Detailed explanation of PHP optimistic locking principle

1. Why do we need locks (concurrency control)?

In a multi-user environment, multiple users may update the same record at the same time, which may cause conflicts. This is the famous concurrency problem.
Typical conflicts are:
1. Lost updates: The updates of one transaction overwrite the update results of other transactions, which is the so-called lost update. For example: User A changes the value from 6 to 2, and user B changes the value from 2 to 6, then user A loses his update.
2. Dirty read: When a transaction reads the records of other half-completed transactions, a dirty read occurs. For example: the values ​​seen by users A and B are both 6, user B changes the value to 2, and the value read by user A is still 6.

In order to solve these problems caused by concurrency. We need to introduce a concurrency control mechanism.

2. Concurrency control mechanism

Lock, that is, lock the target data we selected so that it cannot be modified by other programs.

        1. Pessimistic lock: refers to a conservative attitude towards data being modified by the outside world (including other current transactions of this system and transaction processing from external systems). Therefore, during the entire data processing process, The data is in a locked state
        2. Optimistic locking: Assume that no concurrency conflicts will occur, and only check whether data integrity is violated when submitting the operation. Optimistic locking cannot solve the problem of dirty reads.

3. Implementation of optimistic locking
It is implemented using the data version (Version) recording mechanism. This is the most commonly used implementation method of optimistic locking. What is a data version? That is to add a version identifier to the data, usually by adding a numeric "version" field to the database table. When reading data, read the value of the version field together. Every time the data is updated, the version value is increased by one. When we submit an update, we compare the current version information of the corresponding record in the database table with the version value taken out for the first time. If the current version number of the database table is equal to the version value taken out for the first time, it will be updated. Otherwise, it is considered to be expired data

1. Database table design

task

There are three fields, namely id, value, version

2. Implementation

1) First read the data in the task table (actually there is only one record in this table), and get the value of version as versionValue

2) Every time the value field in the task table is updated, in order to prevent If a conflict occurs, you need to do this

Update task set value = newValue,version = versionValue + 1 where version = versionValue;

Only when this statement is executed will it indicate that the value field is updated this time Value Success

For example, suppose there are two nodes A and B that want to update the value field value in the task table. At almost the same time, the version value read by node A and node B from the task table is 2. Then when node A and node B update the value field value, they both operate update task set value = newValue, version = 3 where version = 2;. In fact, only one node successfully executes the SQL statement. Assuming that node A executes successfully, Then the value of the version field of the task table is 3 at this time. Node B then operates update task set value = newValue, version = 3 where version = 2; this SQL statement will not be executed, thus ensuring that the task table is not updated. A conflict occurs.

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