Detailed explanation of concurrency control of distributed transactions implemented by Redis

With the development of Internet applications, distributed systems have become an inevitable trend. In a distributed system, data interaction is required between multiple services, and these data interactions can be viewed as a series of transactions. When multiple services operate on transactions at the same time, concurrency control is required.

Redis is a high-performance key-value database that is widely used in distributed systems. It supports a variety of data structures and commands, including transactions and monitoring, making it a good choice for concurrency control in distributed systems. This article will introduce in detail how Redis implements concurrency control of distributed transactions.

1. Redis transaction

Redis transaction is an atomic operation sequence. These operations can be packaged into a single command and passed to the Redis server for execution in a separate step, which guarantees the atomicity of the transaction. In a Redis transaction, you can use the MULTI command to start the transaction, the EXEC command to submit the transaction, and the DISCARD command to cancel the transaction.

Commands in a Redis transaction can be executed continuously after starting the transaction without sending a request for each command. After the client has executed all commands, it can use the EXEC command to submit commands to the Redis server in batches. If any errors occur during the execution of a transaction, Redis will cancel the transaction and prohibit all modifications. This ensures that all operations in a transaction are executed or none are executed.

2. Redis Monitoring

Redis monitoring is the key to Redis implementing distributed transactions. It uses the WATCH command to monitor one or more keys in the database. In data types such as LIST, SET, ZSET, HASH and STRING, the monitored key must exist. If modifications to these keys occur during monitoring, the transaction will not be successfully committed. During monitoring, the client can use the MULTI command to start another transaction.

For example, the following code uses Redis monitoring:

WATCH balance
balance = GET balance
balance = balance - 10
MULTI
SET balance $balance
EXEC

This code will monitor the key named "balance", use the GET command to obtain data from this key, and then transfer the data Subtract 10. Then use the MULTI command to start the transaction and write the data back to "balance".

If other clients in this transaction also monitor the "balance" key and modify this key before the client executes the MULTI command, then the transaction will fail. If the transaction is successfully submitted, other clients cannot modify the monitored key before all operations included in the transaction are performed in the Redis server.

3. Redis distributed lock

In order to avoid competition and deadlock problems caused by calling Redis monitoring commands on multiple clients at the same time, distributed locks can be used. Redis provides two types of distributed locks: stand-alone locks and cluster locks.

1. Single-machine lock

Single-machine lock is the simplest distributed lock implementation. In a stand-alone lock, you can use the SETNX command to set a key value for locking. For example, the following code uses a stand-alone lock:

SETNX lock_key $current_time

This code will set a value to "lock_key". If this key does not exist before, the setting is successful and 1 is returned. Otherwise, 0 is returned, indicating that the lock failed. During the lock period, other clients cannot modify this key. At this time, the client can perform its own operations. When the client completes the operation, it needs to use the DEL command to release the lock. This will delete "lock_key" and unlock it.

2. Cluster lock

Cluster lock is a more powerful distributed lock implementation. In cluster locks, the Redlock algorithm can be used for multi-node locking. The Redlock algorithm is a distributed lock algorithm based on clock synchronization. In the Redlock algorithm, the client first acquires a lock and uses the current time as the expiration time of the lock. The client also needs to obtain locks from other Redis servers to ensure that this lock is consistent across multiple nodes. During the lock period, clients can perform their own operations. When the client completes the operation, the lock needs to be released. This will remove the lock and remove the lock on all Redis servers at the same time.

4. Summary

In Internet application development, distributed transactions and concurrency control are very important. Redis provides mechanisms such as transactions, monitoring, and distributed locks, making it a good choice for concurrency control in distributed systems. Proficient in these mechanisms can help developers better design and develop distributed systems, and solve distributed transaction and concurrency control issues.

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