Flash Find ⚡: Parallel Search Optimization with Web Workers

This project addresses the performance challenges associated with client-side search operations as the dataset grows or when using complex search algorithms. In scenarios where traditional approaches fail to provide satisfactory performance, this project offers a solution by leveraging web workers for parallel processing.

Problem Statement

You have a client-side search implemented using various search algorithms, which performs well initially. However, as your dataset grows or when dealing with more complex search requirements, performance begins to degrade. Tweaking search options can only provide marginal improvements, and attempts to enhance user experience through techniques like input debouncing prove insufficient. Eventually, the application freezes or becomes unresponsive during search operations, resulting in a degraded user experience.

You are reluctant to abandon search functionality or migrate the client-side search to the server, as these solutions would compromise the user experience or introduce additional complexity and latency. Instead, you seek a solution that allows for efficient client-side search processing without blocking the main thread or sacrificing search capabilities.

Solution

This project offers a solution by utilizing web workers for parallel processing of search tasks. By distributing search operations among multiple worker threads, the application can leverage the computational resources of modern multi-core processors more effectively. This approach allows for faster search performance without blocking the main thread or compromising search capabilities.

Features

• Utilizes web workers to perform search tasks in parallel.
• Dynamically estimates the number of logical cores available on the user's machine.
• Splits the search data into chunks based on the number of available logical cores.
• Distributes search tasks among worker threads for concurrent execution.
• Aggregates search results from multiple worker threads to generate the final result.

Installation

You can install Flash Find via npm: https://www.npmjs.com/package/thunder-search?activeTab=readme

npm install flash-find

Usage

import FlashFind from 'flash-find';

// Define your data source and callback function
const dataSource = [...]; // Your data source
const callback = (result) => { console.log(result); }; // Callback function to handle search results

// Initialize FlashFind
const flash = new FlashFind(dataSource);

// Initialize FlashFind and perform initialization
flash.init(callback);

// Perform search
flash.search("query");

Features

• Lightning-Fast Performance: FlashFind harnesses the power of web workers to execute search operations in parallel, ensuring blazingly fast performance.
• Scalable: Designed to handle large datasets and complex search requirements, FlashFind offers scalable search capabilities for diverse applications.

Contributing

Contributions are welcome! Please feel free to submit bug reports, feature requests, or pull requests via the GitHub repository.

License

This project is licensed under the MIT License - see the LICENSE file for details.