Introduction
This documentation provides a thorough overview of the System Collections Concurrent API. It covers core concepts, key methods, and practical examples for building robust and scalable concurrent systems.
Data Structures
This section outlines several key data structures utilized within the system:
- Linked Lists: Efficient for dynamic data organization and insertion/deletion operations.
- Hash Tables: Optimized for fast lookups based on keys.
- Stacks: Used for managing data in a linear sequence, supporting LIFO and FIFO operations.
- Queues: For processing data in a specific order, useful for task scheduling or event processing.
Concurrency
The System Collections Concurrent API heavily leverages concurrency. Key techniques include:
- Threads: Utilizing threads for parallel execution.
- Asynchronous Operations: Employing asynchronous operations to avoid blocking the event loop.
- Channels: Using channels for communication and data sharing between threads.
Example
Here's a simplified example demonstrating a basic concurrent operation:
```javascript
// This is a simple example demonstrating concurrent processing of two data sets. // Although simplified, it shows the principles of concurrent operations. // The actual implementation should be more complex, utilizing proper thread synchronization. // Consider using a mutex for safe access to shared data. const dataSet1 = [1, 2, 3]; const dataSet2 = [4, 5, 6]; // Simulate some work being performed on each dataset concurrently. setTimeout(() => { console.log("Data Set 1: ", dataSet1); console.log("Data Set 2: ", dataSet2); }, 1000);