#spark-scala

#spark-scala

In this exercise, we will explore the lower-level RDD API in Spark Scala, focusing on implementing a custom partitioner. While the DataFrame API handles partitioning automatically, the ability to customize partitioning using RDDs is crucial for specific scenarios such as co-locating related keys, balancing skewed loads, optimizing reduce-side joins, and controlling task distribution.

Join operations are foundational for data analysis, helping to connect disparate datasets in Spark Scala, which is critical for enhancing business logic and data insights.