How to implement and select distributed locks in Java

Introduction: The importance of distributed locks and common problems and requirements in distributed systems

The importance of distributed locks

In a distributed system, multiple processes or services may need to access and operate shared resources at the same time, such as databases, file systems, etc. If these operations are not controlled, data inconsistency or operational conflicts may result. Distributed locking is a key technology to solve this problem, which ensures that at the same time, only one process or service can perform specific operations.

For example, consider an online store inventory management system, if multiple users try to purchase the last inventory item at the same time, unsynchronized operations can lead to overselling. Using distributed locks ensures that only one operation at a time can modify the inventory quantity, thereby maintaining data accuracy and consistency.

Common problems and requirements in distributed systems

1. Data consistency：

Without proper synchronization mechanisms, updating the same data can lead to inconsistent states.

Distributed locks provide a mechanism to ensure that only one node can operate data at any moment.

2. System performance：

The implementation of distributed locks requires a trade-off between performance and latency.
The implementation of locks should not become a bottleneck in system performance.

3. Fault tolerance and high availability：

In a distributed environment, nodes may fail.
A robust distributed lock system should be able to handle node failures and will not cause lock services to be unavailable for the entire system due to the problem of a single node.

4. Lock management and monitoring：

In complex distributed systems, lock management should be simple and automated, and monitoring mechanisms are required to analyze lock usage and performance bottlenecks.

5. Prevention and resolution of deadlocks：

Deadlocks are common problems in distributed systems, and there are strategies to detect and resolve deadlocks to keep the system running smoothly.

By solving these problems, distributed locks help build a stable, reliable and efficient distributed system.

In the following chapters, we will explore different ways to implement distributed locks and how to choose a lock system suitable for specific application scenarios.

The difference between distributed locks and local locks

1. Scope of action：

Local lock: Usually used in a single process or in a single multi-threaded environment, it is used to control the access to shared resources by different threads within the same process.
Distributed lock: Used to control access to shared resources by multiple processes distributed on different servers or containers.

2. Implementation method：

Local lock: The implementation is relatively simple, such as in JavasynchronizedandReentrantLocketc. These locks rely on the support of the operating system and are only valid within a single JVM.
Distributed lock: The lock state between different nodes needs to be coordinated through the network. Common implementation methods include using external storage or services, such as Redis, Zookeeper or database to store the lock state.

3. Performance and Complexity：

Local lock: Performance is usually higher because they do not involve network communication and the management of locks is done entirely locally.
Distributed lock: Performance may be affected by increased complexity of network latency and lock management (such as acquisition, renewal, release locks, etc.).

4. Reliability and fault tolerance：

Local lock: Low fault tolerance. If the thread or process holding the lock fails, the lock may not be released.
Distributed lock: High availability and fault tolerance are usually considered during design, such as using heartbeat, lock renewal and other mechanisms to deal with node failures that hold locks.

Distributed locks based on database

Implement distributed locking based on database

Database implementation of distributed locks usually relies on atomic operations of the database, such as row locks or the use of specific SQL statements to ensure synchronization.

Implementation method：

Take advantage of unique indexes: The lock can be implemented by trying to insert a key-value pair with a unique index. If the insertion is successful, the lock is acquired; if the unique constraint fails, the lock is acquired.
Use line lock: By locking specific rows in the database, such as usingSELECT FOR UPDATEStatement to prevent other transactions from modifying this line of data.

Sample code(Using MySQL):

-- Try to acquire the lock
INSERT INTO locks (lock_key, lock_status) VALUES ('inventory_lock', 'locked') ON DUPLICATE KEY UPDATE lock_status = 'locked';

-- Release the lock
UPDATE locks SET lock_status = 'unlocked' WHERE lock_key = 'inventory_lock';

Implementation principle

Distributed locks based on databases usually involve using database tables as records of locks.

The acquisition of a lock is achieved by inserting or updating specific records in a table.

If the operation is successful (for example, inserting a row of data), the lock is considered to have been successfully acquired; if the operation fails (for example, because of a unique constraint violation), the lock is considered to have been acquired.

