https://www.cnblogs.com/dengshaojun/p/3955826.html SQL Server processing of concurrency-optimistic and pessimistic locks
If two threads modify the same record in the database at the same time, it causes the latter record to overwrite the previous one, causing some problems.
For example:
A ticketing system has a number of votes, the client every call to the ticket method, the number of votes minus one.
Scene:
A total of 300 tickets, assuming that two tickets, exactly at the same time ticket, they do the operation is first check the number of votes, and then minus one.
General SQL statements:
123456789 |
declare
@
count
as
int begin
tran
select
@
count
=
count
from
ttt
WAITFOR DELAY
‘00:00:05‘
--模拟并发,故意延迟5秒
update ttt
set
count
[email protected]
count
-1
commit
TRAN
SELECT
*
FROM
ttt
|
The problem is that the same time to obtain the remaining tickets are 300, each ticket has done an update to 299 of the operation, resulting in less than 1 of the votes, and actually out of two tickets.
Open two query windows and quickly run the above code to see the effect.
Definition Explanation:
Pessimistic lock: Believe that concurrency is the overwhelming majority, and each thread must achieve the purpose.
Optimistic Lock: Believe that concurrency is very rare, assuming bad luck encountered, give up and return information to tell it to try again. Because it is very rare to happen.
Pessimistic lock Solution:
1234567 |
declare
@
count
as
int
begin
tran
select
@
count
=
count from
tb
WITH
(UPDLOCK)
WAITFOR DELAY
‘00:00:05‘
--模拟并发,故意延迟5秒
update
tb
set
count
[email protected]
count
-1
commit tran
|
An update lock is added to the query to ensure that no dirty data is generated until the transaction ends without being read by other transactions.
To solve the above problems.
Optimistic locking solution:
123456789101112131415161718192021 |
--首先给表加一列timestamp
ALTER
TABLE
ttt
ADD
timesFlag
TIMESTAMP
NOT
null
然后更新时判断这个值是否被修改
declare
@
count
as
int
DECLARE
@flag
AS
TIMESTAMP
DECLARE
@rowCount
AS
int
begin
tran
select
@
count
=
COUNT
,@flag=timesflag
from
ttt
WAITFOR DELAY
‘00:00:05‘
update
ttt
set
count
[email protected]
count
-1
WHERE
[email protected]
--这里加了条件
SET
@[email protected]@ROWCOUNT
--获取被修改的行数
commit
TRAN
--对行数进行判断即可
IF @rowCount=1
PRINT
‘更新成功‘
ELSE
PRINT
‘更新失败‘
|
This is the optimistic locking solution that solves the data error problem caused by concurrency, but does not guarantee that every call to update will succeed and may return ' update failed '
Pessimistic lock and optimistic lock
Pessimistic locks must be successful, but when the concurrency is particularly large, it can cause a long blockage or even timeout, only suitable for small concurrency situations.
Optimistic locks do not always succeed every time, but can take full advantage of the system's concurrency processing mechanism, in large concurrency when the efficiency is much higher.
SQL Server processing for concurrency-optimistic and pessimistic locks