https://github.com/yash1th-yerra/messaging-queue-prototype
https://github.com/yash1th-yerra/messaging-queue-prototype
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/yash1th-yerra/messaging-queue-prototype
- Owner: yash1th-yerra
- Created: 2025-01-02T17:22:30.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-02T17:28:43.000Z (5 months ago)
- Last Synced: 2025-01-02T18:28:56.030Z (5 months ago)
- Language: Java
- Size: 12.7 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
## 1. Key Points:
Multiple Producers and Consumers: Demonstrates scalability by having two producers and two consumers.
Thread Naming: Threads are named (e.g., "Producer-1") for clearer log output.
Thread Joining: The main thread waits for all producer and consumer threads to complete using join().
## 2. Complete Project Structure
For clarity, here's how the project structure looks:
```
messagequeue/
├── Consumer.java
├── Main.java
├── Producer.java
└── SharedResource.java
```
Ensure all classes are in the messagequeue package.
## 3. Sample Output
When you run the MessageQueueExample class, you might see output similar to the following:
```
Producer-1 produced: 101
Consumer-1 consumed: 101
Consumer 1 processed message: 101
Producer-2 produced: 201
Consumer-2 consumed: 201
Consumer 2 processed message: 201
Producer-1 produced: 102
Consumer-1 consumed: 102
Consumer 1 processed message: 102
Producer-2 produced: 202
Consumer-2 consumed: 202
Consumer 2 processed message: 202
Producer-1 produced: 103
Consumer-1 consumed: 103
Consumer 1 processed message: 103
Producer-2 produced: 203
Consumer-2 consumed: 203
Consumer 2 processed message: 203
```
All producers and consumers have finished processing.
Explanation:
- Producers (Producer-1 and Producer-2) produce unique messages (e.g., 101, 201).
- Consumers (Consumer-1 and Consumer-2) consume and process these messages.
- Synchronization ensures that producers wait when the queue is full and consumers wait when the queue is empty.
- Multiple Threads operate concurrently, demonstrating thread-safe message queuing.
## 4. Key Takeaways
- Manual Synchronization: Using synchronized, wait(), and notifyAll() allows precise control over thread communication but requires careful handling to avoid issues like deadlocks.
- Queue Capacity: Limiting the queue size (e.g., MAX_CAPACITY = 5) prevents producers from overwhelming consumers.
- Thread Safety: Ensuring that access to the shared queue is thread-safe is crucial in concurrent programming.
- Scalability: The implementation can be easily scaled to multiple producers and consumers by creating additional threads.
- Graceful Shutdown: Properly handling InterruptedException ensures that threads can be gracefully interrupted and terminated.
## 5. Enhancements and Best Practices
While the above implementation is functional, here are some enhancements and best practices to consider:
- Use notifyAll() Instead of notify():
Ensures that all waiting threads are notified, preventing potential thread starvation.
- Error Handling:
Implement more robust error handling and possibly logging mechanisms for production systems.
- Graceful Shutdown:
Implement mechanisms to gracefully shut down producers and consumers, especially in real-world applications.
- Avoid Busy Waiting:
Ensure that threads don't consume CPU cycles while waiting by properly using wait() and notifyAll().
- Thread Naming and Identification:
Properly name and manage threads for easier debugging and monitoring.
- Use Higher-Level Concurrency Utilities:
For more complex systems, consider using higher-level concurrency utilities from java.util.concurrent like Semaphore, CountDownLatch, or Exchanger.
## 6. Conclusion
This implementation provides a foundational understanding of how message queues work in a multi-threaded environment using basic Java constructs. By manually handling synchronization, producers and consumers can communicate effectively, ensuring that messages are produced and consumed in a thread-safe manner.
For more advanced and scalable applications, leveraging Java's concurrent utilities like BlockingQueue is recommended, as they provide optimized and battle-tested implementations for common concurrency patterns.
Feel free to customize and extend this implementation based on your specific requirements!