Java code examples

Here is a simple example of a database-based distributed lock implementation using JDBC for database operations:

import ;
import ;
import ;
import ;

public class DatabaseLock {
    private Connection connection;

    public DatabaseLock(Connection connection) {
         = connection;
    }

    public boolean tryLock(String lockId) {
        String sql = "INSERT INTO locks(lock_id, locked) VALUES (?, 1) ON DUPLICATE KEY UPDATE locked = 1;";
        try (PreparedStatement statement = (sql)) {
            (1, lockId);
            int result = ();
            return result == 1;
        } catch (SQLException e) {
            return false;
        }
    }

    public void unlock(String lockId) {
        String sql = "DELETE FROM locks WHERE lock_id = ?;";
        try (PreparedStatement statement = (sql)) {
            (1, lockId);
            ();
        } catch (SQLException e) {
            ();
        }
    }
}

In this example, let's assume there is a name calledlockstable containinglock_idField.tryLockMethod attempts to insert a row of data, iflock_idIf already exists, the record will be updated. If the insertion or update is successful, the lock is considered to be successful.

Pros and disadvantages analysis

advantage：

Simple and easy to implement: Most applications already use databases, so no additional systems or technology stack is required.
Easy to understand: This approach does not require complex external dependencies or additional learning costs.

shortcoming：

Performance issues: Database locks may have a significant impact on database performance, especially in high concurrency scenarios.
Not designed specifically for locks: The database is not optimized for handling lock operations and may not be as efficient as other methods such as Redis or Zookeeper.
Reliability issues: In the event of a database downtime or network problem, the lock status may become uncertain.

Database-based distributed locks are suitable for scenarios where the number of requests is not too high and database dependencies are already present. In systems with high concurrency or latency sensitive, other more specialized distributed lock implementations may need to be considered.

Distributed lock based on Redis

Redis is an in-memory data storage system that supports multiple data structures. Due to its high performance and atomic operation characteristics, it is very suitable for implementing distributed locks.

Implementation method：

SET command: You can use RedisSETCommands and parametersNX(Set keys only if they do not exist) andEX(Set the expiration time of the key) to realize the lock function.

Sample code(Use the Redis command):

# Try to acquire the lockSET lock_key "your_value" NX EX 30
# If OK is returned, the lock setting is successful, otherwise the setting fails.
# Release the lockDEL lock_key

Implementation principle

Redis is a high-performance key-value storage system, and its operations are atomic and are often used to implement distributed locks.

Redis-based distributed locks usually use themSETCommandedNX(Not Exists) andEX(Expire) option to implement.

This method ensures that the lock setting (if the key does not exist) and the timeout setting are atomic operations.

SETNXCommand (has beenSET key value NX EX max-lock-timeInstead) is used to try to set a key, if the key does not exist, the operation is successful (the lock is acquired), otherwise the operation fails (the lock has been held by other clients).
EXPIRESet the expiration time of the key to ensure that even if the holder of the lock fails to release the lock for some reason, the lock will be automatically released after a certain period of time to prevent deadlock.

Java code example usage`Redisson`

RedissonIt is a Java distributed and extensible Java data structure implemented on the basis of Redis. The following is a useRedissonAn example of a Redis distributed lock implemented.

First, you need to add it in the projectRedissonrely:

<!-- Maven dependency -->
<dependency>
    <groupId></groupId>
    <artifactId>redisson</artifactId>
    <version>3.16.4</version>
</dependency>

Then, you can use the following code to acquire and release a distributed lock:

import ;
import ;
import ;
import ;

public class RedisLockExample {
    public static void main(String[] args) {
        Config config = new Config();
        ().setAddress("redis://127.0.0.1:6379");
        RedissonClient redisson = (config);

        RLock lock = ("anyLock");
        try {
            // Try to acquire the lock, wait for up to 100 seconds, and automatically unlock 10 seconds after locking            if ((100, 10, )) {
                try {
                    // Business logic                    ("Lock acquired");
                } finally {
                    ();
                    ("Lock released");
                }
            }
        } catch (InterruptedException e) {
            ().interrupt();
        } finally {
            ();
        }
    }
}

