Apache Spark is a powerful distributed computing system that handles large-scale data processing through a framework based on Resilient Distributed Datasets (RDDs). Understanding how Spark partitions data and distributes it via shuffling or other operations is crucial for optimizing performance. Here’s a detailed explanation: Partitions in Spark Partitioning is the process of dividing data into … Continue reading Apache Spark- Partitioning and Shuffling, Parallelism Level, How to optimize these