Redis realizes consistency and reliability guarantee of distributed transactions

Redis is an open source, high-performance NoSQL database. Due to its fast read and write speed and rich data structure, it is widely used in cache, queues, distributed locks, etc. However, its application in the field of distributed transactions still needs to be further studied. This article will start from the characteristics of Redis and explore how to use Redis to ensure the consistency and reliability of distributed transactions.

1. Data structure features of Redis

Redis supports a wide range of data structures, including strings, lists, hash tables, sets, etc. These data structures have different advantages in different application scenarios. For example, string types can serve as caches, sorted sets can serve as leaderboards, and lists and hash tables can serve as message queues. These data structures can provide us with some conveniences in distributed transaction applications, for example:

1. Transaction atomicity guarantee

Redis supports transactions, and a transaction can include Multiple commands. During transaction execution, if an error occurs, the entire transaction will be rolled back to ensure the atomicity of the transaction.

2. High-speed read and write operations

The read and write speed of Redis is very fast, which is very important for distributed transaction applications that need to read and write data quickly.

3. Message queue feature support

Redis lists and hash tables can be used as message queues. In implementing distributed transactions, these data structures can be used for message delivery. Thereby improving the reliability of the application.

2. How Redis implements distributed transactions

Based on the data structure characteristics of Redis, we can use the following methods to achieve the consistency and reliability of distributed transactions:

1. Transaction caching method

In distributed transaction applications, we usually need to ensure the atomicity of multiple operations. Redis supports transactions and can contain multiple commands in a transaction, which provides the basis for us to ensure atomicity. We can use the Redis transaction cache method to ensure atomicity and reliability.

The specific implementation method is as follows:

(1) Encapsulate multiple operations in one transaction, use the MULTI command to open the transaction, and use the EXEC command to submit the transaction;

(2) ) Use the WATCH command to monitor key data in the transaction. If the key data is modified by other clients, Redis will terminate the execution of the current transaction;

(3) Use Redis's transaction rollback mechanism to ensure the consistency of the transaction .

For example, if we need to transfer 10 yuan from account A to account B, we can use the following command:

WATCH account-A account-B
MULTI
DECRBY account- A 10
INCRBY account-B 10
EXEC

2. Pessimistic locking method

Pessimistic locking is a common locking mechanism, which can ensure that During the lock period, no modification of key data by other clients will occur, thus ensuring data consistency. In Redis, we can use the SETNX command to implement distributed pessimistic locking.

The specific implementation method is as follows:

(1) Use the SETNX command to lock key data. For example, if we need to transfer 10 yuan from account A to account B, we can execute the following command:

SETNX lock true

(2) If the lock is successful, operate the key data; if If locking fails, wait and try again. For example, we can execute the following command:

while (true) {
if (SETNX lock true == 1) {

DECRBY account-A 10
INCRBY account-B 10

}
DEL lock
}

3. Optimistic locking method

Optimistic locking is a relatively lightweight locking mechanism. It does not lock key data, but obtains it before updating the data. The version number of the data (or use information such as a timestamp), and then compare the version number when updating the data. If the version numbers are inconsistent, it means that the key data has been modified by other clients and needs to be retried.

In Redis, we can use the WATCH command and the CAS (Compare and Swap) command to implement optimistic locking.

The specific implementation method is as follows:

(1) Use the WATCH command to monitor key data;

(2) Obtain the version number or timestamp of key data;

(3) Operate key data;

(4) Use the CAS command to compare the version number or timestamp. If they are consistent, submit the operation, otherwise try again.

For example, if we need to transfer 10 yuan from account A to account B, we can execute the following command:

WATCH account-A account-B
versionA = GET account-A- version
versionB = GET account-B-version
account-A = GET account-A
account-B = GET account-B
account-A -= 10
account-B = 10
versionA = 1
versionB = 1
MULTI
SET account-A-version versionA
SET account-B-version versionB
SET account-A account-A
SET account- B account-B
EXEC

3. Redis realizes the consistency and reliability of distributed transactions

In Redis, the following needs to be considered to achieve the consistency and reliability of distributed transactions. Factors:

1. Data synchronization of Redis cluster

Data synchronization is required between different nodes in the Redis cluster to ensure data consistency. We can use Redis's replication mechanism to copy the data from the master node to the slave node. If the master node fails, the slave node can be upgraded to the master node to ensure the availability of the cluster.

2. High availability of Redis cluster

In order to ensure the high availability of Redis cluster, we can use Redis Sentinel to monitor and manage the Redis cluster. Sentinel will monitor the running status of the Redis node and try to automatically repair it when a failure is detected. Specifically, when Sentinel finds that the master node is unavailable, it will coordinate the slave nodes to elect a new master node.

3. Exception handling

When an exception occurs, appropriate handling measures need to be taken. For example, when executing a distributed transaction, if it is found that key data has been modified by other clients, the current transaction needs to be rolled back and re-executed. If there is a node failure in the Redis cluster, a failover is required and automatic repair is attempted. We can use Redis's WATCH command, transaction rollback mechanism, cluster monitoring and management mechanism to handle these abnormal situations.

4. Data backup and recovery

In order to prevent data loss, we can regularly back up the data in the Redis cluster. Backups can be stored on local disk or on a remote server. If data loss or hard drive damage occurs, we can use backup data to restore it.

To sum up, Redis is a high-performance, scalable, and easy-to-use NoSQL database that plays an important role in distributed transaction applications. By rationally utilizing the data structure characteristics of Redis, we can achieve the consistency and reliability of distributed transactions. At the same time, you need to pay attention to technical details such as data synchronization, high availability, exception handling, and data backup of the Redis cluster to ensure the stability and reliability of Redis in distributed transaction applications.

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