What are typical application scenarios for Zookeeper? How to implement distributed locks and service registration/discovery?

Answer

Zookeeper has extensive application scenarios in distributed systems, mainly utilizing its coordination and consistency characteristics.

1. Configuration Center

Application Scenarios:

• Centralized application configuration management
• Dynamic configuration updates without service restart
• Configuration isolation across different environments

Implementation:

• Store configurations in persistent nodes
• Use Watcher to monitor configuration changes
• Notify all clients when configuration is updated

Advantages:

• Unified configuration management, avoiding configuration inconsistency
• Supports configuration version control
• Configuration changes take effect in real-time

2. Service Registration and Discovery

Application Scenarios:

• Service governance in microservice architecture
• Service instance registration and deregistration
• Service load balancing

Implementation:

• Service creates ephemeral node when starting
• Ephemeral node automatically deleted when service goes offline
• Clients monitor node changes to get service list

Advantages:

• Automatically sense service instance changes
• No manual intervention required
• Supports health checks

3. Distributed Lock

Application Scenarios:

• Mutual access control across processes
• Resource competition coordination
• Task scheduling

Implementation:

• Create ephemeral sequential node
• Node with smallest sequence number gets the lock
• Other nodes monitor the previous node

Code Example:

java
// Create ephemeral sequential node
String lockPath = zk.create("/lock/lock-", 
    data, 
    ZooDefs.Ids.OPEN_ACL_UNSAFE, 
    CreateMode.EPHEMERAL_SEQUENTIAL);

// Get all lock nodes
List<String> children = zk.getChildren("/lock", false);

// Check if it's the smallest sequence number
if (lockPath.equals("/lock/" + children.get(0))) {
    // Acquire lock
} else {
    // Monitor previous node
    zk.exists("/lock/" + previousNode, watcher);
}

4. Leader Election

Application Scenarios:

• Master node election in master-slave architecture
• Cluster coordination
• Failover

Implementation:

• All nodes create ephemeral sequential nodes
• Node with smallest sequence number becomes Leader
• Other nodes monitor Leader node

Advantages:

• Automatic election without manual intervention
• Automatic re-election when Leader fails
• Guarantees only one Leader

5. Distributed Queue

Application Scenarios:

• Task distribution
• Message queue
• Work queue

Implementation:

• Use persistent sequential nodes to store tasks
• Consumers consume tasks in sequence number order
• Delete node after completion

Types:

• FIFO Queue: First In First Out
• Barrier Queue: Wait for all participants to arrive

6. Naming Service

Application Scenarios:

• Generate globally unique IDs
• Naming in distributed environments
• Resource addressing

Implementation:

• Use persistent sequential nodes
• Node sequence number as unique identifier
• Combine with business prefix to generate business IDs

Advantages:

• Guarantees global uniqueness
• Available in distributed environments
• Good performance

7. Cluster Management

Application Scenarios:

• Cluster member management
• Cluster status monitoring
• Cluster coordination

Implementation:

• Nodes create ephemeral nodes to register
• Monitor node changes
• Count cluster size

Advantages:

• Automatically sense member changes
• Real-time cluster status monitoring
• Supports dynamic scaling

8. Distributed Notification/Coordination

Application Scenarios:

• Inter-system notification
• Collaborative tasks
• Event broadcasting

Implementation:

• Use Watcher mechanism
• Node changes trigger notifications
• Multiple clients monitor the same node

Advantages:

• High real-time performance
• Decouples system dependencies
• Supports one-to-many notifications

Real-world Application Cases

Kafka:

• Uses Zookeeper to store broker information
• Elect Controller
• Store topic and partition information

Hadoop:

• NameNode high availability
• Resource scheduling coordination
• Cluster management

Dubbo:

• Service registry center
• Configuration center
• Service governance

Considerations for Choosing Zookeeper

Applicable Scenarios:

• Need strong consistency
• Read-heavy, write-light
• Small data volume (node count < 100k)
• Need coordination services

Inapplicable Scenarios:

• Massive data storage
• High concurrency writes
• Need complex queries
• Large file storage