I am in need of resetting flag of a table 'A'
from 'X'
to 'Y'
where the update_date of a row satisfies the conditions 1. update_date > 1 month, 2. flag = 'X' & 3. type = 1
.
我需要将表'A'的标志从'X'重置为'Y',其中行的update_date满足条件1. update_date> 1 month,2。flag ='X'&3。type = 1 。
And the update_date is checked against another table 'B'
. I hope the following query will explain what exactly I need. Also this query works fine for me. But the problem is it is taking too long time. Actually my tables A & B
are much bigger almost contains billion rows and there are about 10 columns.
并且对另一个表'B'检查update_date。我希望以下查询能够解释我到底需要什么。此查询也适用于我。但问题是需要花费太长时间。实际上我的表A和B更大,几乎包含十亿行,大约有10列。
When I run my sub query for selecting A.id
I got the result immediately.
当我运行我的子查询选择A.id时,我立即得到了结果。
SELECT a.id
FROM A a
JOIN B b
ON (a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH) tmp_table)
But only the update query even if I put limit also it's taking much time.
但是只有更新查询即使我放了限制也需要花费很多时间。
UPDATE A
SET flag='Y'
WHERE id IN (SELECT a.id
FROM A a
JOIN B b
ON (a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH) tmp_table))
LIMIT 100
I am looking for alternate solutions of my query which makes it fast. Hope I could write a stored procedure for it. But in SP
I should loop through for each target_ids right?
我正在寻找我的查询的替代解决方案,使其快速。希望我能为它编写一个存储过程。但是在SP中我应该为每个target_ids循环一次吗?
I don't wish to write two separate queries in PHP, since there are many threads of my PHP scripts running on cron which returns same results (time latency).
我不希望在PHP中编写两个单独的查询,因为我的PHP脚本中有许多线程在cron上运行,返回相同的结果(时间延迟)。
Also to note, I do have enough indexing for columns.
还要注意,我确实有足够的列索引。
Wish to update limits by limit. ie., update 1000+ records for every run.
希望通过限制更新限制。即,为每次运行更新1000+条记录。
3 个解决方案
#1
3
Change in with exists
改变与存在
EXISTS will be faster because once the engine has found a hit, it will quit looking as the condition has proved true. With IN it will collect all the results from the subquery before further processing.
EXISTS会更快,因为一旦发动机发现了撞击,它就会退出,因为条件证明是正确的。使用IN,它将在进一步处理之前收集子查询中的所有结果。
UPDATE A a
JOIN B b
ON (a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH))
SET a.flag='Y'
ORDER BY a.id LIMIT 1000;
EDITED Supporting substitute of LIMIT (IT will update only 1st 100 records)
EDITED支持LIMIT的替代品(IT将仅更新前100条记录)
SET @rn = 0;
UPDATE A a
JOIN (SELECT @rn:=@rn+1 AS rId, id, name FROM B b
JOIN A a
ON (@rn < 100 AND a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH)
)
) b
ON (a.id=b.id)
SET a.flag='Y'
WHERE b.rId < 100;
Using exist clause
使用exists子句
Update A a
SET a.flag='Y'
WHERE EXISTS (SELECT 1 FROM B b WHERE a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH))
ORDER BY a.id LIMIT 1000;
Hope this helps
希望这可以帮助
#2
0
You can use a join too
您也可以使用联接
UPDATE A
LEFT JOIN (SELECT
a.id
FROM A AS a
JOIN B AS b
ON a.id = b.id
WHERE a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH)) AS l
ON l.id = A.id
SET flag = 'Y'
WHERE id = l.id
#3
0
Finally, I got the better performing optimized query. Simply A join to temp table.
最后,我得到了性能更好的优化查询。简单地加入临时表。
UPDATE A AS a JOIN (
SELECT a.id FROM A AS a JOIN B AS b ON
b.type = a.type
AND b.name = a.name
AND b.last_update_date < DATE_SUB(NOW(), INTERVAL 1 MONTH)
AND a.type = 1
AND a.flag = 'X'
ORDER BY a.id DESC LIMIT 1000)
AS source ON source.id = a.id
SET flag = 'Y';
Thanks to http://www.xaprb.com/blog/2006/08/10/how-to-use-order-by-and-limit-on-multi-table-updates-in-mysql
感谢http://www.xaprb.com/blog/2006/08/10/how-to-use-order-by-and-limit-on-multi-table-updates-in-mysql
#1
3
Change in with exists
改变与存在
EXISTS will be faster because once the engine has found a hit, it will quit looking as the condition has proved true. With IN it will collect all the results from the subquery before further processing.
EXISTS会更快,因为一旦发动机发现了撞击,它就会退出,因为条件证明是正确的。使用IN,它将在进一步处理之前收集子查询中的所有结果。
UPDATE A a
JOIN B b
ON (a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH))
SET a.flag='Y'
ORDER BY a.id LIMIT 1000;
EDITED Supporting substitute of LIMIT (IT will update only 1st 100 records)
EDITED支持LIMIT的替代品(IT将仅更新前100条记录)
SET @rn = 0;
UPDATE A a
JOIN (SELECT @rn:=@rn+1 AS rId, id, name FROM B b
JOIN A a
ON (@rn < 100 AND a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH)
)
) b
ON (a.id=b.id)
SET a.flag='Y'
WHERE b.rId < 100;
Using exist clause
使用exists子句
Update A a
SET a.flag='Y'
WHERE EXISTS (SELECT 1 FROM B b WHERE a.id = b.id
AND a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH))
ORDER BY a.id LIMIT 1000;
Hope this helps
希望这可以帮助
#2
0
You can use a join too
您也可以使用联接
UPDATE A
LEFT JOIN (SELECT
a.id
FROM A AS a
JOIN B AS b
ON a.id = b.id
WHERE a.name = b.name
AND a.type = 1
AND a.flag = 'X'
AND a.update_date > DATE_SUB(NOW(), INTERVAL 1 MONTH)) AS l
ON l.id = A.id
SET flag = 'Y'
WHERE id = l.id
#3
0
Finally, I got the better performing optimized query. Simply A join to temp table.
最后,我得到了性能更好的优化查询。简单地加入临时表。
UPDATE A AS a JOIN (
SELECT a.id FROM A AS a JOIN B AS b ON
b.type = a.type
AND b.name = a.name
AND b.last_update_date < DATE_SUB(NOW(), INTERVAL 1 MONTH)
AND a.type = 1
AND a.flag = 'X'
ORDER BY a.id DESC LIMIT 1000)
AS source ON source.id = a.id
SET flag = 'Y';
Thanks to http://www.xaprb.com/blog/2006/08/10/how-to-use-order-by-and-limit-on-multi-table-updates-in-mysql
感谢http://www.xaprb.com/blog/2006/08/10/how-to-use-order-by-and-limit-on-multi-table-updates-in-mysql