Explain partitions.

Partitions are the fundamental units of parallelism in Spark. They represent smaller chunks of data that can be processed independently by different worker nodes in a distributed computing environment. Spark divides datasets into partitions, allowing parallel execution of tasks on multiple partitions across the cluster. Partitions enable efficient data processing by enabling parallelism and minimizing data movement between nodes.