Pros and disadvantages analysis

advantage：

High performance: Redis is based on memory operation and has fast response speed, suitable for high concurrency scenarios.
Lightweight: Compared with database-based locks, Redis implementation is lighter and does not require complex table structures and queries.
Automatic unlocking: By setting the expiration time of the key, you can prevent deadlocks.

shortcoming：

Single point of failure problem: If you use a single Redis node, the lock service may be unavailable due to node failure. While availability can be improved through Redis clusters, implementation and management are relatively complex.
Clock dependency: The implementation of Redis locks depends on time, and if the server clock in the system is not synchronized, it may cause the lock to be released or expired.
No guarantee of fairness of locks: The lock provided by Redisson does not guarantee the fairness of the requested lock and may cause some clients to starve.

Distributed lock based on Zookeeper

Zookeeper is a software that provides coordination services for distributed applications. It provides a tree-shaped directory structure that is very suitable for building distributed locks.

Implementation method：

Create temporary sequential nodes：
The client creates a temporary sequential node for the lock and then checks whether it is the smallest node.
If yes, it means that the lock has been acquired; if not, listen for the deletion event of a closest node smaller than itself, and wait for the lock to be acquired.

Sample code(Using Zookeeper's pseudocode):

// Try to acquire the lockString myNode = ("/locks/my_lock_", null, ACL, CreateMode.EPHEMERAL_SEQUENTIAL);
List&lt;String&gt; nodes = ("/locks", false);
(nodes);
if (("/locks/" + (0))) {
    // Acquisition of lock successfully} else {
    // Wait for the lock to be released}

// Release the lock(myNode, -1);

Implementation principle

Zookeeper is an open source distributed coordination service that provides a tiered service for managing high availability of large numbers of hosts. Zookeeper's data model is similar to a file system and contains nodes (Znodes) that can be persistent or temporary (temporary nodes are automatically deleted at the end of the client session where they are created). Zookeeper-based distributed locks mainly utilize these temporary sequential nodes.

To acquire the lock, the client creates a temporary sequential node under the root node of the lock. The client obtains a list of all child nodes and checks whether the nodes created by itself are nodes with the smallest sequence number. If yes, the client holds the lock; if not, it listens to the deletion event of the closest node with a smaller serial number than itself. This listening implements the client's waiting mechanism.

Java code examples use Curator

First, you need to add the Curator dependency to your project:

<dependency>
    <groupId></groupId>
    <artifactId>curator-framework</artifactId>
    <version>5.1.0</version>
</dependency>
<dependency>
    <groupId></groupId>
    <artifactId>curator-recipes</artifactId>
    <version>5.1.0</version>
</dependency>

Here is a simple example of distributed locks implemented using Curator:

import ;
import ;
import ;
import ;

public class ZookeeperLock {
    private CuratorFramework client;

    public void startClient() {
        client = (
            "localhost:2181", // Zookeeper server address            new ExponentialBackoffRetry(1000, 3) // Retry the policy        );
        ();
    }

    public void lockAndRun() throws Exception {
        InterProcessMutex lock = new InterProcessMutex(client, "/locks/my_lock");
        try {
            if ((10, )) {
                try {
                    // Execute tasks here                    ("Lock acquired, executing task");
                } finally {
                    ();
                }
            } else {
                ("Could not acquire the lock");
            }
        } catch (Exception e) {
            ();
        }
    }

    public static void main(String[] args) throws Exception {
        ZookeeperLock example = new ZookeeperLock();
        ();
        ();
    }
}

Pros and disadvantages analysis

advantage：

reliability: Zookeeper ensures the security and consistency of locks and can work properly even under network partitioning.
Sequence guaranteed: Zookeeper's sequential nodes ensure orderly processing of requests.
Deadlock Avoid: Temporary nodes ensure that the lock will be automatically released when the holder crashes, avoiding the problem of deadlock.

shortcoming：

performance: Zookeeper has lower performance compared to memory-based systems such as Redis because it requires more state and communication.
Complexity: Zookeeper's setup and maintenance are relatively complicated and require appropriate configuration and monitoring.
Resource consumption: Zookeeper client needs to keep a continuous connection with the server, which may consume more system resources.

