MapReduce Multi-threaded Framework

Overview

Welcome to the MapReduce Multi-threaded Framework! 🚀

This project is all about making big data processing faster and more efficient. By leveraging the power of multi-threading, our framework breaks down large datasets into manageable chunks, processes them in parallel, and then combines the results. Whether you're handling text analysis, large-scale computations, or any task that benefits from parallel processing, this framework is designed to help you get the job done quickly and efficiently.

Authors

• Amitai Turkel

Build Instructions

Static Library

At the heart of this project is the MapReduce framework itself. To make it easy to integrate into your own projects, we've provided a Makefile in the root directory that compiles everything into a static library, libMapReduceFramework.a.

Here’s how you can build the library:

make

This command compiles all the core components of the framework and packages them into a static library that you can link against in your projects. It’s like building a powerful tool that you can reuse anytime you need it!

When you're done or if you want to start fresh, clean up the build artifacts with:

make clean

Client Example

To see the framework in action, we've included a sample client in the SampleClient folder. This client demonstrates how you can use the framework to solve real-world problems.

To try it out:

1. First, navigate to the SampleClient folder:

   cd SampleClient

2. Then, build the client:

   make

3. Run the client to see the magic of multi-threaded MapReduce:

   make run

4. If you need to clean up:

   make clean

This example is a great starting point if you're new to the framework. It shows how to set up a MapReduce job, feed it data, and handle the results—all in a multi-threaded environment.

License

This project is open-source and available under the MIT License.

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Feel free to explore, experiment, and expand on this framework. We're excited to see what you’ll build with it! 😊