 2 | R | 2012-01-03 17:56:00 | 2000 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 |
| 8 | 3 | R | 2012-01-05 12:12:00 | 1250 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 |
| 12 | 3 | A | 2012-01-08 00:00:00 | -1250 |
| 14 | 2 | R | 2012-01-09 00:00:00 | 2000 |
| 13 | 3 | A | 2012-01-10 00:00:00 | -1500 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 |
+----+---------+------+---------------------+--------+
16 rows in set (0.00 sec)
First, create a query to grab, for each transaction, "the date of the most recent transaction before that one in the same account":
SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time
ORDER BY t2.date_time;
+----+---------+------+---------------------+--------+---------------------+
| id | account | type | date_time | amount | prev_date |
+----+---------+------+---------------------+--------+---------------------+
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 | 2012-01-02 12:53:10 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 | 2012-01-01 10:01:00 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 | 2012-01-03 17:56:00 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 | 2012-01-03 13:10:01 |
| 8 | 3 | R | 2012-01-05 12:12:00 | 1250 | 2012-01-04 15:13:10 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 | 2012-01-05 12:12:00 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 | 2012-01-06 17:24:01 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 | 2012-01-07 00:00:00 |
| 12 | 3 | A | 2012-01-08 00:00:00 | -1250 | 2012-01-07 05:00:00 |
| 14 | 2 | R | 2012-01-09 00:00:00 | 2000 | 2012-01-04 13:23:01 |
| 13 | 3 | A | 2012-01-10 00:00:00 | -1500 | 2012-01-08 00:00:00 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 | 2012-01-09 00:00:00 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 | 2012-01-11 04:00:00 |
+----+---------+------+---------------------+--------+---------------------+
13 rows in set (0.00 sec)
Use that as a subquery to get each transaction and its predecessor on the same row. Use some filtering to pull out the transactions we're interested in - namely, 'A' transactions whose predecessors are 'R' transactions that they exactly cancel out -
SELECT
t3.*,transactions.*
FROM
transactions
JOIN
(SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time) t3
ON t3.account = transactions.account
AND t3.prev_date = transactions.date_time
AND t3.type='A'
AND transactions.type='R'
AND t3.amount + transactions.amount = 0
ORDER BY t3.date_time;
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount | prev_date | id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
| 3 | 3 | A | 2012-01-03 13:10:01 | -1500 | 2012-01-02 12:53:10 | 2 | 3 | R | 2012-01-02 12:53:10 | 1500 |
| 6 | 2 | A | 2012-01-04 13:23:01 | -2000 | 2012-01-03 17:56:00 | 4 | 2 | R | 2012-01-03 17:56:00 | 2000 |
| 9 | 3 | A | 2012-01-06 17:24:01 | -1250 | 2012-01-05 12:12:00 | 8 | 3 | R | 2012-01-05 12:12:00 | 1250 |
| 15 | 2 | A | 2012-01-11 04:00:00 | -2000 | 2012-01-09 00:00:00 | 14 | 2 | R | 2012-01-09 00:00:00 | 2000 |
+----+---------+------+---------------------+--------+---------------------+----+---------+------+---------------------+--------+
4 rows in set (0.00 sec)
From the result above it's apparent we're almost there - we've identified the unwanted transactions. Using LEFT JOIN we can filter these out of the whole transaction set:
SELECT
transactions.*
FROM
transactions
LEFT JOIN
(SELECT
transactions.id
FROM
transactions
JOIN
(SELECT t2.*,
MAX(t1.date_time) AS prev_date
FROM transactions t1
JOIN transactions t2
ON (t1.account = t2.account
AND t2.date_time > t1.date_time)
GROUP BY t2.account,t2.date_time) t3
ON t3.account = transactions.account
AND t3.prev_date = transactions.date_time
AND t3.type='A'
AND transactions.type='R'
AND t3.amount + transactions.amount = 0) t4
USING(id)
WHERE t4.id IS NULL
AND transactions.type = 'R'
ORDER BY transactions.date_time;
+----+---------+------+---------------------+--------+
| id | account | type | date_time | amount |
+----+---------+------+---------------------+--------+
| 1 | 1 | R | 2012-01-01 10:01:00 | 1000 |
| 5 | 1 | R | 2012-01-04 12:30:01 | 1000 |
| 7 | 3 | R | 2012-01-04 15:13:10 | 3000 |
| 10 | 3 | R | 2012-01-07 00:00:00 | 1250 |
| 11 | 3 | R | 2012-01-07 05:00:00 | 4000 |
| 16 | 2 | R | 2012-01-12 00:00:00 | 5000 |
+----+---------+------+---------------------+--------+
这篇关于SQL:选择事务不在同一表内的条件的事务的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
