Zde je řešení založené na vnořených poddotazech. Nejprve jsem přidal několik řádků, abych chytil několik dalších případů. Transakce 10 by například neměla být zrušena transakcí 12, protože transakce 11 je mezi nimi.
> 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)
Nejprve vytvořte dotaz, abyste pro každou transakci získali „datum poslední transakce před transakcí na stejném účtu“:
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)
Použijte to jako poddotaz k získání každé transakce a jejího předchůdce na stejném řádku. Pomocí určitého filtrování vytáhněte transakce, které nás zajímají – jmenovitě transakce „A“, jejichž předchůdci jsou transakce „R“, které přesně ruší –
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)
Z výše uvedeného výsledku je zřejmé, že jsme téměř tam – identifikovali jsme nechtěné transakce. Pomocí LEFT JOIN
můžeme je odfiltrovat z celé sady transakcí:
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 |
+----+---------+------+---------------------+--------+