Selection Guide for Distributed Locks

When choosing the specific implementation of distributed locks, it needs to be decided based on the application requirements, performance requirements, security requirements and the existing technology stack.

The following is a comparison of applicable scenarios, performance and security of different implementation methods, as well as factors that need to be considered in practical applications.

Applicable scenarios for various implementation methods

Distributed locks based on database
- Suitable for scenarios where relational databases have been used and the transaction volume is not particularly high.
- When individual components in a distributed system already depend on the same database, using database locks can avoid the introduction of additional technical dependencies.
Distributed lock based on Redis
- Suitable for scenarios where fast response and high throughput are required.
- Redis-based locking is a good choice when the system requires a high-performance locking mechanism and Redis is already used as a cache or other middleware.
Distributed lock based on Zookeeper
- Suitable for scenarios with extremely high data consistency requirements.
- In distributed systems, if strong data consistency is required, the locking mechanism provided by Zookeeper is very suitable, especially when dealing with complex coordination tasks.

Performance and security comparison

performance:

RedisProvides the fastest lock operation performance and is suitable for high concurrency environments.
ZookeeperIt is inferior to Redis in performance, but provides stronger consistency guarantees.
databaseUsually the performance is lowest, especially in high concurrency scenarios, but may be sufficient for some small-scale or low-concurrency applications.

Security:

ZookeeperProviding strong consistency guarantee is the safest choice among the three.
RedisIn most cases, it is sufficiently secure, but lock failure may occur in extreme cases such as network partitions.
databaseRelying on the transaction and locking mechanism of the database itself is usually more secure, but it needs to be configured and used correctly.

Considerations in practical applications

Technology stack compatibility: Choosing a solution that is compatible with the existing technology stack can reduce learning costs and technical risks.
Deployment and maintenance costs: Considering the deployment and maintenance workload that may be brought about by the introduction of new technologies, choose a solution that is easy to operate and well-supported.
Fault tolerance and reliability: The critical parts of the system require a high-reliability lock mechanism, and select solutions that provide strong consistency and high availability.
Extensibility: As the system scales, the scalability of lock services becomes crucial. Choose lock solutions that can be easily scaled to support higher concurrency and larger data volumes.

Common interview questions

During interviews, questions about distributed locks can help interviewers evaluate candidates’ understanding of concepts such as distributed systems, consistency, and usability. The following are some common distributed lock-related interview questions and their analysis:

1. What is distributed lock? Why are distributed locks needed in distributed systems?

Summary of answers:

Distributed locks are used to manage access to shared resources or services in a distributed system, ensuring that only one process or thread can perform specific operations within the same time.

In a distributed system, since resources may be accessed by multiple nodes at the same time, a distributed lock is required to prevent data competition and ensure the atomicity of operations.

2. Describe the implementation of distributed locks based on Redis and their advantages and disadvantages

Summary of answers:

Redis-based distributed locks are usually usedSETNXCommand to set a lock, which only sets the key when the key does not exist, thus ensuring the uniqueness of the lock. In addition, you can useEXPIREThe command sets an expiration time for the lock to prevent permanent occupation.

advantage:

High performance and high availability.
Simple and easy to use, supports automatic expiration to avoid deadlocks.

shortcoming:

In Redis cluster mode, locks do not have strong consistency.
You need to deal with the life-extending problem of locking the lock due to client crashes.

3. What are the differences between Zookeeper and Redis in distributed lock implementations?

Summary of answers:

Zookeeper implements distributed locks by creating temporary sequential nodes. After the client creates a node, if the node is the smallest node, it acquires the lock; otherwise, it listens for the closest node smaller than itself until it is deleted.

Differences:

Consistency Guarantee:Zookeeper provides strong consistency, while Redis provides final consistency.
Implementation complexity:Zookeeper's lock implementation is relatively complex and requires handling node monitoring and sorting; Redis implementation is relatively simple.
performance:Redis is generally better than Zookeeper in performance, especially in high concurrency scenarios.

