Multi-node deployment details of Redis implementing distributed transactions

As more and more applications involve high concurrency and massive data storage issues, distributed architecture has become an inevitable choice to solve these problems. In a distributed system, due to the interaction and data collaboration between different nodes, ensuring the data consistency of distributed transactions has become a very critical issue. In the distributed architecture, Redis, as a high-performance NoSQL database, is also constantly improving its distributed transaction mechanism. This article will introduce the details of multi-node deployment of Redis to implement distributed transactions.

As a single-threaded in-memory database, Redis has unique advantages in maintaining high performance under high concurrency. In order to achieve transaction consistency in a distributed system, Redis provides two methods: Pipelined (pipeline) and Transaction (transaction).

A warm reminder that before using Redis to implement distributed transactions, you need to understand the basic operations of Redis transactions. The following briefly introduces the transaction operations of Redis.

In Redis, transactions are executed using MULTI, EXEC, DISCARD, WATCH and other commands. The specific process can be summarized as:

1. Use the MULTI command to start the transaction. At this time, the client enters the transaction queue of the Redis server.
2. Execute multiple Redis commands in the transaction queue. The commands in the queue will not be executed immediately, but will wait for the execution of the EXEC command.
3. Use the EXEC command to submit all Redis commands in the transaction queue. Redis executes all commands in the transaction queue and returns the execution results.
4. Before submitting the EXEC command, if the WATCH command is called, it means that the transaction queue will only be executed when the monitored variables change, otherwise the DISCARD command will be executed.

In Redis distributed transactions, Pipelined is a relatively simple implementation method and is also the method used by most Redis distributed applications.

Pipelined is a bit like non-blocking IO. It executes multiple Redis commands sequentially on the Redis server and continuously returns the results to the client on the last reply. In some simple distributed application scenarios, the implementation of Pipelined will make the development and operation of applications very simple.

Let’s take a look at the code snippet of Pipelined implementation.

Jedis jedis = new Jedis("127.0.0.1", 6379);
Pipeline pipeline = jedis.pipelined();
pipeline.multi();
pipeline.set("key1", "value1");
pipeline.set("key2", "value2");
pipeline.exec();
List<Object> results = pipeline.syncAndReturnAll();
jedis.close();

The above code implements a simple distributed application, which can create two key-value pairs on the Redis server and store them on the Redis server. Finally, since both commands are in a transaction, the Redis server will execute both commands at the same time after receiving the Exec command to ensure data consistency.

However, although Pipelined is simple to implement, its efficiency and transaction consistency under high concurrency cannot meet the needs of distributed systems.

Therefore, using Redis transactions with distributed locks, etc., more complex distributed transaction scenarios can be realized. Let's take a look at the process of implementing distributed transaction operations through Redis Watch.

Jedis jedis = new Jedis("127.0.0.1", 6379);
Transaction tx = jedis.multi();
tx.watch("key1");
tx.set("key1", "value1");
tx.exec();
jedis.close();

The above code snippet implements a Redis transaction with Watch monitoring. Use the watch() method to monitor the Key1 key-value pair. After that, execute the SET command and then commit the transaction. If you want to implement a distributed transaction that requires the cooperation of multiple Redis servers, you need to execute the WATCH command on multiple Redis nodes.

When multiple Redis nodes are involved, they need to be implemented using RedisCluster or Redisson. I will not go into details here.

When performing multi-node deployment, there are many issues that need to be paid attention to. Listed below are some points that require special attention.

1. Modification of configuration file. In a multi-node deployment, the configuration files of different nodes need to be modified accordingly. Especially when deploying Redis Cluster, you need to pay attention to the port settings of the Redis configuration file of each Redis node and the IP address settings of the node.
2. Data synchronization between nodes. When using Redis Cluster or Master-Slave to implement multi-node deployment, data synchronization between nodes needs to be ensured. In a distributed system such as Redis Cluster, data synchronization is completed automatically. However, in an asynchronous replication mode such as Master-Slave, data synchronization needs to be set manually to prevent data inconsistency.
3. Fault handling and recovery. When deploying Redis multi-node, you also need to consider the handling and recovery of node failures. When a Redis node fails, corresponding measures need to be taken, such as restarting the node or redistributing data, etc., to ensure the normal operation of the distributed system.

In short, Redis, as a high-performance NoSQL database, provides developers with convenient and easy-to-use transaction processing and multi-node deployment mechanisms, allowing applications to run more efficiently.

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