Apache Spark is an open-source distributed framework for processing large datasets. It is a cluster computing framework that enables data-intensive applications to be processed in parallel and distributed across multiple nodes. It is designed to be highly scalable and efficient, making it suitable for processing large datasets. Spark can be used for a variety of tasks such as data processing, machine learning, stream processing, graph processing, and much more.
Example:
Let’s say you have a dataset of customer purchase data that you want to analyze. You can use Apache Spark to process this data in parallel and distributed across multiple nodes. Spark will take the data and divide it into chunks, then process each chunk in parallel on different nodes. Once all the chunks have been processed, Spark will combine the results and produce the final output. This allows for faster processing of large datasets.