4. How to solve the deadlock problem of distributed locks?

Summary of answers:

The deadlock problem can be solved by setting the timeout time of the lock, ensuring that even if the lock holder cannot release the lock due to crash or other reasons, the lock will be automatically released due to the timeout. In addition, releasing the lock using the heartbeat mechanism can prevent the lock from being released early due to network problems.

5. In the implementation of distributed locks, how to ensure the fairness of the lock?

Summary of answers:

To ensure the fairness of locks, usually requires an orderly queue so that the order of requesting locks is consistent with the order of obtaining locks. In Zookeeper, the nature of temporary sequential nodes can be leveraged to achieve fairness; in other systems such as Redis, additional logic may be required to manage queues.

These questions and answers not only cover the basics of distributed locks, but also touch on implementation details and considerations in practical applications, helping to prepare for relevant technical interviews.

6. Deadlock problem and prevention

Definition and reason:A deadlock is a deadlock caused by two or more operating systems' processes competing for resources, and they wait for each other to release resources. In distributed lock environments, deadlocks can occur in situations where network delays, process crashes, or locks are not released correctly.

Preventive measures:

Lock timeout:Set the maximum holding time of the lock, and the lock will be automatically released after the timeout. This can be done by setting the expiration time of the lock, for example, in both Redis and Zookeeper.
Heartbeat mechanism:If the lock supports renewal (such as Redis's RedLock algorithm), the client should periodically send a heartbeat to renew the lock to avoid failing to release the lock due to the client crash.
Detect deadlock:In some systems, the possibility of deadlock can be detected through algorithms. Once the risk of deadlock is detected, the system can actively interrupt certain operations and release the lock.

7. The issue of fairness of locks

Definition and reason:

The fairness of a lock refers to whether the order of requesting the lock is consistent with the order of obtaining the lock. In an unfair lock, new requests may acquire locks before waiting for requests in the queue, which may cause some requests to be unprocessed for a long time.

Solution:

Use fair locks:For example, in JavaReentrantLockIn the class, you can choose fair mode to ensure that the locks are obtained in the order of requests.
Zookeeper implementation:Zookeeper naturally achieves fairness by creating sequential nodes in the lock directory. The client only needs to check whether there are nodes smaller than its own serial number.

8. High availability and fault tolerance

importance:

In distributed systems, high availability and fault tolerance are key indicators for evaluating distributed lock solutions. No failure of the lock service should affect the availability of the entire system.

Improve strategy:

Redundant deployment:Using a Redis cluster or Zookeeper cluster, lock services can be deployed on multiple nodes so that other nodes can take over the functionality if one node fails.
Failover mechanism:Ensure that the system has the ability to automatically detect faults and re-election or switch to a backup system.
Data persistence:For critical data, you should ensure that the state can be restored even after a system crash, such as Redis's AOF (Append Only File) persistence mechanism.

By understanding these common problems and their solutions, a stable and reliable distributed lock system can be better designed and implemented, thereby ensuring the rational allocation and efficient use of resources in a distributed environment.

Summarize

The above is personal experience. I hope you can give you a reference and I hope you can support me more.

How to implement and select distributed locks in Java

Introduction: The importance of distributed locks and common problems and requirements in distributed systems

The importance of distributed locks

Common problems and requirements in distributed systems

The difference between distributed locks and local locks

Distributed locks based on database

Implement distributed locking based on database

Implementation principle

Java code examples

Pros and disadvantages analysis

Distributed lock based on Redis

Implementation principle

Java code example usageRedisson

Pros and disadvantages analysis

Distributed lock based on Zookeeper

Implementation principle

Java code examples use Curator

Pros and disadvantages analysis

Selection Guide for Distributed Locks

Applicable scenarios for various implementation methods

Performance and security comparison

Considerations in practical applications

Common interview questions

1. What is distributed lock? Why are distributed locks needed in distributed systems?

2. Describe the implementation of distributed locks based on Redis and their advantages and disadvantages

3. What are the differences between Zookeeper and Redis in distributed lock implementations?

4. How to solve the deadlock problem of distributed locks?

5. In the implementation of distributed locks, how to ensure the fairness of the lock?

6. Deadlock problem and prevention

7. The issue of fairness of locks

8. High availability and fault tolerance

Summarize

Java code example usage`Redisson`