How does rdd work in spark?
Answer / Ashish Kumar Jaiswal
An RDD (Resilient Distributed Dataset) is a fundamental data structure in Apache Spark, designed to be highly resilient and fault-tolerant. RDDs are distributed collections of objects that can be processed in parallel across multiple nodes in a cluster. They consist of a logical dataset divided into partitions, each partition being stored on one worker node in the cluster. RDDs can be created from Hadoop Distributed File System (HDFS), local file system, or even by transforming other RDDs. Operations on RDDs are lazily evaluated and transformed into a series of tasks that are executed in parallel.
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