Скачать или смотреть Efficiently Running Functions in Multi-Threaded Java

Learn how to run functions in Java with `multi-threading` to enhance performance while maintaining synchronized operations.
---
This video is based on the question https://stackoverflow.com/q/74380235/ asked by the user 'Emre Terzi' ( https://stackoverflow.com/u/20142626/ ) and on the answer https://stackoverflow.com/a/74380888/ provided by the user 'Alexander Pavlov' ( https://stackoverflow.com/u/998126/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Run the function in thread(Multi-Thread)

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Efficiently Running Functions in Multi-Threaded Java

In the modern world of software development, managing how your applications handle tasks can greatly affect their performance. One of the prevalent problems encountered by developers, especially when working with large lists of data, is efficiently computing functions that require comparison or analysis—like calculating string similarity. If you've ever found yourself inquiring about how to run such tasks concurrently without conflicts, you're in the right place! In this guide, we'll explore how to implement multi-threading in Java effectively, focusing on synchronizing operations to maintain data integrity.

Understanding the Problem

When trying to measure similarities between strings from a list, the processing can take a considerable amount of time, especially with lengthy data sets. This can result in a sluggish application as each function processes items sequentially. To overcome this, utilizing multi-threading allows for concurrent execution of tasks, speeding up performance.

However, running multiple threads can lead to conflicts, especially when they attempt to access shared resources concurrently. This raises the need for a synchronization mechanism to ensure that each thread can safely perform its task. In this post, we’ll use the ExecutorService combined with a thread-safe queue to achieve our goal.

Solution Overview

1. Set Up Your Environment

First things first, ensure you have a Java environment ready to go. The code we’ll implement makes use of the ExecutorService and ConcurrentLinkedQueue classes from the standard Java library.

2. Import Necessary Classes

At the beginning of your code, you need to include the necessary imports:

[[See Video to Reveal this Text or Code Snippet]]

3. Create the Runnable Task

Here we will define the task that each thread will execute. The task involves fetching strings from a synchronized queue and calculating their similarity ratios:

[[See Video to Reveal this Text or Code Snippet]]

By using poll(), we safely retrieve elements from the queue, ensuring that no two threads pick the same item.

4. Using ExecutorService

To manage our threads, we leverage the ExecutorService. By creating a fixed thread pool, we can manage a set number of threads that will execute our runnable task:

[[See Video to Reveal this Text or Code Snippet]]

By using a fixed pool, we can ensure that no more than 10 threads will run concurrently, allowing for an organized execution while still maintaining speed.

5. Filling the Queue and Invoking the Main Method

Before we kick off our thread pool, we’ll prepare our shared queue with strings we want to work on:

[[See Video to Reveal this Text or Code Snippet]]

Finally, incorporate everything inside your main method:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

By implementing the aforementioned strategies, we've efficiently set up a multi-threaded environment in Java to compute string similarity ratios. This approach not only enhances performance but also ensures the integrity of data through the use of synchronization.

If you're dealing with large datasets and want to optimize your application's performance, remember that multi-threading can be an incredible asset when used correctly. Happy coding!