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This article mainly introduces "what is idempotency". In daily operation, I believe that many people have doubts about what idempotence is. The editor consulted all kinds of materials and sorted out simple and easy-to-use methods of operation. I hope it will be helpful for you to answer the doubts about "what is idempotence"! Next, please follow the editor to study!

1 idempotent 1.1 definition

The idempotent concept comes from mathematics, which means that the results of N times transformation and 1 times transformation of the data source are the same. In a project, idempotency is used to indicate that the result of a single request or multiple requests made by a user for the same operation is consistent, and there will be no side effects caused by multiple clicks.

Idempotency includes having side effects on resources on the first request, but subsequent requests will no longer have side effects on resources.

Idempotency is concerned with the side effects of subsequent multiple requests on resources, rather than the results.

Issues such as network timeouts are not the scope of idempotent discussion.

Idempotency is a commitment, not realization, of the system service, which promises that as long as the calling interface is successful, the impact of multiple external calls on the system is consistent. Services declared idempotent will assume that external call failures are normal and are bound to be retried after failures.

1.2 scene

During business development, you may encounter situations where the request cannot be received due to network shock, which triggers the retry mechanism, or the front-end jitter causes the form to be submitted repeatedly. For example, in the transaction system, the purchase request submitted by the user has been correctly processed by the server, but the return result of the server has been lost due to network and other reasons, resulting in the client can not know the processing result. If it is on a web page, some inappropriate design may make the user think that the last operation failed, and then refresh the page, which results in the deduction being called twice and the account being deducted one more time. At this point, you need to introduce an idempotent interface.

Let's take MySQL as an example. There is only a third scenario that requires developers to use other strategies to ensure idempotency:

SELECT col1 FROM tab1 WHER col2=2;, which does not change the state no matter how many times it is executed, is a natural idempotent. UPDATE tab1 SET col1=1 WHERE col2=2;-the state is consistent no matter how many times the execution is successful, so it is also an idempotent operation. UPDATE tab1 SET col1=col1+1 WHERE col2=2;-the result of each execution changes, which is not idempotent.

Here's the difference between repeated commit and idempotency:

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Repeated submission means that the service that does not meet the idempotent requirements changes its state many times when the first request has been successfully performed.

Idempotent is more often used when the first request does not know the result (such as timeout) or fails to initiate multiple requests in order to confirm the success of the first request many times, but there will not be multiple state changes due to multiple requests.

1.3 idempotent thinking

The introduction of idempotency makes the server-side logic more complex, and services that satisfy idempotency need to include at least two points in the logic:

First of all, to query the last execution status, if not, it is considered to be the first request.

Ensure the logic of preventing repeated commits before the business logic of the service changes the state.

Idempotency can simplify client logic processing, but it increases the logic and cost of service providers, so whether to use it or not needs to be analyzed according to specific scenarios, so in addition to special business requirements, try not to provide idempotent interfaces.

Additional control idempotent business logic is added, which complicates business functions.

The function of parallel execution is changed to serial execution, which reduces the execution efficiency.

2 idempotent solution 2.1 front-end setting

After the user clicks the submit button, we can set the button to be unavailable or hidden.

The front-end limit is relatively simple, but there is a fatal mistake. If a knowledgeable user repeatedly submits a request by simulating a web page request, the front-end limit is bypassed.

2.2 unique Index

The easiest and most straightforward way to prevent multiple insertions of an order is to create a unique index, and then the statement may be slightly different when inserted. But the purpose is to ensure that there is only one entry for the same record in the database.

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Method 1: add a unique index to the database, and then if you capture the DuplicateKeyException during execution, you will understand that it is caused by repeated insertion, and you can continue to execute the business.

Method 2: use the keyword ON DUPLICATE KEY UPDATE that comes with MySQL to insert if it does not exist and update if it exists. The keyword will not delete the original record.

Method 3: the main role of replace into is similar to INSERT insert operation, and the bottom layer of replace into is to delete data first and then insert data, which will destroy the index and re-maintain the index. Note that you must have a primary key or unique index to be valid, otherwise replace into will only be added.

2.3 deduplicating the meter

The mechanism for deduplicating the table is based on the characteristics of the mysql unique index, and the general process is as follows:

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The client first requests the server, and the server first stores the request information in a deduplicated table of mysql, which creates a unique index or primary key index according to one of the special fields of this request.

Determine whether the insertion is successful, and if the insertion is successful, continue to make subsequent business requests. If the insert fails, it indicates that the current request has been executed.

2.4 pessimistic lock

Method one: simply use Java's own syn or lock locks to achieve idempotency. The core point is to switch the important execution parts from parallel to serial. The disadvantage is that this lock is not available in distributed scenarios because it is cross-JVM! At this point, you need to introduce distributed locks.

Rely on MySQL's own for update to operate the database to achieve serialization. The point here is for update, which is briefly explained:

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When thread An executes for update, the data locks the current record, and when other threads execute this line of code, they wait for thread A to release the lock before acquiring the lock and continuing with the subsequent operation.

When a transaction is submitted, the lock acquired by for update is automatically released.

The disadvantage of this mode is that if the business processing is time-consuming and concurrent, the later threads will be in the waiting state for a long time, occupying a lot of threads, making these threads in the invalid waiting state, while the number of threads in the web service is generally limited, if a large number of threads are in the waiting state due to the acquisition of for update locks, which is not conducive to the concurrent operation of the system.

2.5 optimistic lock

Add a version field to each row of data, which is actually similar to the idea in the second kill design, using the current read update operation that comes with MySQL. When updating the data, first query to get the corresponding version number, and then try the update operation to ensure whether it is a duplicate submission based on whether the return value is 0.

Select id,name,account,version from user where id = 1412; / / suppose the obtained version = 10 update user set account = account + 10 where id = version + 1 where id = 1412 and version = 10

2.6 distributed Lock

Using the setnx operation in Redis, the idempotent guarantee barrier is set in the distributed lock. If setnx succeeds, it means that this is the first time to insert data, then continue to execute the SQL statement. If the setnx fails, it means it has already been executed.

2.7 token scenario

This approach is divided into two stages: the application token stage and the payment stage.

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The first stage: before entering the order submission page, the order system is required to initiate a request for token to the payment system according to the user information. The payment system saves the token to the Redis cache for the second stage of payment.

The second stage: the order system initiates a payment request with the applied token. The payment system checks whether the token exists in the Redis. If so, it initiates the payment request for the first time, and starts payment logic processing after deleting the token in the cache. If it does not exist in the cache, it indicates an illegal request.

In fact, the token here can be thought of as a token, and the payment system confirms the uniqueness of the insertion according to the token. The deficiency of the token model is that it requires two interactions between systems, and the process is more complex than the above method.

At this point, the study of "what is idempotence" is over, hoping to solve everyone's doubts. The collocation of theory and practice can better help you learn, go and try it! If you want to continue to learn more related knowledge, please continue to follow the website, the editor will continue to work hard to bring you more practical articles!

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