Welcome to the SparkR Sample Codes repository! This repository provides a collection of sample codes and scripts to help you get started with SparkR, the R interface for Apache Spark. SparkR allows you to analyze large datasets and perform distributed computing using the familiar R programming language.
This repository is structured to provide simple and complex examples of using SparkR to perform data analysis and machine learning tasks in a distributed computing environment. Whether you're a beginner or an experienced R user, these examples will help you understand how to leverage Spark’s power in R.
To run these examples, you'll need:
- R (version 3.5 or above recommended)
- Apache Spark (version 2.4 or above recommended)
- Intermediate knowledge of R programming
- Familiarity with Spark concepts (optional, but helpful)
Each sample code demonstrates a different SparkR feature or workflow. Here’s an overview:
- DataFrame Operations: Demonstrates how to create Spark DataFrames, perform transformations, and execute actions.
- Data Manipulation: Shows examples of data wrangling, filtering, and aggregations using SparkR.
- Machine Learning: Implements basic machine learning algorithms like linear regression, logistic regression, and clustering using Spark’s MLlib.
- Spark SQL: Illustrates how to use Spark SQL in SparkR for querying and analyzing data.
- Streaming: Provides a simple example of processing streaming data in SparkR.
Contributions are welcome! If you'd like to add new examples or improve the existing ones, feel free to fork this repository, make your changes, and submit a pull request. Make sure your code follows the repository's style and is well-documented.